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Alterra Report1649 - Swap32 Theory description and user manual

1. MANAGEMENT SECTION Ok ck kk kk I ek kk I ke kk kk kk ko kk kk ko kk kk kk kk ko kk kk kk kk kk kk ok IR IO IR IO RR ke Part 1 Harvest swharvest harvest based on DM 1 or date 2 swharvest 2 Switch for kind of harvest 1 2 I E 1 use dry matter threshold 2 use fixed timing dates if swharvest 1 then supply dmharvest2 daylastharvest dmlastharvest and swgrazing see Part 2 if swharvest 2 then supply dateharvest when swharvest 1 then supply dmharvest2 4200 0d0 daylastharvest 366 dmlastharvest 2700 0d0 when swharvest 2 then supply dataharvest dateharvest 06 May 1980 28 May 1980 24 Jun 1980 07 Jun 1984 05 Jul 1984 02 Aug 1984 11 Sep 1984 07 Nov 1984 Alterra Report 1649 update02 283 OK Ck kk kk kk ke kk ke kk ke kk kk kk ke kk RR AR A RA A Part 2 Grazing swgrazing 2 Switch for grazing 1 2 I 1 grazing 2 no grazing if swgrazing 1 then supply Grazingfactor if swgrazing 2 then supply dmharvest2 see Part 1 when swgrazing 1 then supply Grazingfactor 0 1 dmharvestl 1500 0d0 FI IIR I ko kk kk OOOO OOOO I IR IO IR IO IR IO RK Part 3 Nutrients Supply a table with relation between Nutrient supply and dry matter reduction example table is taken from Van der Meer H G Ryden J C Ennik G C 1986 Nitrogen T fluxes in intensive grassland systems Table has 2 columns Nsuptab Nsupply in kg
2. 2 0 5 235 0 04 0 06 0 08 0 1 Static macropore volume cm3 cm 3 0 02 0 1 0 08 Static macropore volume cm3 cm 3 0 04 0 06 0 02 e N 20 00 0000 00O O0O wo yidag 10 110 12 wo yidag 0 25 S 0 75 m 0 25 Sp 0 25 Static macropore volume cm3 cm 3 0 04 0 06 0 08 0 1 0 02 0 0 04 0 06 0 02 iin Lo wo ydaq 0 5 SWpowm 1 4 0 Sp m 0 5 SWpowm 1 0 04 0 06 0 08 0 1 Static macropore volume cm3 cm 3 0 02 9 0 04 0 06 Static macropore volume cm3 cm 3 0 02 O O O eo ou ooocoo e e 9 Y949 wo ydeg 4 0 Sp 0 75 SWpowm 1 m 0 25 SWpowm 1 p S 4 0 m Alterra Report 1649 update02 236 Appendix 4 Partial derivatives of F to pressure heads The coefficients of the Jacobian are given by OF KHE RE hit p pe n OI VAAnarAn P Yaaa AR 1 K K Ok AG cin Az e S 4e Ki id Ki id ohie ari 7 COR P YAAZ qr Az Ya Az Azj41 OK Kp pil p hito am OK Kp pp hi2 K sk on Ya Az _ EUM On Va Az Azizi ek K K 1 j l OR O KE EA n Mn OM Ya Az Azi Oh P CA Azi J K K p J K K p OK OK y Where C is the differential moisture capacity cm 1 2 and on anj the partial derivatives of the internodal conductivity to the pressur
3. Part 3 Initial values TDWI 33 0 Initial total crop dry weight 0 10000 kg ha R LAIEM 0 0589 Leaf area index at emergence 0 10 m2 m2 R RGRLAI 0 01200 Maximum relative increase in LAI 0 1 m2 m2 d R Ck Ck ck ck ck kk ck ck KA KKK KKK KK KK KK KK KK KKK KK KKK KKK KK KK KKK KK KKK KKK kck kck ck ck KKK ck k ck ck ckck ck k ck ck ckck ck ck ck k ck k ck k ck k ck k ck k ck KK KKK KK Ck ck Sk ck KK ck ck KK KA KK KA KK KK KK KK KK KKK KK KKK KK KK KKK KKK KKK KKK KKK KKK KKK KKK ckck ck ck KKK k ck ck ck k ck k ck k ck k ck k ck k ck k ck k ck KKK Part 4 Green surface area 168 Alterra Report 1649 update02 SPA 0 0000 Specific pod area 0 1 ha kg R SSA 0 0000 Specific stem area 0 1 ha kg R SPAN 35 00 Life span under leaves under optimum conditions 0 366 d R TBASE 2 00 Lower threshold temperature for ageing of leaves 10 30 C R List specific leaf area 0 1 ha kg R as function of devel stage 0 2 R DVS SLA maximum 15 records SLATB 0 00 0 0030 1 10 0 0030 2 00 0 0015 End of Table KKK KKK KKK KKK KKK KKK KKK KKK KK KK KKK KKK KKK KK KK KKK KKK KK KKK kckckck kck KKK KKK KKK KKK KK k ck k KKK k ck k ck k ck k ck k ck k ck kckckck ok KKK KKK KKK KKK KKK KKK KKK KK KKK KK KKK KKK KKK KKK KKK KKK KKK KKK kck kck kck KK KKK ckck ck KKK KKK KKK KKK k ck ck ck k ck k ck k ck k ck k ck kck ok Part 5 Assimilation KDIF 1 00 Extinction coefficient for
4. SWSoilShr 2 SwShrInp 1 5 variables required ShrParA to ShrParE z SWSoilShr 2 SwShrInp 2 5 variables required ShrParA to ShrParE ES SWSoilShr 2 SwShrInp 3 4 variables required ShrParA to ShrParD rest dummy ISOILLAY3 SWSoilShr SwShrInp ThetCrMP GeomFac ShrParA ShrParB ShrParC ShrParD ShrParE 1 d 2 0 5001 340 0 343 0 6558 0 0 0 0 0 0 2 1 2 0 3994 3 0 0 343 0 5392 0 0 0 0 0 0 3 1 2 0 3895 3 0 0 415 0 6281 0 0 0 0 0 0 4 1 2 0 3843 3 0 0 400 0 6233 0 0 0 0 0 0 5 1 2 0 3894 3 0 0 412 0 5340 0 0 0 0 0 0 6 1 2 0 4052 3 0 0 406 0 6583 0 0 0 0 0 0 E 1 2 0 4052 3 0 0 446 0 5536 0 0 0 0 0 0 End of Tabel with shrinkage characteristics ZnCrAr 5 0 Depth at which crack area of soil surface is calculated 100 0 cm R Figure 6 7 illustrates a macropore geometry with six domains MB domain four IC sub domains and Ah sub domain In this example Vy at soil surface 0 04 cm cm Pico 0 6 m 0 4 Nam 6 nsa 4 Rzam 0 2 Zay 25 cm and Zi 85 cm Vario at soil surface equals 0 6 x 0 04 0 024 cm cm This volume is equally divided over the nsa 1 sub domains including the Ah sub domain because at soil surface Pa is equal for all five sub domains and amounts to 0 6 5 0 12 Depth zsa of bottom of domains 2 to 6 equals 85 54 2 35 6 26 9 and 25 cm respectively Figure 6 8 presents an example of lumped sub domains 140 Alterra Report 1649 update02 Va cm cm P
5. When the snow option is switched on SWAP simulates snowfall accumulation of snow in a snowpack and the water balance of the snowpack The present approach is quite simple and consists of the more basic processes including a description of the insulating effect of snow on soil temperature Simulation of snowfall and water balance of the snowpack is performed on a daily basis Snowfall and snowpack are described in the next two Sections 10 1 1 Snowfall Snowfall occurs when air temperature drops below a threshold value In that case precipitation falls partly or completely as snow The division of total precipitation P cm d into snow P cm d and rain P cm d depends on the daily average air temperature For air temperatures Tay C below the threshold temperature Tsnow C all precipitation is snow while for air temperatures above the threshold temperature Train C all precipitation is rain Between both threshold temperatures the snow fraction fonow and rain fraction fri of the precipitation are obtained by linear interpolation Jas x 1 for Ta lt Hm 10 1 a Laa DE a for Tao T T 10 1 Lp O for T 2 Toin 10 1 6 res Is Toe 10 1 d dae and qp P 10 1 0 Alterra Report 1649 update02 193 10 1 2 Snowpack Snow that falls on the soil surface is accumulated in a snowpack on condition that the temperature of the soil surface is below 0 5 C The water balance of the snowpack includes storage
6. as function of development stage DVS tcl 0 2 R maximum 7 records DVS tcl Trel 0 0 0 95 2 0 0 95 End of table Depletion of Readily Available Water TCS 2 If TCS 2 specify minimal fraction of readily available water RAW 0 1 R as function of development stage DVS tc2 0 2 R maximum 7 records DVS tc2 RAW 0 0 0 95 2 0 0 95 End of table Depletion of Totally Available Water TCS 3 If TCS 3 specify minimal fraction of totally available water TAW 0 1 R as function of development stage DVS tc3 0 2 R maximum 7 records DVS tc3 TAW 0 0 0 50 2 0 0 50 End of table Depletion Water Amount TCS 4 If TCS 4 specify maximum amount of water depleted below field cap DWA 0 500 mm R as function of development stage DVS tc4 0 2 R maximum 7 records DVS_tc4 DWA 0 0 40 0 2 0 40 0 End of table Pressure head or Moisture content TCS 5 If TCS 5 specify PHORMC 0 Switch use pressure head PHORMC 0 or water content PHORMC 1 DCRIT 30 0 Depth of the sensor 100 0 cm R Also specify critical pressure head 1 d6 100 cm R or moisture content 0 1 0 cm3 cm3 R as function of development stage DVS_tc5 0 2 R DVS tc5 Value_tc5 0 0 1000 0 2 0 1000 0 End of table fixed irrigation time weekly during crop growth TCS 6 If TCS 6 specify Threshold for weekly irrigation only when deficit is higher then threshold irgthre
7. 0 1 0 R kk KR RK RK RK RK RK RK RK KK RK KK KK KK KKK KK KKK ckckckckckck KKK KKK KKK KK KK KKK KKK KKK KKK KK KKK KKK k ck k KKK KK KKK RK RK RK RK RK RK RK RK KK KK KK KK KK KKK KKK KKK KKK KKK KK KK KKK KKK KKK KK KKK KKK KKK ckck ck KKK KKK KKK KKK KKK ck kckckckckck ok Part 115 salt stress linear relation between ECsat and crop reduction ECMAX 1 7 ECsat level at which salt stress starts 0 20 dS m R ECSLOP 12 0 Decline of rootwater uptake above ECMAX 0 40 dS m R non linear relation between salinity concentration and EC C2ECa 4 21 Coefficient a to convert salt concentration to electrical conductivity 0 0 1000 0 R C2ECb 0 763 Coefficient b to convert salt concentration to electrical conductivity 0 0 10 0 R Switch for solute conversion factors for entire profile or per soil layer SWC2ECF 1 1 conversion factors for entire profile 2 conversion factors per soil layer If SWC2ECF 1 specify for entire soil profile C2ECf 1 7 Factor f to account for over saturation of saturated paste 0 0 10 0 R If SWC2ECF 2 specify for each soil layer QC2ECf 1 7 1 7 Factor f to account for over saturation of saturated paste 0 0 10 0 R Kk kk ROO kk kk Ko III I ko Kc ko Kok III KC Kok III Kk ck ck ko K III III II ke IO II oko Kok RR lee KKK KKK KK ck ck ck ck ck ck KK RK KK KK KK KK KK KKK KKK KKK KKK KKK KKK KKK KKK kck ck ck k ck ck ckck ck ck ckck ck ck ckck ck k ck
8. 2 70 depends on the thickness of the top soil compartments Increase of compartment thickness generally results in smaller values for Emax due to smaller hydraulic head gradients For accurate simulations at extreme hydrological conditions the thickness of the top compartments should not be more than 1 cm see Chapter 2 There is one serious limitation of the Emax procedure as described above Emax is governed by the soil hydraulic functions amp h and K It is still not clear to which extent the soil hydraulic functions that usually represent a top layer of a few decimeters are valid for the top few centimeters of a soil which are subject to splashing rain dry crust formation root extension and various cultivation practices Therefore also empirical evaporation functions may be used which require calibration of their parameters for the local climate soil cultivation and drainage situation SWAP has the option to choose the empirical evaporation functions of Black 1969 or Boesten and Stroosnijder 1986 Reduction of soil evaporation according to Black Black 1969 calculated the cumulative actual evaporation during a drying cycle XE cm as E P ae 2 71 where p is a soil specific parameter cm d characterizing the evaporation process and fary is the time d after a significant amount of rainfall P yin SWAP resets tary to zero if the net precipitation Pnet exceeds Pin Reduction of soil evaporation accordi
9. A 000 Vmb 002 Vic 004 B 00 Pm 05 Pic 1 0 20 40 60 Z cm Lu Zic 100 3 100 120 7 120 140 Zst 140 Zst Figure 6 7 Example of macropore geometry with the IC domain partitioned in four sub domains and an Ah sub domain Static macropore volume V left and volumetric proportion P right for MB IC and IC sub domains Vso 0 04 cm cm Pico 0 6 m 0 4 Nam nsa 4 Rzam 0 2 Zay 25 cm and Zi 85 cm Zsa j is bottom of sub domain j Static macropore volume cm3 cm 3 0 0 025 0 05 Depth cm do 100 120 140 160 Figure 6 8 Example of a combination of horizontal and vertical discretisation number of IC sub domains nsa 10 italic figures while resulting total number of domains nam 9 regular figures Former sub domains 3 and 4 are lumped to obtain present domain 4 and former sub domains 6 and 7 are lumped to obtain present domain 6 Vio 0 1 cm3 cm 3 Pico 0 6 m 1 Rzam 0 Zan 720 cm Zic 80 cm Za 120 cm Obtaining parameter values for macropore continuity and distribution Most macropore input parameters are functional parameters with a physical relevancy Information on their values can be derived from field and lab research This especially counts for the depths Zan Zic and Z4 Depth of A horizon Zan may be Alterra Report 1649 update02 141 known from soil map
10. Growth and senescence Plant organ growth is obtained by multiplying the organ growth rate with the fraction allocated to that organ Its total dry biomass dead and alive is obtained by integrating the growth rate over time Subtracting the death rate the integration over time of the net dry matter increase yields the living dry matter weight 270 Alterra Report 1649 update02 W W _ AWn At where Wi Dry matter weight organ i at time step t kg ha AWn Net dry matter growth rate of organ i kg ha d At Times step d i Stems st roots rt leaves lv The dry matter partitioning approach is descriptive the distribution keys are defined as a function of the day number only The influence of environmental factors could be included by applying modification factors to these keys depending on temperature water and nutrient status of the crop and its reserve level In Grass however this is not applied more attention is paid to the crop growth by introducing a death rate for leaves roots and stems respectively For roots and stems the living biomass increase can be determined as the growth rate minus the death rate yielding the net growth rate AWn AW W where AWn Net dry matter growth rate of organ i kg ha d AW Dry matter growth rate of organ i kg ha d Wi Dry matter weight organ i kg ha fi Death rate organ i kg kg d 1 Stems st roots rt Plant organ death is d
11. Some of the macropore inflow is trapped in discontinuous macropores and is therefore forced to infiltrate into the unsaturated matrix at different depths This process is called internal catchment Bouma and Dekker 1978 Van Stiphout et al 1987 The water flow and balance are described in more detail in Section 6 1 2 6 1 1 Macropore geometry In SWAP the geometry of macropore structure is described by characterising the macropore volume according to three main properties 1 Continuity vertical continuity controls flow of water that is taken up at the soil surface to different depths in the profile and horizontal continuity controls exchange of water between macropores Section 6 1 1 1 2 Persistency static macropore volume is permanent while dynamic macropore volume shrinkage cracks depends on soil moisture status Section 6 1 1 2 3 Horizontal distribution in the horizontal plane macropore volume is distributed over cracks and holes The shape of the horizontal cross section of the macropore volume has a large impact on the water exchange between macropore volume and soil matrix and on rapid drainage Section 6 1 1 3 The concept provides a functional rather than a meticulous description of these macropore geometry properties With a limited number of input parameters it determines a functional macropore bottom depth distribution and magnitude and horizontal shape of the macropore volume as a function of depth A basic
12. at the specific depth z Lateral infiltration into and exfiltration out of the saturated matrix qi Lateral infiltration of macropore water into the saturated soil matrix and lateral exfiltration of soil matrix water into the macropores takes place strictly over the depth where stored macropore water is in contact with the saturated matrix This only concerns static macropores below the groundwater table since in the present concept in saturated condition the soil is assumed swollen to its maximum volume without dynamic macropore volume The lateral in and exfiltration rate per unit of depth q i p cm cm d in case of water filled macropores Amp gt 0 is described by Darcy flow similar to Eq 6 32 AAC Asp Fo Awa Eo d o 6 45 pol pol Alterra Report 1649 update02 127 The same shape factor fsnp as in Eq 6 32 is adopted since the same considerations about uncertainties in the exact shape of the soil matrix polygons apply Infiltration occurs if Amp gt Am and exfiltration if Amp lt Amt Exfiltration rate out of the matrix into empty macropores Amp 0 is described as a seepage face d uer cm cm d It is approached with a seepage resistance Yseep d that is based on Ernst s drainage resistance equation Eq 4 16 without term Yent ant Ii dis seep gt 6 36 a Jot Y ver Y hor Y rad D see Y ver K 3 with D Pow a Zseep 6 36 b sat 2 ol Yer gt 6 36 6 SK D seep d
13. for trees in a forest Allen et al 1986 1989 This value is input as is the crop height For a wet bare soil SWAP will assume ro O and crop height Aerop 0 1 cm As Fig 3 3 shows the Penman Monteith method can be applied for the reference grass in combination with crop factors This method has been extensively discussed by Allen et al 1998 In that case SWAP will set rao 70 s m herop 12 cm and a 0 23 as generally defined for the reference grass Table 3 2 shows how the crop factors relate ET and ET to the corresponding values for grass The crop factors belong to a certain crop and depend on its development stage In case of bare soils the crop factor has just one value and is called soil factor The use of a soil factor is optional Without soil factor SWAP will directly calculate Epo with the Penman Monteith method With soil factor SWAP wil relate Epo to the reference evapotranspiration rate calculated with Penman Monteith for grass ETpo grass see Table 3 2 Table 3 1 Three uniform surfaces and its corresponding potential evapotranspiration ET parameter settings for the method Penman Monteith EMT M r crop hierop ay Description of uniform surface ET P sm cm wet canopy completely covering the soil ET input input input dry canopy completely covering the soil ET o input input input wet bare soil Eno 0 0 0 1 0 15 Table 3 2 Options in SWAP to derive potential evapotranspirat
14. 0 0 1000 0 cm R NCOMP number of compartments in this layer HSUBLAY HCOMP 1 MACP I ISOILLAY ISUBLAY HSUBLAY HCOMP NCOMP al 1 10 0 1 0 10 1 y 20 0 5 0 4 2 3 30 0 54 0 6 Z 4 140 0 10 0 14 end of table KKK KKK KKK KKK KKK KKK KKK KKK KKK KK KK KKK KKK KK KKK KKK KKK KKK KKK kckckck ck ckckckckckck ck kckck ck k ck k ck k ckck ckckckokock KKK KKK KK KKK KKK KK KKK KKK KKK KK KK KKK KKK KK KKK KKK KKK KKK KKK KKK KK KKK AK KK KKK KKK k ck ck RRA ckokckokock Part 5 Soil hydraulic functions as table or as function SWSOPHY 0 Switch for use of tables or functions tables 1 functions 0 If SWSOPHY 1 then supply input data for tables FILENAMESOPHY File names with extension of input data A80 FILENAMESOPHY topsoil_sand_B2 csv subsoil_sand_02 csv If SWSOPHY 0 then supply input data for functions Specify for each soil layer maximum MAHO ISOILLAY1 number of soil layer as defined in part 4 1 MAHO I ORES Residual water content 0 0 4 cm3 cm3 R OSAT Saturated water content 0 0 95 cm3 cm3 R ALFA Shape parameter alfa of main drying curve 0 0001 1 cm R NPAR Shape parameter n 1 4 R KSAT Saturated vertical hydraulic conductivity 1 d 5 1000 cm d R LEXP Exponent in hydraulic conductivity function 25 25 R ALFAW Alfa parameter of main wetting curve in case of hysteresis 0 0001 1 cm R H_ENPR Air entry pressure head 40 0 0
15. 1 36 0 00 2 00 0 00 End of table List fraction of total above ground dry matter incr part to the leaves kg kg R as function of development stage 0 2 R DVS FL maximum 15 records FLTB 0 00 0 75 1 00 0 75 1 27 0 00 2 00 0 00 End of table List fraction of total above ground dry matter incr part to the stems kg kg R as function of development stage 0 2 R DVS ES maximum 15 records FSTB 0 00 0 25 14 2 0 25 1 36 0 00 2 00 0 00 End of table List fraction of total above ground dry matter incr part to the st organs kg kg R as function of development stage 0 2 R DVS FO maximum 15 records FOTB 0 00 0 00 1 00 0 00 1 27 0 75 1 36 1 00 2 00 1 00 End of table ck ck ck ck ck ck ck ck ck KKK ce ck ck ck ck KK KKK ck ck ck ck ck ck KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK ko ko kv Part 9 Death rates PERDL 0 030 Maximum rel death rate of leaves due to water stress 0 3 d R List relative death rates of roots kg kg d as function of dev stage 0 2 R DVS RDRR maximum 15 records RDRRTB 0 0000 0 0000 1 5000 0 0000 1 5001 0 0200 2 0000 0 0200 End of table List relative death rates of stems kg kg d as function of dev stage 0 2 R id DVS RDRS maximum 15 records RDRSTB 0 0000 0 0000 1 5000 0 0000 1 5001 0 0200 2 0000 0 0200 End of table KKK KKK KK KK KK KKK KKK
16. 1 4 1 8 1 4 1 7 1 4 1 8 1 4 1 7 1 5 1 7 1 1 1 6 1 0 1 7 1 4 1 6 1 3 1 7 1 3 1 5 1 3 1 6 1 0 1 5 1 0 1 4 1 0 1 6 1 1 1 6 0 1 0 7 0 1 0 6 0 8 1 4 Sand B1 B2 B3 B4 B5 B6 Loam B7 B8 B9 Clay B10 B11 B12 Silt B13 B14 Peat B15 B16 B17 B18 Sand O1 O2 O3 O4 O5 O6 O7 Loam O8 O9 O10 Clay O11 O12 O13 Silt O14 O15 Peat O16 O17 O18 Ores cm cm fO C C o GB BImSImIm o2 E EG 0 01 0 01 0 00 0 00 Ores cm cm OF OSS 7225S SP PPP SBP 6 22 2 5 Osat cm cm 0 43 0 42 0 46 0 46 0 36 0 38 0 40 0 43 0 43 0 43 0 59 0 54 0 42 0 42 0 53 0 80 0 72 0 77 Osat cm cm 0 36 0 38 0 34 0 35 0 32 0 33 0 51 0 47 0 46 0 48 0 42 0 56 0 57 0 38 0 41 0 89 0 86 0 57 Koat cm d 23 41 12 52 15 42 29 22 52 91 100 69 14 07 2 36 1 54 1 70 4 53 5 37 12 98 0 80 81 28 6 79 4 46 6 67 Ka cm d 15 22 12 68 10 87 9 86 25 00 33 92 39 10 9 08 2 23 2 12 13 79 1 02 4 37 1 51 3 70 1 07 2 93 43 45 a cm 0 0234 0 0276 0 0144 0 0156 0 0452 0 0222 0 0194 0 0099 0 0065 0 0064 0 0195 0 0239 0 0084 0 0051 0 0242 0 0176 0 0180 0 0197 cm 2o o 2 2222922 224 213 170 155 521 162 123 136 0094 0097 0191 095 0194 0 0030 0 071 0103
17. 150 843 273 107 192 056 757 SASSWNAN 698 968 430 085 336 363 876 057 QBottom 0 0 000 0 000 0 000 0 0 0 0 000 000 000 000 000 CAAR RONG Alterra Report 1649 update02 25 1 7 Reading guide In the next chapters we discuss subsequently Chapter 2 Soil water flow Chapter 3 Evapotranspiration and rainfall interception Chapter 4 Surface runoff interflow and drainage Chapter 5 Surface water system Chapter 6 Macropore flow Chapter 7 Crop growth Chapter 8 Solute transport Chapter 9 Soil heat flow Chapter 10 Snow and frost Chapter 11 Irrigation The first part of each chapter describes the physical relations incorporated in SWAP This part also describes implemented numerical procedures 1f required to use SWAP in a proper way The second part of each chapter describes the model input If relevant suggestions for input are included The appendices contain information on e Description of the application of the Penman Monteith method e Description of derivation and examples of macropore equations e Equations for the partial derivatives of F to pressure heads e Equations for the implicit linearization of hydraulic conductivities e Equations for the numerical solution of heat flow e Tables with soil hydraulic functions Staring Series 2001 e Tables with critical pressure heads for root water extraction e Tables with salt tolerance data e Tables with shr
18. A6 15 Az Az At p 2 C75 i A6 16 Az AZ j j At Lia Ue er iut A6 17 Az n In case of prescribed temperature Tbot at the soil profile bottom Eq A6 1 transforms to At Tit LUDUM Ne p E er n T ya n l n A5 n bot A6 18 Az Az Az u n which can be written as At At nite At Az AZ n Ve At A5 T Ye Az Az n bot Ver j l j jt jo pitri A E A f SCT Az Az Az Az nt Ve Combination of Eq A6 19 and A6 3 gives the following coefficients AP Lees a A A n Ve eum 46 20 j J At jt At jt B co F n Ve n V Az AZ Az Az A6 21 aut At 41 f CP D AU A ufa eu 46 12 Alterra Report 1649 update02 243 46 19 244 Alterra Report 1649 update02 Appendix 7 Parameters of soil hydraulic functions Staring series After Wosten et al 2001 Sand B1 B2 B3 B4 B5 B6 Loam B7 B8 B9 Clay B10 B11 B12 Silt B13 B14 Peat B15 B16 B17 B18 Sand O1 O2 O3 O4 O5 O6 O7 Loam O8 O9 O10 Clay O11 O12 O13 Silt O14 O15 Peat O16 O17 O18 Dutch nomenclature Zand Leemarm zeer fijn tot matig fijn zand Sterk lemig zeer fijn tot matig fijn zand Sterk lemig zeer fijn tot matig fijn zand Zeer sterk lemig zeer fijn tot matig fijn zand Grof zand Keileem Zavel Zeet lichte zavel Matig lichte zavel Zware zavel Khi Lichte klei Matig zware klei Zeer zware k
19. ALPHAW BETAW 96 0 Tu Res 45 0 Ls y e51 5 1 7 5 66 5 1 7 ES End of table KOK ROK ROK RK RK RK RK RK ck ckckckck ck ck ck ck ckck ck ck ck ck ck ck ck ck ck ck KK KK KK KK RK RK KK KK KR KK RR OR OK OK OK kckck ck ck ck OK OK OK Part 4d table discharge relation If SWOHR 2 and for ALL periods specify IMPER index of management period 1 NMPER I ITAB index per management period 1 10 I HTAB surface water level ALTCU 1000 ALTCU 100 cm R A first value for each period ALTCU 100 cm QTAB discharge 0 500 cm d R E should go down to a value of zero at a level that is higher than the deepest channel bottom of secondary surface water system IMPER 4d IMPTAB HTAB OTAB 1 1 15 0 2 0 End of table KOK ROK ROK RK RK RK RK RK RK ck ckck ck ck ckck ck ck ckck ck ck ck ck ck ck ck ck ckck ck ck KK KK ck ck ckckckck ck ck ck ck ckck ck ck ckck ck KK KK KK KK KK KK KARA 108 Alterra Report 1649 update02 Box 5 6 Automatic and soil moisture controlled Weir management in drainage file DRA Part 4e automatic weir control For the periods when SWMAN 2 specify next two tables Table 41 IMPER index of management period 1 NMPER I DROPR maximum drop rate of surface water level 0 100 cm d positive R if the value is set to zero the parameter does not play any role at all HDEPTH depth in soil profile for comparing with HCRIT 100 0 cm be
20. E 9 16 Ot heat oz This partial differential equation can be solved for simple boundary conditions assuming Dhea constant or very simple functions for Drea Van Wijk 1966 Feddes 1971 Wesseling 1987 A commonly used top boundary condition is a sinusoidally varying soil surface temperature T 0 1 2 T T mean ampl sin Yar e t t 9 17 where Tmean is the mean yearly temperature C Tampi is the wave amplitude C 2n 1 is the angular frequency where 1 is the period of the wave d t is time d starting January 1 and tmax equals when the temperature reaches its maximum In case of a semi infinite soil profile with constant Dy and using Eq 9 17 the solution to Eq 9 16 is e sin a 0 1 tnax ij 9 18 temp T z t T T mean ampl where diemp is the damping depth cm which equals d Dra 9 19 temp m Equation 9 18 can be used for daily or yearly fluctuations Measured values of Dheat for various dry and wet soils are given in Table 9 3 Figure 9 1 gives an example of calculated soil temperatures for a dry and wet sand soil The sinusoidal temperature fluctuations at each depth are reduced in amplitude and delayed in time with respect to the top boundary condition Although the heat capacity of wet sand is higher than of dry sand the temperature wave in the wet sand is less attenuated due to the higher thermal conductivity Alterra Report 1649 upda
21. Fig 3 4 Critical pressure head values of this sink term function for a number of crops are given by Taylor and Ashcroft 1972 see 0 In part 7 also the minimum canopy resistance for the Penman Monteith method should be specified Preferential root water uptake may be described using an input option swroottyp when left out a default value swroottype 1 is assumed Part 8 specifies the parameters which describe the reduction of root water uptake as function of salinity concentrations Fig 3 5 Critical salinity concentrations have been experimentally determined for many crops Maas 1990 0 lists salt tolerance data for a number of crops Interception input data are specified in Part 9 For agricultural crops just one interception coefficient for the Von Hoyningen Hune and Braden concept is required The default value of a 0 25 mm will suffice for most agricultural crops In case of trees and forests Gash concept SWAP requires average rainfall and evaporation fluxes as function of crop development These values are independent of other specified weather data Box 7 1 Crop input data for simple model in file crp ES PLANT GROWTH SECTION ES Part 1 Crop development IDEV 1 length of crop cycle 1 fixed 2 variable If fixed growth length IDEV 1 specify ICC 168 Length of the crop cycle 1 366 days I If variable growth length IDEV 2 specify TSUMEA 1050 0 Temperature sum from eme
22. Hydrol 75 287 299 Jensen M E R D Burman and R G Allen 1990 Evapotranspiration and irrigation water requirements ASCE manuals and reports on enigineering practice 70 ASCE New York 332 pp Jury W A 1982 Simulation of solute transport using a transfer function mode Water Resour Res 18 363 368 Jury W A D Russo and G Sposito 1987 The spatial variability of water and solute transport properties in unsaturated soil II Scaling of water transport Hilgardia 55 33 56 Jury W A W R Gardner and W H Gardner 1991 Soil Physics Fifth edition Wiley New York 330 pp Kabat P B J Broek van den and R A Feddes 1992 SWACROP A water management and crop production simulation model ICID Bulletin 92 vol 41 No 2 61 84 Kaluarachchi J J and J C Parker 1987 Effects of hysteresis with air entrapment on water flow in the unsaturated zone Water Resour Res 23 1967 1976 Kase M and J Catsky 1984 Maintenance and growth components of dark respiration rate in leaves of C3 and C4 plants as affected by leaf temperature Biologia Plantarum 26 461 470 Kim D J 1992 Characterization of swelling and shrinkage behaviour hydraulic properties and modelling of water movement in a physically ripening marine clay soil PhD thesis Catholic University Leuven Kim R 1995 The water budget of heterogeneous areas Doctoral thesis Wageningen Agricultural University Wageningen The Netherlands 182 pp Kool
23. Period 01 Jan 1980 until 31 Dec 1980 Depth soil profile 200 00 cm Water storage Solute storage Final 72 19 cm 0 4570E 02 mg cm2 Initial 72 07 cm 0 0000E 00 mg cm2 Change 0 12 cm 0 4570E 02 mg cm2 Water balance components cm In Out Rain snow e 66 01 Interception i 4 52 Runon z 0 00 Runoff z 0 00 Irrigation 4 0 05 Transpiration 5 25 82 Bottom flux z 0 00 Soil evaporation 14 42 Crack flux 0 00 Drainage level 1 QL ET Sum 66 06 Sum 65 94 In Out Rain 0 0000E 00 Decomposition 0 0000E 00 Irrigation 0 5000E 02 Root uptake 0 0000E 00 Bottom flux 0 0000E 00 Cracks 0 0000E 00 Drainage 0 4300E 01 Sum 0 5000E 02 Sum 0 4300E 01 Output is requested at the end of each month for incremental and cumulative fluxes and at the end of each year for overviews of the water and solute balance Box 1 5 shows the water and solute balance components for the year 1980 The rainfall 66 01 cm is divided over interception 4 52 cm transpiration 25 82 cm soil evaporation 14 42 cm and drainage 21 17 cm The soil water storage increases slightly with 0 12 cm During the experiment a tracer application 500 mg cm has been applied After one year 4 3 mg cm solutes have leached towards the drains the remaining amount 45 7 mg cm is still in the soil profile Alterra Report 1649 update02 23 A more detailed overview of the water balance components is given in the Result blc file Box 1 6 In
24. The moisture transport resistance between the soil and the atmosphere plays also an important role The general consensus is that the major resistance to moisture transport is in the plant in case the soil moisture potential is low in the soil in case the soil moisture potential is high 276 Alterra Report 1649 update02 Root growth is implemented in a straightforward way The vertical root extension rate is equal to the maximum daily increase and cannot exceed the maximum daily rooting depth increase acronym rri G min RD RD RR where G Root growth rate cm d RD Maximum rooting depth cm RD Actual rooting depth cm RR Maximum daily root growth rate cm d The maximum rooting depth is established by selecting the lowest value of the maximum rooting depth determined by the crop acronym rdc the maximum rooting depth determined by the soil acronym rds and the depth the roots would reach in the potential production situation RD max RD min RD RD where RD Maximum rooting depth determined by the soil cm RD Maximum rooting depth determined by the crop cm RD Initial rooting depth cm Root growth continues until the maximum rooting depth is reached The rooting depth can be established by RD RD _ G At where RD _ rooting depth at time step t cm At time step d In theory root growth ceases when no more assimilates are available when an impermeabl
25. Ty eu Wap n for Ta osa 10 4 4 L mertr O for Ta ST 2 10 4 b where C is the heat capacity of water 4180 J kg C Lp is the latent heat of fusion 333580 J kg and Tsnow is the temperature of the snowpack which is set to 0 C The melt fluxes leave the snow pack as infiltration into the soil and or runoff when infiltration capacity of the soil is exceeded Snow can evaporate directly into the air a process called sublimation The sublimation rate E is taken equal to the potential evaporation rate E see Chapter 3 When a snow pack exists the evapotranspiration from the soil and vegetation is set to Zero A snowpack on top of the soil surface has great effect on soil temperature Because of the low thermal conductivity of snow 0 1 0 4 times thermal conductivity of water a snowpack can form a perfect insulating layer that will considerably damp the effects on soil temperature of strong changes in air temperature The insulating effect of a snowpack on soil temperature is accounted for by calculating the temperature at the soil surface the driving force for soil temperature calculations see Chap 9 taking into account the thermal conductivity and thickness of the snowpack Therefore the surface temperature Ty C is calculated as a weighted average derived from the distances from the top of the snow cover and the first soil temperature node to the surface and the respective temperatures of air and soil and therma
26. Water Resour Res 13 348 354 Penning de Vries F W T A H M Brunsting and H H van Laar 1974 Products re quirements and efficiency of biosynthesis a quantitative approach Journal of Theoretical Biology 45 339 377 Penning de Vries F W T J M Witlage and D Kremer 1979 Rates of respiration and of increase in structural dry matter in young wheat ryegrass and maize plants in relation to temperature to water stress and to their sugar content Annals of Botany London 44 595 609 Penning de Vries F W T and H H van Laar 1982 Simulation of growth processes and the model BACROS In Penning de Vries F W T and H H van Laar Eds Simulation of plant growth and crop production Simulation Monographs Pudoc Wageningen The Netherlands p 114 135 Penning de Vries F W T D M Jansen H F M ten Berge and A Bakema 1989 Simulation of ecophysiological processes of growth in several annual crops Pudoc Wageningen the Netherlands 271 pp Penman H L 1948 Natural evaporation from open water bare soil and grass Proc Royal Society London 193 120 146 Philip J R 1957 The theory of infiltration 4 Sorptivity and algebraic infiltration equations Soil Science 84 264 275 Alterra Report 1649 update02 217 Press W H B P Flannery S A Teukolsky and W T Vetterling 1989 Numerical Recipes The art of scientific computing Cambridge University Press 702 pp Priestley C H B and R J Taylor 1972 On
27. Yini and y are the entrance and exit resistance factor per unit drain distance L4 and divided by the wetted perimeter 44 The radial resistance has been lumped with the entrance or exit resistance By assuming a trapezoidal cross section of the water courses the wetted perimeter can be calculated U drain i Wbed i mo 2 9 sur bed D l pA 2 4 6 i i YN Cs i Where w is the channel bed width cm and ay is the slope of the channel bank as sli Another feature of this model option includes the ability to simulate the flooding of the field when the surface water level higher appears to be higher than both the ponding sill and the ponding level or groundwater level Fig 4 7 Surface runoff Flooding ho ho A loaweshold y A No threshold Figure 4 7 In between position of groundwater ponding level hy and surface waterlevel sw in case of surface runoff left and flooding right The model concept for flooding does not take account for the resistance of water flowing on the field surface and an immediate equilibrium between the ponding level and the surface water level is assumed when flooding occurs 84 Alterra Report 1649 update02 4 4 Distribution with depth of drainage fluxes 4 4 1 Implicit approach of travel times In this section the concept for the distribution drainage fluxes with depth as one of the sink terms in the SWAP model is described Although
28. cm macropores that are permanent present The static volume as a function of depth is constant in time 2 Dynamic macropore volume expressed as volume fraction Vay cm cm 1 e shrinkage cracks The dynamic volume as a function of depth is not constant in time The dynamic shrinkage volume is added up to the static volume if present and in this way enlarges the total macropore volume Fig 6 3 The total macropore volume fraction Vinp cm cm is distributed over the two domains according to their volumetric proportion Va V4 E Va 6 6 4 V z P aV mp z Ps V T Vy F V tmb EV ay 6 6 0 Ve PS mp z B V xi V Vic T PVay 6 6 6 This implies that below depth Zic all dynamic volume is part of the MB domain And below depth Z only dynamic volume may occur Static macropore volume The static macropore volume consists of structural shrinkage cracks bio pores e g worm and root holes and macropores that originate from tillage operations Contrary to dynamic macropore volume it is independent of the soil moisture status The volu 116 Alterra Report 1649 update02 Main bypass flow Internal catchment Static 16 172 4 Dynamic 20 15 5 Figure 6 3 Partitioning of static and dynamic macropore volume over the two macropore domains according to the volumetric proportions of the domains Pj 0 25 ratio between MB and IC domains is equal for static and dynamic macropore volume White areas repres
29. position I On top of Pava H A bii M Hooghoudt mogen impervious arain DECUS per Donnan layer 2 T a Asc ope Mond drain 7 with Homogeneous impervious fo equivalent y depth 3 At interf f Two layers ce ur Hooghoudt two soil layers 4 Two layers In bottom Ernst Kiop LLK bor layer 5 Two pane In top layer Ernst Kiop gt gt K por Case 1 Homogeneous profile drain on top of impervious layer The drainage resistance is calculated as LR Y drain Y entr 4 9 4K mprof 9 gwl C drain i Alterra Report 1649 update02 75 with Khprof the horizontal saturated hydraulic conductivity above the drainage basis cm d5 Larain the drain spacing cm and Yent the entrance resistance into the drains and or ditches d The value for can be obtained analogous to the resistance value of an aquitard by dividing the thickness of the channel walls with the permeability If this permeability does not differ substantially from the conductivity in the surrounding subsoil the numerical value of the entry resistance will become relatively minor Case 2 Homogeneous profile drain above impervious layer This drainage situation has been originally described by Hooghoudt 1940 An extension for the entrance resistance has been added later on The drainage resistance follows from Tian Y drain Yen 4 10 8K morof Da 4K prot owl drain m where D is the equivalent depth cm that accounts for
30. retention curve between 1 05 and 0 95 times the h value is approached by a cubic spline for which the parameters are chosen as such that the continuity of both the soil moisture retention curve and the differential moisture capacity function is preserved 2 4 Hysteresis Hysteresis refers to non uniqueness of the O A relation and is caused by variations of the pore diameter inkbottle effect differences in radii of advancing and receding meniscus entrapped air thermal gradients and swelling shrinking processes Hillel 1980 Feddes et al 1988 Gradual desorption of an initially saturated soil sample gives the main drying curve while slow absorption of an initially dry sample results in the main wetting curve In the field partly wetting and drying occurs in numerous cycles resulting in so called drying and wetting scanning curves lying between the main drying and the main wetting curves Fig 2 1 Scanning drying curves Soil water pressure head h Main drying curve Scanning wetting curve Main wetting curve oO O Volumetric water content q gt Figure 2 1 Water retention function with hysteresis showing the main wetting main drying and scanning curves Alterra Report 1649 update02 29 In simulation practice often only the main drying curve is used to describe the O A relation This is mainly due to the time and costs involved in measurement of the complete 0 7 relationship
31. see Par 5 1 2 1 3 For a soil moisture controlled weir the discharge follows simply from the water balance equation as given by Eq 5 4 with asup Set to Zero and the storage V set equal to the storage for the target level The discharge q is then the only unknown left and can be solved directly 98 Alterra Report 1649 update02 5 1 1 Multi level drainage with imposed surface water levels SWAP comprises an option for imposing a surface water level time series to be used as drainage level time series When using this option it is assumed that the surface water level is equal for all drainage systems Surface waters associated to the different drainage systems have open connections to each other and conduit resistances are neglected This results to only one overall surface water level The number of drainage systems to account for depends on the position of the groundwater level and the surface water level relative to the channel bed level 5 1 2 Multi level drainage with simulated surface water levels Another option in the SWAP model is to simulate the surface water level on the basis of the control unit surface water balance Then the discharge is governed by a either a fixed weir or an automated weir The user can specify different water management periods for which the settings of the weirs can be different During each time step SWAP determines in subsequent order 1 the target level 2 whether the target level is r
32. 0 avg Q drain i darain 2 i l Y drain i 5 5 where the drainage level Parani is in this case equal to the channel bed level zy When the groundwater level is situated above the highest bed level and with the surface water level is below the lowest one the total drainage flux If the surface water level tends to rise to levels higher than the channel bed level Zpeqj the latter is replaced by the surface water level Calculation of the discharge rate q is the last step in solving Eq 5 4 1 If the supply rate q takes a positive value the discharge is set to zero The calculation of the supply rate is based on the comparison the target level and that actual surface water level After establishing a target level it is examined whether the surface water level can take the target value If necessary surface water supply is used to attain the target level The water supply should meet to the following criteria a The supply rate should not exceed a user defined value of the maximum supply rate bras b Water supply only occurs when the surface water level takes a value below the water supply level This water supply level is defined as a tolerance value in relation to the target level 2 For the fixed weir the discharge follows from the iterative procedure to establish a target level from the stage discharge relationship This relationship can either be expressed in tabulated form or as a power function for weir flow
33. 0 d0 100 d0 cm R AVEVAP average evaporation intensity during rainfall from a wet canopy 0 d0 10 d0 cm R OR OR X X X X T PFREE PSTEM SCANOPY AVPREC AVEVAP 0 0 0 9 0 05 0 4 6 0 1 5 365 0 0 9 0 05 0 4 6 0 1 5 End of table KKK KKK KKK KKK KKK KKK ck ck KKK ck ck ck ck ck KKK KKK KKK KKK KKK KKK KKK KKK KK KK KKK KKK KAKA KKK KKK ck ck ckckck k ck k ck k ck k ck kck k ck kckckckok KKK KKK KKK KK RA KA KKK KK KKK ck ck ck KKK KKK KKK KKK KKK KKK KKK KK KK KKK KKK KKK KKK KKK KKK KK ck ck ck k ck ck ck k ck ck ck k ck k ck k RARA RARA Part 10 Root density distribution and root growth List relative root density 0 1 R as function of rel rooting depth 0 1 R Rdepth Rdensity maximum 11 records RDCTB 0 00 1 00 1 00 0 00 End of table KKK RK RK RK RK RK KK RK RK RK KK RK RK RK KKK KKK KKK KKK ck ck kckck ck k ck k ck k KKK k ck k ck k ck k ck k ck k ck k ck k ck kck kckokock 166 Alterra Report 1649 update02 7 4 2 Detailed crop module Input of the detailed crop module has been divided in 13 parts 1 Crop factor of crop height Crop development Initial values Green surface area Assimilation Conversion of assimilates into biomass Maintenance respiration Partitioning SO 9 ICQ YA Pe Ss Death rates Crop water use m Salt stress N Interception W Root growth and root density profile An example of the input file is given in Box 7 2 In general t
34. 12 and the extinction coefficient of the diffuse flux component Kait might be calculated as Kait Ka yl O bear 7 13 In Eq 7 12 the factor 0 5 represents the average projection on the ground surface of leaves showing a spherical angle distribution Averaging 0 5 sinp during a day with an overcast sky gives a value of Kair 0 8 The value of Kaip can be measured directly under completely overcast sky conditions when only diffuse radation reaches the canopy The average value is about 0 72 Goudriaan 1977 In many situations the leaf angle distribution is not spherical Therefore in WOFOST the actual leaf angle distribution is accounted for by using a so called cluster factor which is the measured extinction coefficient for diffuse radiation relative to the theoretical one for a spherical leaf area distribution On its way through the canopy part of the direct flux is intercepted and scattered by the leaves Hence the direct flux segregates into a diffuse scattered component and another component which remains direct Attenuation of the remaining direct component proceeds like in a hypothetical canopy of black non scattering leaves The diffuse component is obtained as the difference between the total direct flux and its direct component The rate of light absorption at depth L in the canopy PAR J m leaf d is obtained by taking the derivative of Eq 7 11 with respect to L PAR k 1 p PARe
35. 1649 update02 order if their role as part of the surface water system is being considered When considering their drainage characteristics we will refer to them in terms of their level The SWAP model has the option for specifying resistances for calculating the sub irrigation flux that differ from the resistance values used for drainage An additional model option involves the limitation of the sub irrigation rate by defining the groundwater level ome at which the maximum sub irrigation rate is reached Such a limitation is needed because the sub irrigation rate does not increase infinitely when the groundwater level lowers q drain 0 Soil surface Q avg drain ddrain 0 avg Y drain Drainage base drain E Pave Parain darain Vint Groundwater level at which max infiltration rate is reached min 9 avg drain Y int Qdrain Figure 4 5 Lineair relationships between drainage Gdrain gt 0 and infiltration qq 44 lt 0 flux and mean groundwater level dayg 4 3 4 Regional scale drainage relation defined by a tabulated function An example of a non linear relation between discharge and groundwater elevation resulting from an analysis of observed field data is presented in Fig 4 6 Massop and De Wit 1994 It can be seen from this figure that the non linear relation may be linearized to a piece wise linear relation in which each part of this relation cor
36. 1649 update02 167 Boons Prins et al 1993 documented specific parameters for the crops winter wheat grain maize spring barley rice sugar beet potato field bean soy bean winter oilseed rape and sunflower WOFOST input files for these crops will be provided with the SWAP program Box 7 2 Crop input data for detailed model in file crp KKK KKK KKK KKK KKK KKK KKK KKK KK KKK KK KK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK ck kckck ck ck KKK k ck ck ck k ck kck k ck k ck k ck k ck kck KK KKK PLANT GROWTH SECTION KK KK KK KKK KKK KKK KKK KKK KKK KK KKK KKK KKK KKK KKK KK KKK KK KKK KKK KKK KKK KKK KKK KKK KKK KKK ck k ck k ck k ck k ck k ck k ck k ck KK KKK Part 1 Crop factor or crop height SWCF 1 choice between crop factor 1 or crop height 2 Choose crop factor if ETref is used either from meteo input file SWETR 1 or with PM Choose crop height if PM should be used with actual crop height albedo and resistance If SWCF 1 list crop factor CF 0 5 1 5 R as function of dev stage DVS 0 2 R If SWCF 2 list crop height CH 0 1000 cm R as function of dev stage DVS 0 2 R maximum 36 records DVS CH CF 0 0 1 0 1 0 1 0 40 0 1 1 2 0 50 0 gl End of Table If SWCF 2 list crop specifi values for ALBEDO 0 23 crop reflection coefficient 0 1 0 R RSC 70 0 Minimum canopy resistance 0 10 6 s m R KKK KKK KKK KKK KK KKK KKK KK KKK KKK KKK KKK KKK KKK KKK KKK
37. C Conversion efficiency factor of assimilates total crop kg kg Coi Conversion efficiency factor of the assimilates of a specific organ kg kg pci Partitioning factor of organ i kg kg 1 Leaves lv stems st rt roots 268 Alterra Report 1649 update02 The total crop dry matter growth rate can be calculated as AW C R where AW _ Dry matter growth rate total crop kg ha d Ce Conversion efficiency factor of assimilates total crop kg kg Rg Growth respiration rate kg ha d Dry matter partioning The dry matter partitioning is calculated in two steps First the total available assimilates are distributed over the roots and the above ground plant parts i e leaves and stems AW pc AW AW pc AW where AW _ Dry matter growth rate total crop kg ha d AW Dry matter growth rate roots kg ha d AW Dry matter growth above ground plant parts kg ha d pen Partitioning factor of roots kg kg In a second step the leaf and stem growth rates are calculated as the product of the above ground dry matter growth rate and the fraction allocated to these organs AW pc AW where AW Dry matter growth rate of organ i kg ha d AW Above ground dry matter growth kg ha d pci Partitioning factor of organ i kg kg 1 Leaves lv stems st The partitioning factors are a function of the day number An AFGEN function with the day number as the independent var
38. Dirksen C 1987 Water and salt transport in daily irrigated root zone Neth J Agric Sci 35 395 406 Alterra Report 1649 update02 211 Dirksen C 1991 Unsaturated hydraulic conductivity In Soil analysis physical methods K A Smith and C E Mullins eds Marcel Dekker New York p 209 269 Dirksen C J B Kool P Koorevaar and M Th van Genuchten 1993 Hyswasor simulation model of hysteretic water and solute transport in the root zone In D Russo and G Dagan Eds Water flow and solute transport in soils Springer Verlag Adv Series in Agric Sci 20 99 122 Dirksen C and S Matula 1994 Automatic atomized water spray system for soil hydraulic conductivity measurements Soil Sci Soc Am J 58 319 325 Doorenbos J and W O Pruitt 1977 Guidelines for predicting crop water requirements Irrigation and Drainage Paper 24 FAO Rome Italy Doorenbos J and A H Kassam 1979 Yield response to water FAO Irrigation and Drainage Paper 33 FAO Rome Italy Elrick D E and W D Reynolds 1992 Infiltration from constant head well permeameters and infiltrometers In Advances in measurement of soil physical properties bringing theory into practice G C Topp W D Reynolds and R E Green eds SSSA special publication no 30 p 1 24 Ernst L F 1956 Calculation of the steady flow of groundwater in vertical cross sections Netherlands Journal of Agricultural Science 4 126 131 Ernst L F 1962 Gro
39. Drain spacing 1 1000 m R Specify drainage flux Qdrain 100 1000 cm d R as function of groundwater level GWL 1000 0 10 0 cm R negative below soil surface maximum of 25 records start with highest groundwater level GWL Odrain 20 0 0 5 100 0 1 End of table KK OK ROK ROK ROK ROK RK ck ckckckck ck ck ckckckck ck ck ck ck ck ck ck ck ck ck KK KK KK RK RK KK KK RK ck ck ckckckckckckckckckckckckckckckckckck ck ck k ck ck ckckckckok 92 Alterra Report 1649 update02 The input requirements for the simulation of multi level drainage given in Box 4 5 for a basic system with fixed resistances and imposed levels In Box 4 6 the requirements are given for an extended system with surface water dependent resistances and simulated drainage levels Up to five different drainage levels can be specified For each level the user can specify whether drainage or infiltration or both are allowed Both the drainage and infiltration resistance needs to be specified by the user In case of sub irrigation the entrance resistance then denoted as Yint can be either higher or lower than that for drainage Jain depending on local conditions A substantial raising of the surface water level can for instance result in infiltration through a more conductive bio active zone which will reduce the entrance resistance In most situations with sub irrigation the radial resistance will be higher than with drainage because the wetted section of t
40. Grain crops Corn vegetative period during ripening Small grains vegetative period during ripening Seed crops Alfalfa prior to bloom during bloom during ripening Carrots at 60 cm depth Onions at 7 cm depth at 15 cm depth Lettuce during productive phase Azn 500 500 400 1000 200 350 800 300 500 8000 400 8000 2000 4000 8000 4000 4000 1500 3000 247 800 500 500 1000 300 450 1500 1500 500 12000 500 12000 248 Alterra Report 1649 update02 Appendix 9 Salt tolerance data After Maas 1990 Crop common name Fiber and grain crops Barley Bean Corn Cotton Peanut Rice paddy Rye Sorghum Soybean Sugar beet 7 Sugar cane Wheat Wheat durum Grasses and forage crops Alfalfa Barley forage Bermuda grass Clover ladino Corn forage Cowpea forage Ryegrass perennial Sundan grass Wheat forage Wheat durum forage Vegetables and fruit crops Bean Beet red f Broccoli Cabbage Carrot Corn sweet Cucumber Lettuce Onion Potato Spinach Tomato Crop botanical name Hordeum vulgare Phaseolus vulgaris Zea mays Gossypium hirsutum Arachis hypogaea Oryza sativa Secale cereale Sorghum bicolor Glycine max Beta vulgaris Sacharum officinarum Triticum aestivum Triticum turgidum Medicago sativa Hordeum vulgare Cynodon dactylon Trifolium repens Zea mays Vigna unguiculata Lolium perenne Sorgh
41. ICI ICI OOOO III GIGI III III III III III III RII Ra ak FI I I I I ke I kk ke kk kk I ke kk kk ko kk kk kk I III I IO IR IO IR IO RR I RR RAR Part 8 Death rates PERDL 0 0500 Maximum rel death rate of leaves due to water stress 0 3 d R List relative death rates of roots kg kg d as function of daynumber 1 366 d R DNR RDRR maximum 15 records RDRRTB 1 0 0 0 180 0 0 02 366 0 0 02 death rate stems and roots van 0 0 op 0 02 gezet End of table List relative death rates of stems kg kg d as function of daynumber 1 366 d R DNR RDRS maximum 15 records RDRSTB 1 0 0 0 180 0 0 02 366 0 0 02 death rate stems and roots van 0 0 op 0 02 gezet End of table FEI III III III III IIIS III ISIC IIIS IIIS III III III III III I I Ik OK kk kk I I kk OOOO II I III II I IO IIR IO IR IO A ROR IO A eee Part 9 Crop water use Switch for concept root water extraction swroottyp 1 1 Macroscopic concept Feddes et al 1978 1 2 Microscopic concept De Jong van Lier et al 2008 if swroottyp 1 specify HLIM1 0 0 No water extraction at higher pressure heads 100 100 cm R HLIM2U 1 0 h below which optimum water extr starts for top layer 1000 100 cm R HLIM2L 1 0 h below which optimum water extr starts for sub layer 1000 100 cm R HLIM3H 300 0 h below which water uptake red starts at high Tpot 10000 100 cm R HLIM3L 300 0 h below which water uptak
42. Isubl have a value of 0 when snow processes were not simulated This 0 value instead of 99 9 value is applied to facilitate uniformity of water balance calculations The description given in these pages uses the following symbols Unit units as applied in these output files units mostly differ from those applied in Swap Range upper and lower boundary of given data R an asterisk indicates that data are written to a new record DT data type R means Real 4 I means Integer 2 C means CharacterString Mnemonic the name of the variable as applied in the source code of Swap Description of variable Unit Range R DT Mnemonic Headerof 5 records each records with a fixed length of 80 characters Project Name gt os 5 C80 Project example Project CranGras File Content 5 HE x C80 FilText example File content formatted hydrological data File Name 5 E C80 FilNam example File name Result bfo Model Version n C80 Model ID example Model version SWAP3 0 0 Date and time of file creation j kis d C80 DTString example Generated at 28 Mar 2003 13 59 31 File Options SWitch for OPtions of content of this file shaded parts in this table 1 2 5 l swop SwOp 1 no data of macro pore flow SwOp 2 data of macro pore flow in this table shaded and red Time domain Year when hydrological simulation started ft S l bruny Year when hydrological
43. J and S P Neuman 1986 Estimation of aquifer parameters under transient and steady state conditions 2 Uniqueness stability and solution algorithms Water Resour Res 22 211 27 Carsel R F and R S Parrish 1988 Developing joint probability distributions of soil water characteristics Water Resour Res 24 755 769 Causton D R and J C Venus 1981 The biometry of plant growth Edward Arnold London 307 pp Celia M A E T Bouloutas and R L Zarba 1990 A general mass conservative numerical solution for the unsaturated flow equation Water Resour Res 26 1483 1496 Clausnitzer V J W Hopmans and D R Nielsen 1992 Simultaneous scaling of soil water retention and hydraulic conductivity curves Water Resour Res 28 19 31 Clothier B E M B Kirkham and J E McLean 1992 In situ measurement of the effective transport volume for solute moving through soil Soil Sci Soc Am J 56 733 736 Dane J H and G C Topp 2002 Methods of soil analysis Part 4 Physical methods SSSA Book series number 5 Madison Wisconsin 1692 p De Jong van Laer Q J C van Dam K Metselaar R de Jong and W H M Duijnisveld 2008 Macroscopic root water uptake distribution using a matric flux potential approach Vadose Zone J 7 1065 1078 doi 10 2136 Dekker L W and P D Jungerius 1990 Water repellency in the dunes with special reference to the Netherlands In Dunes of the European Coasts Catena Suppl 18 173 18
44. J B J C Parker and M Th van Genuchten 1985 Determining soil hydraulic properties from One step outflow experiments by parameter estimation I Theory and numerical studies Soil Sci Soc Am J 49 1348 1354 Kool J B and J C Parker 1987 Development and evaluation of closed form expressions for hysteretic soil hydraulic properties Water Resour Res 23 105 114 Kool J B J C Parker and M Th van Genuchten 1987 Parameter estimation for unsaturated flow and transport models a review J Hydrol 91 255 293 Kool J B and M Th van Genuchten 1991 HYDRUS One dimensional variably saturated flow and transport model including hysteresis and root water uptake Research Report 124 U S Salinity Laboratory USDA ARS Riverside CA Koorevaar P G Menelik and C Dirksen 1983 Elements of soil physics Developments in Soil Science 13 Elsevier Amsterdam p 223 Alterra Report 1649 update02 215 Klute A 1986 Water retention laboratory methods In Methods of soil analysis Part 1 Physical and Mineralogical methods A Klute Ed Agronomy series n 9 ASA and SSSA Madison Wisconsin p 635 662 Klute A and C Dirksen 1986 Hydraulic conductivity and diffusivity laboratory methods In Methods of soil analysis Part 1 Physical and Mineralogical methods A Klute Ed Agronomy series n 9 ASA and SSSA Madison Wisconsin p 687 734 Kraalingen D W G and C Rappoldt 2000 Reference manual of the
45. K and P Germann 1982 Macropores and water flow in soils Water Resour Res 18 1311 1325 Biggar J W and D R Nielsen 1976 The spatial varability of the leaching characteristics of a field soil Water Resour Res 12 78 84 Black T A W R Gardner and G W Thurtell 1969 The prediction of evaporation drainage and soil water storage for a bare soil Soil Sci Soc Am J 33 655 660 Boesten J J T I 1986 Behaviour of herbicides in soil Simulation and experimental assessment Ph D thesis Winand Staring Centre Wageningen Boesten J J T I and L Stroosnijder 1986 Simple model for daily evaporation from fallow tilled soil under spring conditions in a temperate climate Neth J Agric Sci 34 75 90 Boesten J J T I and A M A van der Linden 1991 Modeling the influence of sorption and transformation on pesticide leaching and persistence J Environ Qual 20 425 435 Bolt G H 1979 Movement of solutes in soils principles of adsorption exchange chromatography In G H Bolt Ed Soil Chemistry B Physico Chemical Models Elsevier Amsterdam p 285 348 Boogaard H L C A van Diepen R P R tter J C M A Cabrera and H H van Laar 1998 WOFOST 7 1 User guide for the WOFOST 7 1 crop growth simulation model and WOFOST Control Center 5 1 Techn Doc 52 Alterra WUR Wageningen The Netherlands pp 144 Alterra Report 1649 update02 209 Booltink H W G 1993 Morphometric methods for simulation o
46. KK KKK KKK KKK KKK KKK ck k ck ck ck ck KKK k ck ck ckck ck k ck k ck k ck k ck k ck k ck kckckckok KK KK KK KK KK KK KK KK KK KK KK KK KK KK KKK KKK KKK KKK KKK KKK KKK KK KKK KKK KKK ck ck ckck ck ck KKK ck ck ck ck ck ck ck ck k ck k ck k ck k ck k ck k ck kckckckok Part 2 Crop development IDSL 0 Switch for crop development 0 Crop development before anthesis depends on temperature only 1 Crop development before anthesis depends on daylength only i Crop development before anthesis depends on both N I If IDSL 1 or 2 specify DLO 14 0 Optimum day length for crop development 0 24 h R DLC 8 inimum day length 0 24 h R o If IDSL 0 or 2 specify TSUMEA 152 00 Temperature sum from emergence to anthesis 0 10000 C R TSUMAM 1209 00 Temperature sum from anthesis to maturity 0 10000 C R List increase in temperature sum 0 60 C R as function of daily average temp 0 100 C R TAV DTSM maximum 15 records DTSMTB 0 00 0 00 2 00 0 00 13 00 11 00 29 00 11 00 End of Table DVSEND 2 00 development stage at harvest Ck kk ck ck ck ck ck ck KK KKK KKK KK KKK KKK KKK KKK KKK KKK KKK KKK KKK KK KK KKK KKK KKK ck ckck ck k ck k ck ck KKK k ck k ck k ck k ck kck k ck k ck k ck k ck kckckckok KKK KK KK KKK KK KKK KKK KK KK KK KK KKK KKK KKK KKK KKK KKK KK KKK KK kck kck kckck ck ck ck ck ckck ck k ck ck ckck ck ck ck k ck k ck k ck k ck k ck k ck k ck KK KKK
47. M Th and R J Wagenet 1989 Two site two region models for pesticide transport and degradation Theoretical development and analytical solutions Soil Sci Soc Am J 53 1303 1310 Van Genuchten M Th F J Leij and S R Yates 1991 The RETC code for quantifying the hydraulic functions for unsaturated soils U S Salinity Laboratory Riverside California Van Genuchten M Th and FJ Leij 1992 On estimating the hydraulic properties of unsaturated soils In Indirect methods for estimating hydraulic properties of unsaturated soils M Th van Genuchten and F J Leij eds Proc Int Workshop Riverside California p 1 14 Van Grinsven J J M C Dirksen and W Bouten 1985 Evaluation of hot air method for measuring soil water diffusivity Soil Sci Soc Am J 49 1093 1099 Van Heemst H D J 1986a The distribution of dry matter during growth of a potato crop Potato Research 29 55 66 Van Heemst H D J 1986b Crop phenology and dry matter distribution In H van Keulen and J Wolf Eds Modelling of agricultural production soil weather and crops p 13 60 Van Ittersum M K P A Leffelaar H van Keulen M J Kropff L Bastiaans and J Goudriaan 2003 On approaches and applications of the Wageningen crop models Europ J Agronomy 18 201 234 Van Keulen H 1975 Simulation of water use and herbage growth in arid regions Simulation Monographs Pudoc Wageningen the Netherlands 184 pp Van Keulen H N G S
48. METFIL Wageningen File name of meteorological data without extension YYY A16 Extension equals last 3 digits of year number e g 2003 has extension 003 SWETR 0 Switch use reference ET values of meteo file Y 1 N 0 If SWETR 0 then LAT ALT and ALTW must have realistic values LAT 52 0 Latitude of meteo station 60 60 degrees R North ALT 10 0 Altitude of meteo station 400 3000 m R ALTW 2 0 Altitude of wind speed measurement 10 m is default 0 99 m R Use of detailed meteorological records lt 1 day SWMETDETAIL 0 Switch use detailed meteor records of both ET and rainfall Y 1 N 0 In case of detailed meteorological weather records SWMETDETAIL 1 NMETDETAIL 10 Number of weather data records per day 1 96 I In case of daily meteorological weather records SWMETDETAIL 0 SWETSINE 0 Switch distribute daily Tp and Ep according to sinus wave Y 1 N 0 SWRAIN 0 Switch for use of actual rainfall intensity SWRAIN 0 Use daily rainfall amounts SWRAIN 1 Use daily rainfall amounts mean intensity SWRAIN 2 Use daily rainfall amounts duration SWRAIN 3 Use short time rainfall intensities as supplied in sep file If SWRAIN 1 then specify mean rainfall intensity RAINFLUX 0 d0 1000 d0 cm d R as function of time TIME 0 366 d R maximum 30 records TIME RAINFLUX 1 0 2 0 360 0 2 0 End of table
49. Multi level drainage with surface water dependent resistances and simulated drainage levels Distribution with depth of drainage fluxes 4 4 1 Implicit approach of travel times 4 4 2 Discharge layers User instructions 4 5 Surface runoff 4 5 2 Interflow 4 5 3 Drainage 5 Surface water management 5 1 5 2 Surface water balance 5 1 1 Multi level drainage with imposed surface water levels 5 1 2 Multi level drainage with simulated surface water levels 5 1 2 1 Fixed weir 5 1 2 2 Soil moisture controlled weir management User instructions 5 2 1 Example case 5 2 2 Input instructions 6 Macropore flow 6 1 6 2 6 3 Concept 6 1 1 Macropore geometry 6 1 1 1 Continuity 6 1 1 2 Persistency 6 1 1 3 Horizontal distribution 6 1 2 Water flow and balance Numerical implementation 6 2 1 Macropore geometry 6 2 1 1 Continuity 6 2 1 2 Persistency 6 2 1 3 Horizontal distribution 6 2 2 Water flow and balance User instructions 6 3 1 General input parameters 6 3 2 Macropore input parameters 83 85 85 86 90 90 91 91 97 97 99 99 99 100 101 101 103 111 111 112 113 116 122 123 130 130 130 132 133 134 137 137 138 Alterra Report 1649 update02 7 10 11 6 3 2 1 Macropore geometry 6 3 2 2 Water flow Crop growth 7 1 Introduction 7 2 Simple crop module 7 3 Detailed crop module 7 3 1 Phenological development stage 7 3 2 Radiation fluxes above the canopy 7 3 3 Radiation profiles withi
50. O A ppu H 5 7 where Q is the discharge m s H is the head above the crest m and input is a weir coefficient m s Pis a weir exponent The preparatory work that the user has to do is to compute the value of a from the various coefficients preceding the upstream head above the crest For instance for a broad crested rectangular weir o is approximately given by Qus 71 7 b 5 8 input where 1 7 is the discharge coefficient of the weir based on SI units b is the width of the weir m To correct for units the model carries out the following conversion 8 65 100 9 a weir xi p 23 3 A cu 5 9 where A is the size of the control unit ha The model requires input of the size of the control unit Acu which in simple cases will be identical to the size of the simulation unit Alterra Report 1649 update02 107 If the discharge relation is described using a table SWQHR 2 then for each water management period with a fixed weir crest using weir characteristics the user should specify a table in section 4d In section 4e of the input file the required parameters should be given to introduce an automatic weir SWMAN 2 controlled by soil moisture characteristics see also par 5 1 2 2 For each management period with an automatic weir the user should specify in section 4e the maximum allowed drop rate of the water level setting the depth HDEPTH in the soil profile for a co
51. R maximum 36 records DNR GH CE 0 0 12 0 1 0 180 0 12 0 1 0 366 0 12 0 1 0 End of Table If SWCF 2 list crop specifi values for ALBEDO 0 23 crop reflection coefficient 0 1 0 R RSC 70 0 Minimum canopy resistance 0 10 6 s m R RSW 0 0 Canopy resistance of intercepted water 0 10 6 s m R kkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkk FI I I I I I I I I I II I II I II I IIR I I IR I IR I IR OR IO RR I Ke Part 2 Initial values TDWI 1000 00 Initial total crop dry weight 0 10000 kg ha R LAIEM 0 6300 Leaf area index at emergence 0 10 m2 m2 R RGRLAI 0 00700 Maximum relative increase of LAI per day 0 1 m2 m2 d R FO III II E E E E II ICRI III III ICI ICICI IGS ISIC III ICICI III III ICR IIS III III III ICR III IO ICR II Rd K OK kk kk kk ok kk kk I I I ke OOOO RR IO RR IO RA ee Part 3 Green surface area List specific leaf area ha kg R as function of daynumber 1 366 d R DNR SLA maximum 15 records SLATB 1 00 0 0015 80 00 0 0015 300 00 0 0020 366 00 0 0020 End of Table SSA 0 0000 Specific stem area 0 1 ha kg R SSA 0 004 Specific stem area 0 1 ha kg R value from Retta et al 2000 SPAN 30 00 Life span of leaves under optimum conditions 0 366 d R TBASE 0 00 Lower threshold temperature for ageing of leaves 10 30 C R FI I I I I I I II OOOO OOOO AA RA AR
52. RK RK RK RK RK KK KK KK KK KK KK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK ck k ck k ck k ck k ck k ck k KKK KK KKK RK KK RK RK KK RK RK KK RK KK RK KK RK KK KKK KK KK KKK KK KK KK KK KKK KKK KKK KKK KKK KKK KKK k ck kck k ck k ck k KKK KK KKK Part 4 crop factor or crop height SWCF 2 choice between crop factor 1 or crop height 2 Choose crop factor if ETref is used either from meteo input file SWETR 1 or with PM Choose crop height if PM should be used with actual crop height albedo and resistance If SWCF 1 list crop factor CF 0 5 1 5 R as function of dev stage DVS 0 2 R If SWCF 2 list crop height CH 0 1000 cm R as function of dev stage DVS 0 2 R maximum 36 records DVS CH C 0 Ls 3 X5 5 40 m 140 0 170 4 180 0 I755 of table NRroooo GO oO Ga Goog PRRPROOO N OM P Ow 0 0 Hj End If SWCF 2 in addition to crop height list crop specific values for ALBEDO 0 23 crop reflection coefficient 0 1 0 R RSC 70 0 Minimum canopy resistance 0 10 6 s m R KKK KK KKK KKK KKK KKK ck ck KKK ck ck A ck ck ck ck ck ck ck ck ck KKK ck ck ckck c kck KKK KK KKK ck ckckck ck ckckckck ck ck ckck ck KK KKK KAKA KKK kckck KKK KKK KKK KK KKK Ck kk kk KK KKK KKK KKK KKK KKK AA KKK KKK KKK KK KKK KKK KKK KKK KKK KKK KKK KK KKK KKK KKK ckck ck ck KKK k ck kckck ck kckck ck k ck k ck KK KKK Part 5 rooting depth List rooting depth 0 1000 cm R as a function of
53. Station DD MM YY RAD Tmin Tmax HUM WIND RAIN ETref WET nr nr nr kJ m2 C C kPa m s mm mm d EEES 2003 2540 ols 1550 2003 3520 6 0000 2003 1510 8 0050 2003 740 0 1750 2003 990 2 0550 2003 1090 Ds 2175 2003 1720 1 0075 2003 500 0 0000 2003 1500 0 0000 2003 660 i 0000 2003 1080 So s 0000 p o N e ds o Ww a OY N o Wageningen Wageningen Wageningen Wageningen Wageningen Wageningen Wageningen Wageningen Wageningen Wageningen Wageningen FH O00 10 UO 0 NS oooooooooo ODFPNBAAWNHU FPORPWUAUNWOR NaOwoanorars oc000o00o00o0o0o0oo NNNNFNWABAN EH dU NOU O0 N l Oooooot oo oooowuuJInono O O tO tO tO tO tO xo to O Oooooooooo RR Alternatively weather records can be specified with short constant time intervals gt 15 minutes according to the format listed in Box 3 3 Radiation and rainfall denote cumulative amounts during the time interval Air temperature humidity and wind speed denote average values during the time interval A third combination is daily evapotranspiration data and detailed rainfall data In this case evapotranspiration data are input according to Box 3 2 while the rainfall data are input according to Box 3 4 The rainfall data follow the format of a tipping bucket measurement device The rainfall amount refers to the amount fallen in the previous period 66 Alterra Report 1649 update02 Box 3 3 Weather records for short cons
54. Summerfield and F R Minchin 1984 Effects of temperature and photoperiod on flowering in soya bean a quantitative model Annals of Botany 53 669 681 Hargreaves G L and Z A Samani 1985 Reference crop evapotranspiration from temperature Applied Engineer In Agric 1 2 96 99 Harrison L P 1963 Fundamental concepts and definitions relating to humidity In Humidity and moisture A Wexler Ed Vol 3 Reinhold Publishing Company New York Alterra Report 1649 update02 213 Haverkamp R M Vauclin J Touma P J Wierenga and G Vachaud 1977 A comparison of numerical simulation models for one dimensional infiltration Soil Sci Soc Am J 41 285 294 Haverkamp R and M Vauclin 1979 A note on estimating finite difference interblock hydraulic conductivity values for transient unsaturated flow problems Water Resour Res 15 181 187 Hendriks R F A K Oostindie and P Hamminga 1999 Simulation of bromide tracer and nitrogen transport in a cracked clay soil with the FLOCR ANIMO model combination J Hydrol 215 94 115 Hendriks R F A 2004 An analytical equation for describing the shrinkage characteristics of peat soils In J P iv nen Ed Wise use of Peatlands Proceedings of the 12th International Peat Congress Tampere Finland Hendriks R F A J J T I Boesten J C van Dam and P Groenendijk in prep Modelling macropore flow in swelling shrinking clay and peat soils on the basis of macropo
55. Surface water level Storage in surface water reservoir Sum of drainage runoff and rapid drainage External supply to surface water reservoir Outflow from surface water reservoir Surface water management 2 man 4 Weir type Groundwater level Pressure head for target level Total air volume in soil profile Weir target level Surface water level and outflow Number of target level adjustments Indicator weir overflow Weir crest level Snowpack water balance snw 4 Final and initial water storage Water balance components Detailed waterbalance Macropores bma Final and initial water storage Water balance components Soil physical parameters soilphysparam csv For each soil layer the relation between soil water pressure head h cm theta O en cm differential capacity C cm RelSat S and hydraulic conductivity K cm d Soil heat conductivity and capacity heatparam csv For each soil layer the relation between theta heatcapacity and heat conducitivity Final values of state variables end Snow and ponding layer Soil water pressure heads Solute concentrations Soil temperatures 22 Alterra Report 1649 update02 Box 1 5 Example of Result bal file for Hupsel case Project Hupsel File content overview of actual water and solute balance components File name Result bal Model version Swap 3 2 revision 10 Date 02 May 2008 Generated at 05 May 2008 15 57 05
56. Therefore at a certain light intensity the CO uptake rate and the photosynthesis are much higher in case of C plants 7 3 5 Daily gross assimilation rate of the canopy The instantaneous rates per leaf layer need to be integrated over the canopy leaf area index and over the day This is efficiently achieved using the Gaussian integration method Press et al 1989 This method specifies the discrete points at which function values have to be calculated and the weighting factors with which the function values have to be multiplied in order to minimize deviation from analytical integration A three point algorithm evaluates the function at 0 1127a 0 5a and 0 8873a of the interval 0 2 with weighting coefficients 1 0 1 6 and 1 0 respectively The Gaussian integration method is remarkably accurate in case of trigonometric radiation and exponential light absorption functions WOFOST computes at three selected moments of the day incoming PAR just above the canopy Using this radiation assimilation is computed at three selected depths in the canopy Spitters et al 1989 Gaussian integration of these values results in the daily rate of potential gross CO assimilation A peross kg CO ha d 156 Alterra Report 1649 update02 Until now the assimilation has been treated as a function of the intercepted light and of photosynthetic crop characteristics such as initial light use efficiency and maximum leaf CO assimilation at light
57. Wageningen weather station KKK KKK ck ck ck KKK KK KKK ck ck ck ck ce ck KKK KKK KKK KKK KKK KKK KKK KKK AAA KKK KKK Comment area Amount refers to the rainfall amount in the previous period like a tipping bucket rainfall measurement device KKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKK Station Day Month Year Time Amount js nr nr nr d mm ES Wageningen 1 1 2003 0 0 0 Wageningen 2003 Wageningen 2003 Wageningen 2003 Wageningen 2003 Wageningen 2003 Wageningen 2003 3 7 3 Soil data Box 3 5 lists the soil data which are required to determine the actual evaporation at the soil surface The soil factor CFBS can be used to transform reference crop evapotranspiration into potential soil evaporation see Section 3 3 2 and Table 3 2 When the Penman Monteith equation is applied SWETR 0 in Box 3 1 SWAP will calculate directly potential soil evaporation by setting crop 0 Acrop 0 1 cm and ar 0 15 In that case soil factor CFBS is not needed Three options are offered to reduce soil evaporation according to the maximum water flux which can be delivered by the soil Applying straight soil physically theory the first option would suffice However as discussed in section 3 6 this method in generally results in overestimation of the actual soil evaporation Therefore we Alterra Report 1649 update02 67 recommend to use the combination of reduction to maximum Darcy flux and reduction with either the
58. al 1992 Dekker and Ritsema 1996 If measured sorptivities are not available sorptivity as a function of moisture content is derived from the soil hydraulic characteristics Parlange 1975 To account for water repellent coatings a correction factor SorpFacParl can be entered Greco et al 1996 found values for this factor of 0 33 for the topsoil and 0 5 for the sub soil of a Dutch clay soil similar to the Andelst soil They describe a simple way of measuring sorptivity as a function of moisture content ShapeFacMp can be used to decrease or increase exchange fluxes between macropores and soil matrix Theoretically its value lies between 1 and 2 see Section 6 1 2 default value is 1 0 RapDraResRef depends on the system of macropores and their connection to drains or ditches In case of a network of structural cracks RapDraResRef will be smaller than in case of mainly hole shaped macropores The opposite applies to RapDraReaExp 146 Alterra Report 1649 update02 7 Crop growth 7 1 Introduction SWAP contains three crop growth routines a simple module a detailed module for all kind of crops WOFOST WOrld FOod STudies and a detailed module for grass re growth The simple module prescribes crop development independent of external stress factors Its main function is to provide proper upper boundary conditions for soil water movement The simple model is useful when crop growth doesn t need to be simulated or when crop growth
59. an expression which relates the proportions of the discharge layer to the discharge flow rates Alterra Report 1649 update02 87 D L D LD LD LD LD3 4 14 darain 1Ldrain 1 4 drain 2 dean a q drain drain 7 d drain 3L drain 3 q drain 3 drain 3 In theory the terms qas iLanini Larain2L rain2 ANG daunoLauno Ferain 3Ldrain 3 CAN take negative values for specific combinations of qu Lai arain2Larainz aNd Qaain3Larina When 4arain 1Larain 1 Lorain2Larain2 lt O it is assumed that D will be zero and the nesting of superposed flows systems on top of the flow region assigned to drainage class 1 will not occur Likewise a separate nested flow region related to a drainage class will not show up when 4arain2Larain2 Larain3L rain 3 lt O These cases are depicted schematically in figure 4 8 drain 1Ldrain1 drain 2Larain2 lt 0 Flow to second order drains Flow to first order drains drain 2Ldrain2 7 Qdrain 3Lgrainz lt O Flow to third order drains Flow to second order drains Va 2 Figure 4 8 Schematization of regional groundwater flow to drains of three orders when either drain ILarain 1 Qarain2Larain 2 0 or ddrain 2Ldrain 2 Qarain 3Larain 3 If the soil profile is stratified with respect to horizontal conductivities the heterogeneity can be taken into account by substituting transmissivities kD for layer thicknesses in Eq 4 33 _
60. and the depth of the soil profile The output interval may range from a day to years Some output can be generated with time intervals less than a day We may distinguish output of state variables incremental fluxes since the last output time and cumulative fluxes since a specified data The output file with final values of state variables can be used as input for a subsequent simulation period This might be useful to derive suitable initial conditions In addition to the ASCII files formatted and unformatted binary export files can be generated with data that cover the entire simulation period These output files can be used as input for other models such as the pesticide and nutrient models like PEARL Leistra et al 2001 and ANIMO Groenendijk et al 2005 A description of these files is given in Appendix 14 Description of output files afo and aun and Appendix 15 Description of output files bfo and bun 1 6 Example run Hupsel catchment The setup file contains the input for a field in the Hupsel catchment in The Netherlands The simulation run covers the years 1980 1982 The potential evapotranspiration fluxes are calculated from daily meteorological measurements Daily rainfall fluxes are used as in the catchment with mild slopes and sandy soils no runoff is expected The cropping pattern consists of maize in the summer season of 1980 and 1982 The development of these crops is prescribed In the summer season of 1981 potatoes
61. applications SWIRFIX 0 no irrigation applications are prescribed SWIRFIX 1 irrigation applications are prescribed If SWIRFIX 1 SWIRGFIL 0 Switch for file with fixed irrigation applications SWIRGFIL 0 data are specified in the swp file SWIRGFIL 1 data are specified in a separate file If SWIRGFIL 0 specify information for each fixed irrigation event max MAIRG IRDATE date of irrigation dd mmm yyyy IRDEPTH amount of water 0 0 100 0 mm R IRCONC 7 concentration of irrigation water 0 0 1000 0 mg cm3 R IRTYPE type of irrigation sprinkling 0 surface 1 IRDATE IRDEPTH IRCONC IRTYPE 05 jan 1980 5 0 1000 0 1 end of table If SWIRGFIL 1 specify name of file with data of fixed irrigation applications IRGFIL testirri File name without extension IRG A16 ck KK KK kk KK KK KK KA KK KK RK RK RK KK kckckckckckckckckckckckckckckckckckckck ckckckckckckckckckckckckckckckckckckckckckck ck ck ck ck ck ck k ck kkk Box 11 2 Scheduled irrigation in the input file CRP IRRIGATION SCHEDULING part 1 IRRIGATION SCHEDULING SECTION KKK KKK KK KK KK KKK KK KKK KKK KKK KK KKK KKK KKK KKK KKK KKK KKK KKK KKK KK KKK k ck k ck k ck ck ck k ck ck ck k ck k ck ck KKK AK Part 1 General SCHEDULE 0 Switch for application irrigation scheduling Y 1 N 0 If SCHEDULE 0 no more information is required in this input file If SCHEDULE 1 continue STARTIRR
62. applied for drainage combined with a flux bottom boundary condition Also the coupling of the SWAP model to a regional groundwater model by exchanging information concerning fluxes and hydraulic heads at the bottom of the schematization may require alternative formulations for the drainage equation to be used The influence of frost at a certain depth can optionally be accounted for by the reduction of prevailing drainage fluxes at that depth similar to the reduction of hydraulic conductivities see Chapter 2 74 Alterra Report 1649 update02 4 3 1 Field scale drainage relation according to Hooghoudt and Ernst The drainage equations of Hooghoudt and Ernst allow the evaluation of drainage design and are based on the drainage flux as a function of the head difference the maximum groundwater elevation midway between the drains and the drainage level Depending on position of the groundwater level the drainage level and the possibility for water supply in the surface water system the channels will act as either drainage or sub irrigation media The theory behind the field drainage equations used for drainage design purposes is summarized by Ritzema 1994 Five typical drainage situations are distinguished Table 4 2 For each of these situations the drainage resistance Yarain d can be defined Table 4 2 Five field drainage situations considered in SWAP after Ritzema 1994 Case Schematization Soil profile Drain Theory
63. arain drain Q rain 2 L rain 2 R drain 2Ldrain 2 E arain 3 Ldrain 3 t Ydrain 3 KD KD KD 4 15 Litan 1 L rain2 Lateral drainage fluxes to a certain drainage system per nodal point are calculated by multiplying the flux and the transmissivity proportion of that nodal point in the total transmissivity of the discharge layer 88 Alterra Report 1649 update02 In deep aquifers the thickness of a model discharge layer is limited by p lt Farin Kv 4 16 4 K where K is the vertical conductivity and Kj is the horizontal conductivity In stratified aquifers the weighted arithmetic mean is used for the horizontal conductivity and the weighted harmonic mean is used for the vertical conductivity The top of any of the discharge layers is situated at the average groundwater level This implies that solute transport to drains is calculated for the soil compartments between the simulated groundwater level and the bottom of the discharge layer The groundwater level as the defined top of the zone that contributes to surface water loading may be inaccurate in case of concentration profiles with steep gradients In reality the surface water load is determined by the present concentrations and water fluxes at the exfiltration zone in the drain From Fig 4 9 left it can be seen that the concentrations at the drain bottom and at the depth of the surface water level are lower than the ones at the groundwater level In such c
64. are grown of which the actual growth is simulated On 5 January 1980 a tracer is applied which leaches in the subsequent years towards the drains Initial soil water contents are assumed to be in hydrostatic equilibrium with a groundwater level at 75 cm depth The sandy soil profile consists of a top and sublayer with thicknesses of 30 and 170 cm respectively At the bottom of the soil profile a layer of boulder clay with low permeability prevents vertical soil water movement Therefore at the bottom a zero flux condition is specified Drainage fluxes are calculated for subsurface drains at 80 cm depth and with a lateral distance of 11 m Results are shown in water balances in Box 1 5 summary and Box 1 6 detail Alterra Report 1649 update02 21 Box 1 4 Summary of information in output files Short water and solute balance bal Final and initial water and solute storage Water balance components Solute balance components Extended water balance blc 4 Final and initial water storage Water balance components of sub systems Incremental water balance inc Gross rainfall and irrigation Interception Runon and runoff Potential and actual transpiration Potential and actual evaporation Net drainage and bottom flux Cumulative water balance wba Gross and net rainfall Runon and runoff Potential and actual transpiration Potential and actual evaporation Net lateral flux drainage Net bottom flux Change water sto
65. assumption in the concept is that property persistency is not correlated with both other properties Persistency refers to volume and not to pore structure static macropore volume and dynamic macropore volume form together the total macropore volume Characterisation according to the other two properties applies to the total volume The properties continuity and horizontal distribution are correlated the horizontal macropore volume distribution as a function of depth depends on the macropore bottom depth distribution 112 Alterra Report 1649 update02 6 1 1 1 Continuity With respect to vertical and horizontal continuity the macropores are divided into two classes that are integrated in two domains 1 Main Bypass MB flow domain the network of continuous horizontal interconnected macropores 2 Internal Catchment IC domain discontinuous non interconnected macropores ending at different depths The MB domain represents the main system of continuous structural and shrinkage cracks as well as root and worm holes These macropores penetrate relatively deep into the soil profile and are assumed to be horizontal interconnected for example in a network of structural and shrinkage cracks In the MB domain water is transported relatively fast and deep into the profile bypassing the soil matrix This may lead to short circuiting between soil surface and groundwater and rapid drainage to drains The IC domain represents
66. can be calculated with T T Rar Rn Qo 17 where Rar Maintenance respiration rate at temperature T kg ha d Rm Maintenance respiration rate at reference temperature of 25 C kg ha d Qio Relative increase of the respiration rate per 10 C temperature increase T Average daily temperature C T Reference temperature 225 C in the model C For tropical species the reference temperature may be 10 C higher than for species from temperate climates The grass crop maintenance requirements are likely to be adapted to the higher growth temperatures However in Grass the temperature is fixed at 25 C Note that the maintenance respiration cannot exceed the gross daily assimilation rate Growth respiration The primary assimilates in excess of the maintenance are converted into structural plant material The growth respiration rate can then be calculated as R g Ra ES R T where Rg Growth respiration rate kg ha d Ra Actual daily CHO assimilation rate see eq 5 37 kg ha d Rar Maintenance respiration rate at temperature T kg ha d However this process requires energy and therefore a conversion factor is defined This factor depends on the conversion efficiency of assimilates and on the efficiency factor to calculate the dry matter increase It can be calculated as a weighted average of the efficiencies of various plant organs 1 C c c PN ai pe Con i l e i where
67. carbohydrates CH20 produced are used to provide energy for the maintenance of the living biomass maintenance respiration The remaining car bohydrates are converted into structural matter In this conversion some of the weight is lost as growth respiration The dry matter produced is partitioned among roots leaves stems and storage organs using partitioning factors that are a function of the phenological development stage of the crop Spitters et al 1989 The fraction partitioned to the leaves determines leaf area development and hence the dynamics of light interception The dry weights of the plant organs are obtained by integrating their growth rates over time During the development of the crop part of living biomass dies due to senescence Light interception and CO assimilation are the main growth driving processes Some simulated crop growth processes are influenced by temperature like for example the maximum rate of photosynthesis and the maintenance respiration Other processes like the partitioning of assimilates or decay of crop tissue are a function of the pheno logical development stage 150 Alterra Report 1649 update02 7 3 1 Phenological development stage As many physiological and morphological processes change with the phenological stage of the plant quantification of phenological development is essential in any crop growth simulation model For many annual crops the phenological development can conveniently be
68. ck ck k ck ck KKK KKK ck k ck KK KK KKK Part 12 Interception COFAB 0 25 Interception coefficient Von Hoyningen Hune and Braden 0 1 cm R KKK KKK KKK ke KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KK KKK KKK KKK KEK KKK KKK KKK KKK KKK KKK KK KKK KKK KKK KK KK RK RK RK RK RK RK RK KK KK KK RK KK KKK KKK KKK KKK KKK KK KKK KKK KKK KKK KKK KKK KKK ckck ck k ck k KKK k ck kck k ck k ck k ck k ck KK KKK Part 13 Root growth and root density profile RDI 10 00 Initial rooting depth 0 1000 cm R RRI 1 20 Maximum daily increase in rooting depth 0 100 cm d R RDC 50 00 Maximum rooting depth crop cultivar 0 1000 cm R List relative root density 0 1 R as function of rel rooting depth 0 1 R Rdepth Rdensity maximum 11 records RDCTB 0 00 1 00 1 00 1 00 End of table ck kk kk KKK KKK KKK KK ck ck ck A ck KKK KKK KK KK KKK KKK KK KKK KKK KKK KKK KKK ck ck ck RARA RARA ck ck ck k ck ck ck k RARA RAR Alterra Report 1649 update02 171 172 Alterra Report 1649 update02 8 Solute transport 8 1 Introduction Many solutes enter the natural system at the soil surface The solute residence time in the unsaturated zone is important for soil and groundwater pollution management For instance organic compounds are mainly decomposed in the unsaturated zone where the biological activity is concentrated Most plants are able to extract water and nutrients from the soil only i
69. cm d T is the soil temperature C T and T C are the threshold values bounding the linear reduction and K is a minimum value of the hydraulic conductivity cm d which holds for temperatures less than T Alterra Report 1649 update02 31 2 6 Lower boundary The bottom boundary of the one dimensional SWAP is either in the unsaturated zone or in the upper part of the saturated zone where the transition takes place to three dimensional groundwater flow The lower boundary conditions in SWAP can be specified depending on the application and the relevant spatial scale Three general types and some special cases of lower boundary conditions are distinguished 1 The Dirichlet condition The head controlled boundary is often referred as to the Dirichlet condition and involves the imposing of a pressure head Apo at the lower boundary A special case involves the use of a recorded groundwater elevation The pressure head at the groundwater elevation is defined as h 0 This yields a linear relation between the pressure heads at the grid points above and below 5 Pave T Ziy ZiT Pave h h 1 2 15 i 1 2 The Neumann condition 32 The flux is often referred as to the Neumann condition and involves prescribing a flux qp at the bottom Since the model employs an explicit linearization scheme the flux groundwater level relations are treated as a Neumann condition where the actual
70. cm d is calculated from MB domain water level elevation mp cm above drainage level oa cm and Yact d at actual moisture content la a xx Pas 6 38 6 2 Numerical implementation SWAP applies the same vertical spatial Az and temporal Af discretisation for macropore flow as is used for matrix flow Besides SWAP uses a horizontal discretisation in the form of macropore domains for macropore flow In this section the horizontal discretisation its relationship with vertical and temporal discretisation and the numerical implementation of water balance and flow equations are described 6 2 1 Macropore geometry 6 2 1 1 Continuity To obtain the required resolution in IC macropores the IC domain is divided into nsa sub domains This partition represents the horizontal discretisation of the macropore system The IC volume at soil surface minus the Rzay volume is equally distributed over the ns sub domains Thus all n sub domains take up an equal amount of infiltrating water at the soil surface The volumetric proportion Psa of sub domain j as a function of z is calculated according to 1 1 R Z n Paj gt for 0 gt Z gt Zaja 6 39 4 F 1 sd ic 0 j 1 A E EA zo da 6 39 b F 1 ic 0 Py 0 for 2 Tay 6 39 0 130 Alterra Report 1649 update02 where j 1 is the deepest and j nsa the shallowest sub domain respectively left and right in Fig 6 1 B and Zsa is the depth at which sub d
71. combination with the model PESTLA Van den Berg and Boesten 1998 and PEARL Leistra et al 2000 Tiktak et al 2000 For nutrient transport nitrogen and phosphorus SWAP can be used in combination with the model ANIMO Rijtema et al 1997 Kroes and Roelsma 1998 In this chapter we first describe the solute transport processes that are considered in SWAP Next we discuss the boundary conditions applied Also we consider how SWAP deals with solute transport in water repellent soils and in cracked clay soils Finally we describe the input data for solute transport 8 2 Basic equations 8 2 4 Transport processes The three main solute transport mechanisms in soil water are diffusion convection and dispersion Diffusion is solute transport caused by the solute gradient Thermal motion of the solute molecules within the soil solution causes a net transport of molecules from high to low concentrations The solute flux Jar g cm d is generally described by Fick s first law Oc Jat AD y 8 1 Oz with Dait the diffusion coefficient cm d and c the solute concentration in soil water g cm Dait is very sensitive to the actual water content as it strongly affects the solute transport path and the effective cross sectional transport area In SWAP we employ the relation proposed by Millington and Quirk 1961 e 3 2 b por Dit D 8 2 with Dw the solute diffusion coefficient in free water cm d and por th
72. d Lg Leaf area index growth rate at time step t during exponential growth stage ha ha d The accumulated leaf area cannot be calculated directly it has to be corrected for leaf senescence which occurred during the current time step Leaf senescence can be caused by physiological ageing water stress and or high leaf area index i e mutual shading Later in this text more attention will be paid to these effects To correct for leaf senescence the specific leaf area of each time step Sa the dry matter growth increase of the leaves per time step AW and the physiological age Page have to be stored in three different arrays These arrays are organized as follows the first element of the arrays represents the most recent age class or time step and the last element of the arrays represents the oldest age class or time step It should be clear that the position of an element in the arrays represents its age class in time steps The dry matter weight of the leaves that died during the current time step has to be subtracted from the dry matter weight increase per time step One array contains thus the net leaf dry matter growth per Alterra Report 1649 update02 273 time step AWny The procedure describing this process will be explained later in this text After correction for leaf senescence the accumulated leaf area can be established The net dry matter leaf weight AWny in the remaining and new leaf classes is multiplied wi
73. developed taking into account these requirements The macropore flow concept is described by Hendriks et al in prep It is new in the present SWAP and therefore and to promote a well considered use of this option its description is rather extensive and detailed The concept of macropore flow is described in Section 6 1 The numerical implementation in the SWAP model is discussed in Section 6 2 User instructions are given in Section 6 3 6 1 Concept In the SWAP model macropore water flow includes the following processes uptake of water by macropores at the soil surface vertical transport to deeper layers or the groundwater bypassing the soil matrix lateral infiltration into and exfiltration out of the soil matrix rapid drainage to drainage systems water storage in the macropores Alterra Report 1649 update02 111 The simulation of these processes is based on the description of the macropore geometry as proposed by Hendriks et al 1999 The description of this geometry that SWAP uses is discussed in Section 6 1 1 Water flowing into macropores is instantaneously added to the water storage at the bottom of the macropores Lateral infiltration into the soil matrix of macropore water running rapidly downwards is neglected Because such downward flow occurs in a low number of contracted films contact areas with the matrix are small and consequently this infiltration is negligible Hoogmoed and Bouma 1980 Booltink 1993
74. diffuse visible light 0 2 R KDIR 0 75 Extinction coefficient for direct visible light 0 2 R EFF 0 45 Light use efficiency for real leaf 0 10 kg CO2 J adsorbed R List max CO2 assimilation rate 0 100 kg ha hr R as function of development stage 0 2 R i DVS AMAX maximum 15 records AMAXTB 0 00 30 000 1 57 30 000 2 00 0 000 End of table List reduction factor of AMAX R as function of average day temp 10 50 C R TAVD TMPF maximum 15 records TMPFTB 0 00 0 010 3 00 0 010 10 00 0 750 15 00 1 000 20 00 1 000 26 00 0 750 33 00 0 010 End of table List reduction factor of AMAX R as function of minimum day temp 10 50 C R TMNR TMNF maximum 15 records TMNFTB 0 00 0 000 3 00 1 000 End of table KKK KK KKK KK RK KK KK KK KK KK KK KK KK KK KK KK KK KK KK KK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK k ck k ck k ck k ck k ck k ck k RARA KKK KKK KK KK KK KK KK KK KK KK KK KK KK KK KK KK KK KKK KKK KKK KKK KKK KKK KKK KKK kck kck k KKK KKK ck k ck k ck k ck k ck k ck kck k ck k ck k ck kck kckok Part 6 Conversion of assimilates into biomass CVL 0 7200 Efficiency of conversion into leaves 0 1 kg kg R CVO 0 8500 Efficiency of conversion into storage organs 0 1 kg kg R CVR 0 7200 Efficiency of conversion into roots 0 1 kg kg R CVS 0 6900 Efficiency of conversion into stems 0 1 kg kg R KKK KK KK KKK KK KK KK KK KK KK KK K
75. flux is calculated from the groundwater level of the previous time step The relation between flux and groundwater level can be obtained from regional groundwater flow models e g Van Bakel 1986 Some special options are available to define qbot A zero bottom flux may be applied when an impervious layer exists at the bottom of the profile Impose a time series of qbot Calculate q at the start of a time step as a function of the groundwater level Pry of the previous timestep either by interpolation in a tabulated function or by using an exponential function defined as Qbot C bot exp Doot Have 2 16 where ay cm d and bp cm are empirical coefficients Alterra Report 1649 update02 Calculate q at the start of a time step as a function of the groundwater level of the previous timestep the hydraulic head in a semi confined aquifer Prout cm and the resistance of the semi confining layer c d according to bot Pogat Pais 2 17 ar Y i i Sati Io gt The flow resistance in the saturated zone between the groundwater level and the lower boundary has been accounted for by summation of the flow resistances Azi in this zone Some options for defining are available sat i 3 The Cauchy condition The flux q at the lower boundary is defined as a function of the prevailing pressure head This condition can be used when unsaturated flow models are combined with models for regional
76. fluxes evapotranspiration and rainfall data can be specified in more detail At the bottom various forms of head and flux based conditions are used In the horizontal direction SWAP s main focus is the field scale At this scale most transport processes can be described in a deterministic way as a field generally can be represented by one microclimate one vegetation type one soil type and one drainage condition Also many cultivation practices occur at field scale which means that many management options apply to this scale Upscaling from field to regional scale for broader policy studies is possible with geographical information systems The smallest time steps in SWAP are in the order of seconds for fast transport processes such as intensive rain showers with runoff or flow in macroporous clay soils These time steps are automatically increased in periods with less fluctuating flow conditions Depending on simulation complexity computation times for 50 year periods range from 30 to 500 seconds on ordinary personal computers 1 2 SWAP installation The SWAP model can be downloaded from Internet site www swap alterra nl This site contains also general information on model features applications and test reports Various SWAP versions are available at the Internet site all running under MS Windows SWAP2 0 7 d contains a graphical user interface This manual applies to SWAP3 2 Only the most recent SWAP version is supported by the Swap t
77. following two conditions are met the groundwater level is higher than the channel bed level the groundwater level is higher than the surface water level Sub irrigation can only occur if the following two conditions are met the surface water level is higher than the channel bed level the surface water level is higher than the groundwater level In both cases we take for the drainage base a cm either the surface water level Psur cm or the channel bed level Zbea cm whichever is higher 82 Alterra Report 1649 update02 C drain max o sur Zbed 4 1 The variable is defined positive upward with zero at the soil surface The drainage infiltration flux qais cm d to from each surface water system i is calculated from the linear relation arain i Pavg 7 Parainii 4 2 Y drain i Where grainj is the drainage base is equal to the surface water level of system i cm below the soil surface and y is the drainage resistance of system i d Similar to the case of single level drainage a drainage level is only active 1f either the groundwater level or the surface water level is higher than the channel bed level The drainage base is determined separately for each of the drainage levels In computing the total flux 47 to from surface water the contributions of the different channel drain orders are simply added n lanin A Adrain i 4 3 i 4 3 6 Multi level drainage with surface wate
78. for influence of minimum temperature on AMAX The photosynthesis process reduces the absorbed CO to carbohydrates CH5O using the energy supplied by the absorbed light For each kg of CO absorbed 30 44 kg of CH5O is formed the numerical values representing the molecular weights of CH5O 30 R A m where Ra Gross daily CH O assimilation rate not corrected for water stress kg CHO ha d Aa Gross daily CO assimilation rate corrected for low minimum temperature kg CO ha d The gross daily CH5O assimilation rate is subsequently corrected for water stress and nitriogen shortage Ri R F w F where R Gross daily CH2O assimilation rate kg CHO ha d Ra Gross daily CH2O assimilation rate not corrected for water stress kg CHO ha d Fy Water stress reduction factor Fa Nitrogen application reduction factor 266 Alterra Report 1649 update02 The water stress reduction factor is related to ratio of the actual transpiration and the potential transpiration F w La T where T Actual transpiration cm d Tp Potential transpiration cm d The nitrogen stress factor depends on the nitrogen application and the crop nitrogen uptake Not all applied feretilizer will be consumed by the crop An AFGEN table acronym relnitab with the applied Nitrogen amount kg as independent variable is used to describe this dependency Figure B16 4 Reduction factor as a function of the
79. for pesticide behaviour and emissions in soil plant systems Description of processes Alterra report 13 RIVM report 711401009 Alterra Wageningen 107 pp Lin H C Richards D R Yeh G T Cheng J R Cheng H P Jones N L 1997 FEMWATER A Three Dimensional Finite Element Computer Model for Simulating Density Dependent Flow and Transport in Variably Saturated Media Technical Report CHL 97 12 Waterways Experiment Station U S Army Corps of Engineers Vicksburg MS 39180 6199 Maas E V and G J Hoffman 1977 Crop salt tolerance current assessment J Irrig and Drainage Div ASCE 103 115 134 Maas E V 1990 Crop salt tolerance In Agricultural salinity assessment and management K K Tanji Ed ASCE Manuals and Reports on Engineering practice No 71 New York Makkink G F 1957 Testing the Penman formule by means of lysimeters J Int Water Eng 11 277 288 Massop H Th L and P A J W de Wit 1994 Hydrologisch onderzoek naar de gewasweerstanden van het tertiair ontwateringsstelsel in Oost Gelderland Report 373 Winand Staring Centre Wageningen The Netherlands 132 p 216 Alterra Report 1649 update02 Miller E E and R D Miller 1956 Physical theory for capillary flow phenomena J Appl Phys 27 324 332 Millington R J and J P Quirk 1961 Permeability of porous solids Trans Faraday Soc 57 1200 1207 Milly P C D 1985 A mass conservative procedure for time stepping in models of unsa
80. fraction of the actual freezable volumetric soil water content actual water content minus residual water content at depth z According to measured data from Kujala 1991 fice z can reasonably well be described by a linear function of soil temperature T z C between two threshold temper atures Fis 2 0 for T z 2 Ty 10 9 4 T T filz fe TO for Tau lt T 2 T 10 9 b frz mlt 196 Alterra Report 1649 update02 FON E EE for T z XT 10 9 0 where T is the temperature below which soil water starts freezing and Tmut is the temperature above which soil ice starts melting and below which all soil water except Ores is frozen A value of T5 lt 0 C expresses freezing point depression Taz and Tmt are model input with default values of O and 1 C The following parameters are adjusted in case of soil ice 1 hydraulic conductivity K K 2 f 2 KO Kain K min 10 10 where K z is the adjusted hydraulic conductivity at depth z cm d and K n is a very small hydraulic conductivity cm d For K a default value is taken of 107 cmd 2 actual crop uptake is reduced as S z 20 z with a 0 for T z lt 0 C 10 11 where o is a multiplication factor for soil temperatures 3 drainage fluxes of all drainage levels osito Fa z larani Z 10 12 where jain Z is the drainage flux at depth z from drainage level i cm d 4 bottom flux oor fr 2 Gpo 10 1
81. ha N 0 0 1000 0 kg ha N R DMfac reduction factor mfror N supply 0 1 0 R maximum 36 records Nsuptab DmFac 0 0 0 4 200 0 0 7 300 0 0 82 400 0 0 90 600 0 0 96 800 0 1 50 End of Table Nsupply for this field experiment in kg ha N Nsupply 600 0 f 0 0 1000 0 kg ha N R Ok ck kk kc kk ek ek kk ok kk OOOO OOOO OOOO A RR RA RA IRRIGATION SCHEDULING SECTION OK kk kk ke kk ek kk kk kk kk kk kk ko kk kk ko kk kk kk ko kk kk kk I kk ok kk ko kk A IR IO IR IO RK Part 1 General SCHEDULE 0 Switch for application irrigation scheduling Y 1 N 0 If SCHEDULE 0 no more information is required in this input file If SCHEDULE 1 continue with irrigation data identic to other crop input A files see other example input files for details FI II III ICI III ICI ICI III III III IIR ICICI III III A ke End of crp file 284 Alterra Report 1649 update02
82. i l i l Oa Oes The only unknown in Eq 2 13 is Os which can be directly solved The drying scanning curve is described accordingly with the parameters Qary n Ores Biar As long as the soil keeps drying this drying scanning curve is valid The opposite occurs when the soil gets wetter Again we start from the arbitrary actual water content 0 4 at the soil water pressure head act and now define 0 as the water content of the main wetting curve at hac and Ores as the residual water content of the wetting scanning curve Linear scaling of the main wetting curve with respect to the vertical axis 0 0 4 gives Fig 2 2B 0 0 0 0 x 6 9 sat res _ sat act gt 0 Z 0 E 8 sat act 2 13 Pa Oes Ds E Onw l i l l Di u O mw From Eq 2 14 0 4 can be directly solved The wetting scanning curve is accordingly described with the parameters Owen 71 Ores Osa and is valid as long as the soil keeps wetting As the wetting drying history is different at each soil depth each node may show a different scanning curve The unique K 0 relation of a soil layer always follows from the parameter set n Ores Osat Ksat A according to Eq 2 6 2 5 Frozen soil conditions Impacts of frozen soil moisture on soil water flow can optionally be described by a reduction of the hydraulic conductivity T T 3 2 14 cS K Ky K K nin max 0 min 1 min where K is the adjusted hydraulic conductivity
83. irrigation depth irgdepmin 1 0d7 mm I Alterra Report 1649 update02 207 208 Alterra Report 1649 update02 References Abenney Mickson S A Yomota and T Miura 1997 Water balance of field plots planted with soybean and pumpkin Trans ASAE 40 899 909 Allen R G M E Wright and R D Burman 1989 Operational estimates of evapotranspiration Agron J 81 650 662 Allen R G 1991 REF ET Reference evapotranspiration calculator version 2 1 Utah State University Logan 39 pp Allen R G L S Pereira D Raes and M Smith 1998 Crop evapotranspiration Guidelines for computing crop water requirements Irrigation and Drainage Paper 56 FAO Rome Italy 300 p Angus J F R B Cunningham M W Moncur and D H Mackenzie 1981 Phasic development in field crops I Thermal response in seedling phase Field Crops Research 3 365 378 Ashby M A J Dolman P Kabat E J Moors and M J Ogink Hendriks 1996 SWAPS version 1 0 Technical reference manual Technical document 42 Winand Staring Centre Wageningen Bear J 1972 Dynamics of fluids in porous media Elsevier Amsterdam Belmans C J G Wesseling and R A Feddes 1983 Simulation of the water balance of a cropped soil SWATRE J Hydrol 63 271 286 Beltman W H J J J T I Boesten and S E A T M van der Zee 1995 Analytical modelling of pesticide transport from the soil surface to a drinking water well J Hydrol 169 209 228 Beven
84. j At each new contact event Sp and 1 4 are updated 134 Alterra Report 1649 update02 The sorptivity approach assumes that the moisture content is not influenced by another process then sorption In the model moisture content 0 is also affected by vertical matrix flow and uptake by roots To account for this inadequacy for each time step sorptivity Sp is corrected according to the deviation A0 between actual 0 and theoretical Ome j moisture content at the beginning of the time step PETER E N A Spji Sp maxi 2 6 55 where A0 0 Ome For further explanation see Eq 6 30 Oe is computed with Eq 6 54 on the basis of initial sorptivity Sp that is obtained by Eq 6 55 without term A The lateral absorption rate during time step At is linearised to obtain an average con stant rate qua cm d t t At E Ds a IDs Qab j i m t 6 56 Infiltration rate qup cm d by lateral Darcy flow from domain j into compartment i reads in accordance to Eq 6 32 K sss hu Dubya Pf shp Awali En F P Fo 8 Ky a hui d pol 6 57 poli where fp is calculated with Eq 6 33 by using Qmp cm the water level in domain j and z The resulting lateral infiltration rate qu cm d from macropore domain j into unsaturated compartment i is derived from Eq 6 34 Lateral infiltration into and exfiltration out of the saturated matrix qi Rate of lateral water exchange
85. kg ha d At Time step d The death leaves weight Wa is subtracted from the weight of the oldest leaf class If there is only one class the result should be positive When more leaf classes exist the oldest leaf class may be emptied completely the remainder is subtracted from the next leaf class Emptying the oldest leaf class goes on until the original amount is dissipated completely and the remaining leaf amount remains positive All leaves are shifted every time step daily to the next class Stem death rate The stem death rate due to water stress is calculated in a similar way as the leaf death rate due to water stress using the same factor for the maximum relative death rate T AW W a Te qp mss p where AW Stem death rate due to water stress kg ha d Tmajv Maximum relative leaf death rate due to water stress kg kg d Wa Stem dry matter weight kg ha Ta Actual transpiration cm d Tp Potential transpiration cm d Grass assumes that the death rate due to ageing depends on the day number An AFGEN function with the day number as independent variable is used to describe this relation acronym rdrstb For further calculations the average of both death rates is used Note that in Grass rdrstb is set to zero for all day numbers Root extension Crop transpiration must be balanced by water uptake from the soil which depends on the potential difference between plant moisture and the soil moisture
86. lumped domain nam is reduced with 1 In this way the resolution of the horizontal discretisation in terms of nam is determined by nsa the thickness of Alterra Report 1649 update02 131 compartments and the shape of curve F the combination of large nsa small Az s in the IC domain and a linear F curve m 1 yields the largest nam 6 2 1 2 Persistency The volume of macropores Vp j i cm cm unit of area for domain j in compartment i is calculated for each time step At as V mp j i P Va V y 6 44 st i Static V and dynamic Vay macropore volume cm cm in each compartment i are obtained as explained below Dynamic volume is changing in time static volume is not Consequently if dynamic volume is present in compartment i the total macropore volume in this compartment is changing in time as well The total volume Vam cm cm of macropore domain j equals ndb Viu 2 Vos 6 45 i l where ndb is the number of the compartment that contains the bottom of domain j Static macropore volume The volumes of static macropores per compartment i for the MB and IC domain Veimbi and Vario cm cm are obtained by integration over Az Zi m Msn Vim dZ and Vaii Vsi AZ 6 46 Zbi Zb i The total volume of static macropores Vs in compartment i equals Vai Vamo V st i st mb i stic i 6 47 Dynamic macropore volume Dynamic macropore volume Vy cm cm in compartment i is co
87. macropores cracks and holes that are not interconnected and not connected to the MB domain and that end at different depths in the profile In this domain macropore inflow is entrapped at the bottom of individual macropores resulting in forced infiltration of macropore water into the mainly unsaturated soil matrix at different relatively shallow depths A B V cm cm Main bypass flow Internal catchment domain V dl Stc 0 04 0 00 Veimo 0 02 0 Figure 6 1 A schematic representation of the two main domains 1 Main bypass flow domain MB transporting water deep into the profile and possibly leading to rapid drainage 2 Internal catchment domain IC infiltration of trapped water into the mainly unsaturated matrix at different Va as a function of depth for the MB Va and IC Vic domain with the IC domain divided in several depths B mathematical description of the two domains as static macropore volume fraction sub domains Alterra Report 1649 update02 113 Figure 6 1 A presents a conceptual visualisation of the two classes of macropores Figure 6 1 B depicts a mathematical representation of the conceptual figure It describes the static macropore volume fraction Vs cm cm of the two domains Viumb and Vario as a function of depth From these two volume fractions the partition of the static macropore volume over the two domains at any depth can be calculated This partition as a
88. may specify Dai 0 The parameter dispersion length Lais cm depends on the scale over which the water flux and solute convection are averaged Typical values of Lai are 0 5 2 0 cm in packed laboratory columns and 5 20 cm in the field Jury et al 1991 In case of high salinity levels SWAP will reduce the root water uptake according to the reduction function of Maas and Hoffman 1977 see Fig 3 5 In order to apply this reduction function we should translate the simulated salinity concentration in the soil water to the salinity concentration in the saturated paste Bu C sat Cat sat 8 26 where Cacr is the actual salt concentration in the liquid phase mg cm Q4 is the actual volumetric soil water content cm cm Ova is the saturated volumetric soil moisture Bod n content cm cm Ll fis a factor to account for over saturation in the soil paste SWAP calculates the salt concentration of the saturated paste for each compartment Next the electrical conductivity is derived from the salt concentration Alterra Report 1649 update02 181 b E C a Csat 8 oF where EC is the electrical conductivity in the saturated paste extract dS m Caris the solute concentration in the liquid phase at saturated volumic soil moisture content mg cm and a and b are empirical coefficients The user should supply as input in the crop input file a b and f Section 7 4 As a general rule the mo
89. media Adv Water Resour 6 165 168 Huang K B P Mohanty and M Th van Genuchten 1996 A new convergence criterion for the modified Picard iteration method to solve the variably saturated flow equation J Hydrol 178 69 91 Hunt E R J A Weber and D M Gates 1985 Effects of nitrate application on Amaranthuspowellii Wats I Changes in photosynthesis growth rates and leaf area Plant Physiology 79 609 613 Ippisch O H J Vogel and P Bastian 2006 Validity limits for the van Genuchten Mualem model and implications for parameter estimation and numerical simulation Adv Water Resour 29 1780 1789 214 Alterra Report 1649 update02 Jacucci G P Kabat L Pereira P Verrier P Steduto C Uhrik G Bertanzon J Huygen B van den Broek J Teixeira R Fernando G Giannerini F Carboni M Todorovic G Toller G Tziallas E Fragaki J Vera Munoz D Carreira P Yovchev D Calza E Valle and M Douroukis 1994 The Hydra Project a Decision Support System for Irrigation Water Management Proceedings of the International Conference on Land and Water Resources Management in the Mediterranean Region 4 8 September 1994 Valenzano Bari Italy Jarvis N J 1989 CRACK A model of water and solute movement in cracking clay soils Technical description and user notes Report 159 Dept Soil Sci Swedish Univ Agric Sci Uppsala Sweden 37 pp Jaynes D B 1984 Comparison of soil water hysteresis models J
90. of e and V Va 7 AV 7 AV AeV 7 e e JV s sol 6 16 where e is the void ratio at saturation The shrinkage characteristic expresses the variable e as a function of the variable 9 cm cm which represents the moisture ratio e f 8 6 17 4 where the moisture ratio is defined as gom t 6 17 5 V 1 0 sol s with V cm cm the actual water volume fraction that equals 0 the volumetric moisture content of the matrix Volume fraction of solids V cm cm equals 1 6 0 0 at saturation Alterra Report 1649 update02 119 The exact form of the shrinkage characteristic depends on soil texture in terms of content and nature of clay minerals and organic matter Shrinkage characteristics of clay and organic soils peat and peaty soils differ strongly Shrinkage characteristic of clay and clayey soils Figure 6 4 A shows a typical shrinkage characteristic of a clay soil Three stages can be distinguished Stroosnijder 1975 Bronswijk 1988 1 Normal shrinkage volume decrease of clay aggregates is equal to moisture loss The aggregates remain fully saturated 2 Residual shrinkage upon drying the volume of the aggregates still decreases but moisture loss is greater than volume decrease Air enters the pores of the aggregates 3 Zero shrinkage soil particles reach their most dense configuration Upon further moisture extraction the volume of the aggregates remains constant Mo
91. or NRSRF swtopdislay madr Switch for each drainage level to distribute drainage flux vertically with a given position of the top of the model discharge layers 0 1 I 0 2no 1 yes ztopdislay madr Array with depth of top of model discharge layer for each drain level see also swtopdislay L SWDISLAY 2 then specify ftopdislay instead of ztopdislay ftopdislay madr Array with factor of top of model discharge layer for each drain level see also swtopdislay level is a dummy array just as either ztopdislay or ftopdislay level swtopdislay ztopdislay ftopdislay 055 end of SWDISLAY tabel 96 Alterra Report 1649 update02 5 Surface water management 5 1 Surface water balance Surface water management options have been implemented in the SWAP model by taking account of the water balance of the surface water The groundwater surface water system is described at the scale of a horizontal subregion The subregion has a single representative groundwater level and it is assumed that the soil profile occupies the whole surface area This results in water balance terms of the soil profile that are computed per unit area cm cm and have the same numerical value for the sub region as a whole The surface water system is simplified to a control unit for which the following surface water balance equation is formulated Wu dt sup ais Y Darin Teran Tranott 2 where Vour regional surface water st
92. output of SWAP is used as input in water quality calculations it is recommended to use another type of lower boundary condition 3 Calculate the bottom flux from the hydraulic head of a deep aquifer To illustrate this option figure 2 4 shows a soil profile which is drained by ditches and which receives a seepage flux from a semi confined aquifer SWAP makes a distinction between garain the local drainage flux to ditches and drains see Chapter 4 and qvo the bottom flux due to regional groundwater flow Alterra Report 1649 update02 47 aa SWAP soil column Groundwater level Figure 2 4 Pseudo two dimensional Cauchy lower boundary conditions in case of drainage to ditches and seepage from a deep aquifer The bottom flux q depends on the average groundwater level ayg cm the hydraulic head in the semi confined aquifer quif CM and the resistance of the semi confining layer c d Pags Pave 248 n Az C x n i i sat i where the subscript iew points to the compartment number in which the groundwater level is located The vertical resistance between the bottom of the model and the groundwater level may be taken into account by adding it to the aquitard resistance c The hydraulic head ui is prescribed using a sinusoidal wave 2x t tnax Prout Proitm T Paquita cos Quito 2 49 where a ae Paquita and Paquito are the mean cm ampl
93. pit Jee jH ni n l n 14x a Ya 3 h 9 a on ft YAz _ Azp 8h ba Ad Kj Seepage face AP Az 0 gt jl ex j K j j OF Az ja os m Ki OK iy hi hy E aCe An ORI TAE 1 i i i l i 1 2 1 ek j k OF Az cj Az Sa Ki Ky PV Arcu Oh P AU OC Oh YA Az y Az Azn ISA ine BI 021 aft ahs Az Az ahi Az Free drainage Sinn Kis Kis OF AZ cit n TAZ oe Oh V Az Az YAz ohj Ati OK hihi OK a K jd 1 T K j Oh Y2LAZ 1 Az Oh The internodal conductivity K 7 is in the case of free drainage irrespective the value of x always treated implicitly Alterra Report 1649 update02 238 Appendix 5 Implicit linearization of hydraulic conductivities An implicit linearization of hydraulic conductivities in the numerical elaboration of Eq requires expressions for the derivative of the conductivity to the pressure head jte p j Lp OK E _ 0K on on i l i l Arithmetic mean j K K p j Lp OK Ey m OK j 1 E j 1 oh P Oh 2 j K K p j Lp OK AZ 4 OK ony Az Az ani Weighted arithmetic mean j K K j 1 UE AZ oK Tm TE Un I Aza Az ORI T j K K p j Lp j l p aK EE Ki OK i j4l 2 l j4l 8h Ki Oh Geometric mean j k p j Lp j l p OK TY zb OK jp j l p j l p h K h Az E A ON E AZ e p pe OK gt P jp JEP REG pe oh Az RAZA OS 0h Weighted geometric mean Az j K
94. pot stem death rate kg ha d drstl stem death rate due to water stress kg ha d drst2 stem death rate due to ageing kg ha d dslv pot leaf death rate due to stress shading or water kg d dslv1 leaf death rate due to water stress kg d dslv2 leaf death rate due to mutual shading kg d drlv pot total death rate leaves kg d dtga pot gross daily CO assimilation rate kg ha d dwlv pot dry weight death leaves kg ha dwrt pot dry weight death roots kg ha dwst pot dry weight death stems kg ha dteff daily effective temperature C eff light use efficiency of single leaf kgha hr Im s fr root partitioning factor fs stem partitioning factor fl leaves partitioning factor fltb list fraction of total dry matter increase partitioned to kg kg the leaves as function of day number frtb list fraction of total dry matter increase partitioned to kg kg the roots as function of day number fstb list fraction of total dry matter increase partitioned to kg kg the stems as function of day number gass pot available assimilates after correction for drought stress kg ha d glaiexp pot leaf area index growing rate during the exponential ha ha d growing phase gla pot leaf area index growth rate glasol pot source limited leaf area index growing rate ha ha d grlv pot leaf growth rate kg ha d grrt pot roots growth rate kg ha d grst pot stem grow
95. prescribe a minimum interval between irrigated applications 11 2 1 1 Allowable daily stress The level of soil water shortage by drought and salinity stress may be diagnosed from a threshold defined by the ratio of reduced transpiration 7 to potential transpiration T Irrigation is applied whenever reduced transpiration becomes lower than a limit defined by this threshold T lt fiT 11 2 where T is the transpiration reduced by drought and salinity stress cm d T is the potential transpiration cm d fi C is a user defined factor for allowable daily stress 11 2 1 2 Allowable depletion of readily available water In order to optimize irrigation scheduling where irrigation is always secured before conditions of soil moisture stress occur the maximum amount of depletion of readily available water in the root zone can be specified Irrigation is then applied whenever the water depletion exceeds fraction f of the readily available water amount Ussa 0 2 f Uri U 11 3 where U cm is the actual water storage in the root zone U 4 cm is the root zone water storage at h given value for field capacity and U cm is the root zone water storage at h hz the pressure head from where root water extraction starts being reduced due to drought stress f is a user defined depletion fraction U is calculated by integrating numerically the water content in the rooting layer For deficit irrigation purposes str
96. pressure head h3 increases for higher potential transpiration rates Tp Alterra Report 1649 update02 61 E Cotope d 0 0 0 0 E ha hy h 0 0 0 0 EC max Soil water pressure head Soil water electrical conductivity A Figure 3 4 Reduction coefficient for root water Figure 3 5 Reduction coefficient for root uptake 0 as function of soil water pressure head h water uptake ars as funetion of soil water and potential transpiration rate T after Feddes et electrical conductivity EQ after Maas and al 1978 Hoffman 1977 SWAP uses the response function of Maas and Hoffman 1977 for salinity stress Fig 3 5 Below salinity concentrations of ECmax dS m no salinity stress is assumed At salinity levels above ECmax the root water uptake declines at a rate of EC gope m dS In case of both water and salt stress Skaggs et al 2006 argue that we may multiply the stress factors for water and salt stress In SWAP we follow this multiplication approach and calculate the actual root water flux Sa z d by S 2 A gb wA 05 S 2 2 68 where Qa Any 05s and a are the reduction factors due to wet conditions h gt h2 drought stress h lt h3 salinity stress and frozen soil conditions Par 10 2 Integration of S z over the root layer yields the actual transpiration rate T cm d T S 2 69 LINEXOT 2 69 Splitting up the total transpiration reduction into individu
97. quj cm d between macropore domain j and saturated compartment i by Darcy flow is computed in accordance to Eq 6 35 his us fas 8K saci Bayi Pa mpj i mti shp sat i mpj i mt i disDj i 7 Pf as Awani K sati x P d 6 58 pol i pol i and in case of a seepage face Ampy 0 according to Eq 6 36 hu i l 6 59 a dis seep j i gt Yates Y nor i F Y radi Alterra Report 1649 update02 135 mE 6 59 b Mera E t 2 oli gt 6 59 c e 8K AZ d Az Ya hn 5 6 59 4 rad i TK u sat i seep i where Useep i is set to 10 of Azi Lateral exfiltration out of the saturated matrix as interflow qiu Lateral exfiltration rate qli j i cm d 1 out of compartment i with perched groundwater into macropore domain j by interflow is calculated according to Eq 6 58 and Eq 6 59 with an opposite sign Rapid drainage q a The actual drainage resistance Yact d for calculating rapid drainage flux qra cm d according to Eq 6 30 is obtained by nb act ha cr act i Az i d iMac poli Yact nbe m Y er 6 60 y Wenrefi Az i Ml ef poli where nl and nb are the numbers of the compartments with the water level and the bottom of the MB domain respectively for actual and reference situation For use in solute models the rapid drainage flux qra is distributed over the compartments nlac to NDact according to their relative KD values Na War acti Az La poli fidi x x dra 6 61 cr ac
98. radiation J m d and sin Bmod sun the integral of sin Bsun over the day which is corrected for reduced atmospheric transmission at low solar elevations A diffuse radiation flux results from scattering of sun rays by clouds gases and dust in the atmosphere To quantify the degree of scattering the measured daily total radiation is compared with the amount that would have reached the Earth s surface in the absence of an atmosphere which can be calculated as S 1 1810 1 0 033 222 7 7 365 where Ssn is the solar constant J m d and j the day number in the year DOY The ratio of potential and measured daily total radiation is called atmospheric transmission A The proportion of diffuse radiation Irait is derived from the atmospheric transmission by an empirical relationship Spitter et al 1989 Taking also into account that only 50 percent of the solar radiation is photosynthetically active the diffuse photosynthetically active radiation PAR4i J m d can thus be calculated by PAR ge 9 5 lag A S Sin Boun 7 8 The direct radiation flux PARair J m d is obtained by subtracting the diffuse part from the photosynthetically active radiation flux PAR PAR PAR 7 9 7 3 3 Radiation profiles within the canopy The incoming PAR is partly reflected by the canopy The reflection coefficient is defined as the fraction of the downward radiation flux that is reflected by the entire can
99. rainfall and irrigation This is required because the solute concentration of both water sources may be different Observed rainfall Poros minus intercepted rainfall P is called net rainfall Paet Likewise applied irrigation depth Zeross minus intercepted irrigation water is called net irrigation depth Zret The method of Von Hoyningen H ne and Braden is based on daily precipitation values Although rainfall may be specified in smaller time steps the interception will be based on daily amounts 3 2 2 Forests An important drawback of the method of Von Hoyningen H ne and Braden is that the effect of rain duration and evaporation during the rain event is not accounted for In case of interception by trees and forests the effect of evaporation during rainfall can not be neglected Gash 1979 1985 formulated a physically based and widely used interception formula for forests He considered rainfall to occur as a series of discrete events each comprising a period of wetting up a period of saturation and a period of drying out after the rainfall The canopy is assumed to have sufficient time to dry out between storms During wetting up the increase of intercepted amount is described by ap Ot P 1 p Po Pren Eno 2 54 where p is a free throughfall coefficient p is the proportion of rainfall diverted to stemflow Pmean is the mean rainfall rate mm h 5 Emean 18 the mean evaporation rate of intercepted water when the
100. soil A green vegetation cover has an albedo of about 0 20 0 25 De Bruin 1998 SWAP will assume in case of a crop a 0 23 in case of bare soil q 0 15 The earth emits longwave radiation which increases with temperature and which is adsorbed by the atmosphere or lost into space The longwave radiation received by the atmosphere increases its temperature and as a consequence the atmosphere radiates energy of its own Part of this radiation finds its way back to the earth s surface As the outgoing longwave radiation is almost always greater than the incoming longwave radiation the net longwave radiation Rw represents an energy loss Allen et al 1998 recommend the following formula for the net longwave radiation nl 4 4 R o Tm tia oaa 0 14 e 0 1 0 9N where Os is the Stefan Boltzmann constant 4 903 10 J K m d Tmin and Tmax are the minimum and maximum absolute temperatures during the day K respectively a is the actual vapour pressure kPa and Ne is the relative sunshine duration The latter can be derived from the measured global solar radiation R and the extraterrestrial radiation R J m d which is received at the top of the Earth s atmosphere on a horizontal surface where a and b are empirical coefficients which depend on the local climate For international use Allen et al 1998 recommend a 0 25 and b 0 50 The extraterrestrial radiation R depends on the latitude and the day of t
101. soil depends upon its mineral composition and organic matter content as well as the volume fractions of water and air Since the thermal conductivity of air is much smaller than that of water or solid matter a high air content or low water content corresponds to a low thermal conductivity The components that affect neat are the same as those affecting Chea However the variation in Anea is much greater than that of Chea In the range of soil wetness normally experienced in the field Chea may undergo a threefold or fourfold change whereas the corresponding change in Anea may be hundredfold or more Unlike heat capacity thermal conductivity is also sensitive to the sizes shapes and spatial arrangements of the soil particles Hillel 1980 The thermal conductivity is found by considering the soil as a continuous liquid or gaseous phase in which soil and respectively gas or liquid particles are dispersed In the case of a wet soil 0 gt 0 4 liquid water is assumed to be the continuous phase and the thermal conductivity is given by Ji X sand water Tasa ad X ctay water Tas t A enei oa ak a a F Xs Jair Nair 9 11 heat X x 0 2 K air water Fai x A oe PEE SM sand water J sand clay water clay organic water Y organic water water The k values on the right hand side of Eq 9 11 refer to the thermal conductivities J cm C d of each individual component as listed in Table 9 1 The weighting factor
102. systems number as a rapid drainage system and 3 specification of a ponding threshold Parameters to relate EC of saturated paste extract to the mandatory c 163 actual salt concentration 181 Crop growth of grasland according to wofost approach optional Y ET q 265 SWAP version 3 2 Theory description and user manual J G Kroes J C Van Dam P Groenendijk R F A Hendriks C M J Jacobs Alterra Report1649 02 Swap32 Theory description and user manual doc Alterra Wageningen 2008 ABSTRACT Kroes J G J C Van Dam P Groenendijk R F A Hendriks C M J Jacobs 2008 SWAP version 3 2 Theory description and user manual Wageningen Alterra Alterra Report1649 02 Swap32 Theory description and user manual doc 262 pages 47 figs 12 tables 39 boxes 249 refs SWAP 3 2 simulates transport of water solutes and heat in the vadose zone It describes a domain from the top of canopy into the groundwater which may be in interaction with a surface water system The program has been developed by Alterra and Wageningen University and is designed to simulate transport processes at field scale and during whole growing seasons This 1s a new release with special emphasis on numerical stability macro pore flow and options for detailed meteorological input and linkage to other models This manual describes the theoretical background model use input requirements and output tables Keywords agrohydrology drainage eva
103. t during the source limited growth stage ha ha da AWy Dry matter growth of leaves at time step t kg ha d Sia Specific leaf area at time step t ha kg The exponential growth is limited by the available assimilates for leaf growth i e source limited growth L min L Los exp t where L Leaf area index growth rate at time step t ha ha da The accumulated leaf area index at time step t is described as LAI LAI L At where LAI Leaf area index at time step t ha ha At Time step d 272 Alterra Report 1649 update02 LAI is initialized by setting the starting value equal to the leaf area index at emergence acronym LAIEM The specific leaf area Sj acronym SLATB is defined as the leaf area increase per kg living leaf increase see Fig Grass assumes that Sj is a function of the day number This dependency is described using an AFGEN table with the day number as the independent variable Figure B16 6 Specific Leaf Area 0 0025 y Oe NEM Im 0 0015 0 001 ha kg 0 0005 4 Day Figure B16 6 Specific Leaf Area SLA as function of time Special attention should be paid to the exponential growth during this stage the specific leaf is not established and has to be calculated according to Ls t S uos AW where Sap Specific leaf area at time step t during the exponential growth stage ha kg AW Leaf dry matter increase kg ha
104. the extension denotes the year A main choice is whether pre calculated ET are used SWETR 1 or basic data on solar radiation air temperature air humidity and wind speed These basic weather data may be 64 Alterra Report 1649 update02 specified daily or with shorter constant time intervals SWMETDETAIL 1 In case of daily meteorological weather records SWAP may distribute the evapotranspiration fluxes uniform over the day default or sinusoidal during daylight SWETSINE 1 As listed in Box 3 1 the rainfall input may range from daily amounts to short time rainfall amounts Box 3 1 General information on meteorological input in main file SWP METEOROLOGY SECTION KK KK KK KK KK KK KA KKK KKK KKK KKK KKK KK KK KK KKK KKK KKK KKK KKK KKK KKK kck ck ck k ck ck ckck ck k ck k ck k ck k ck k ck ok KK KKK General data METFIL Wageningen File name of meteorological data without extension YYY A16 Extension equals last 3 digits of year number e g 2003 has extension 003 SWETR 0 Switch use reference ET values of meteo file Y 1 N 0 If SWETR 0 then LAT ALT and ALTW must have realistic values LAT 52 0 Latitude of meteo station 60 60 degrees R North ALT 10 0 Altitude of meteo station 400 3000 m R ALTW 2 0 Altitude of wind speed measurement 0 99 m R Use of detailed meteorological records shorter time interval than one day SWMETDETAIL 0 Switch use detai
105. the ground The user specifies as a function of development stage either leaf area index or soil cover fraction along with crop height and rooting depth The development stage can be controlled either by the temperature sum or can be linear in time Alterra Report 1649 update02 147 The simple model does not calculate the crop potential or actual yield However the user may define yield response factors Doorenbos and Kassam 1979 Smith 1992 for various growing stages as a function of development stage For each growing stage k the actual yield Y x kg ha relative to the potential yield Y ox kg ha during this growing stage is calculated by 1 Yax K 1 um 7 1 k Y d Tz where Ky x is the yield response factor of growing stage k and Tpx cm and Tax cm are the potential and actual transpiration respectively during growing stage k The relative yield of the whole growing season is calculated as the product of the relative yields of each growing stage Y p Yx E 7 2 P pk where Y is the cumulative actual yield kg ha of the whole growing season Y is the cumulative potential yield kg ha of the whole growing season index k is the growing stage and n is the number of defined growing stages 7 3 Detailed crop module Three groups of growth factors Fig 7 1 may be distinguished to obtain a hierarchy of production levels in crop production Van Ittersum et al 2003 Growth
106. this parameter can save a substantial amount of water Alterra Report 1649 update02 105 Box 5 3 Input of surface water levels in drainage file DRA Part 3 surface water level in secondary water course is input Table with Water Levels in the Secondary system max 52 Water level in secondary water course WLS ALTCU 1000 ALTCU 0 01 cm R as function of DATE2 dd mmm yyyy DATE2 WLS 24 Apr 1993 77 25 Apr 1993 78 26 Apr 1993 79 29 Dec 2000 86 30 Dec 2000 86 31 Dec 2000 85 End_of_table KK ROK ROK ROK RK RK ck ck ck ckckckck ck ck ck ck ck ck ckck ck ck ck ck ck ck ck ck ck ck ckck ck ck RK RK RK KK RK RK RR RK RR OR OK OR OK OK OK ck ck OK OK OK Box 5 4 Simulation of surface water levels in drainage file DRA KKK KKK KK KKK KKK KKK KKK KKK KK KKK KKK KKK KKK KKK KKK KKK KKK KKK kck kck kck ck ckck ck ck ckck ck k ck k ck k ck KKK KKK AK Part 4 surface water level is simulated KKK KKK KKK KKK KK KKK KKK KK KKK KK KK KKK KKK KK KKK KKK KK KKK KKK KKK kck kck ck ck k ck k ck k ck k ck k ck ck ck k ck ck KKK AK Part 4a Miscellaneous parameters WLACT 77 0 initial surface water level ALTCU 1000 ALTCU cm R OSSWLM 2 5 criterium for warning about oscillation 0 10 cm R ES Part 4b management of surface water levels NMPER 34 number of management periods 1 10 I For each management period specify IMPER index of management period 1 NMPER I IMPEND date that perio
107. to 0 lt S Vam In case of water deficit S lt 0 all outgoing fluxes are decreased with a part of the deficit according to their relative rate In case of water excess S gt Vas all incoming fluxes are decreased with a part of the excess according to their relative rate The excess of the inflow at soil surface is distributed over macropore domains that are not fully filled up that is if S lt Vam for a particular domain The remaining excess is added to the ponding layer Inflow at soil surface Ip and I The inflow at the soil surface fluxes Ipr and Iru cm d 1 are calculated according to Eq s 6 25 to 6 28 with the relevant properties of the first compartment When these fluxes exceed storage capacity of total macropore volume the inflow excess is added to the ponding layer before calculation of regular runoff takes place Distribution of Jp and Z over all macropore domains j is according to the domains proportions at soil surface that is in model compartment 1 T P ly and Laj Puls 6 53 Lateral infiltration into the unsaturated matrix qu Cumulative lateral absorption lay cm for all compartments i of the unsaturated matrix that are in contact with water in macropore domain j is computed according to Eq 6 29 AAZS il D agi Laji P Ana pia bunk P 6 54 d NU SA poli Az t where fcum i d is the cumulative time since first contact of compartment i with water in macropore domain
108. well established methodology to apply the Penman Monteith equation for evapotranspiration estimates at a daily time scale using routinely measured weather data Allen et al 1998 The required weather data include daily values of air temperature preferably the minimum as well as the maximum value global radiation wind speed and relative humidity The FAO methodology is applied in SWAP and the basic equations are listed in 0 In general the parameter rj is used to calculate ET from a mixture of vegetation and bare soil in which case this parameter is called the surface resistance r In SWAP we will always apply the Penman Monteith method to either vegetations fully covering the soil or bare soils Therefore we replace r by Ferop at bare soils Ferop is absent and equals zero SWAP calculates three quantities for three uniform surfaces Alterra Report 1649 update02 57 e ETyo cm d evapotranspiration rate from a wet canopy completely covering the soil e ET cm d evapotranspiration rate from a dry canopy completely covering the soil e Es cm d evaporation rate from a wet bare soil These ET quantities are obtained by varying the values for crop resistance Ferop crop height Aerop and reflection coefficient for the three uniform surfaces as listed in Table 3 1 For a dry crop completely covering the soil with optimal water supply in the soil rao is minimal and varies between 30 s m for arable crop to 150 s m
109. zone weighted by the root density Actual evaporation depends on the capacity of the soil to transport water to the soil surface SWAP uses the soil hydraulic functions and semi empirical equations to determine this transport capacity Chapter 3 Surface runoff will be calculated when the height of water ponding on the soil surface exceeds a critical depth The rate of surface runoff depends on a specified resistance Interflow may occur when the groundwater level becomes higher than the interflow drainage level Drainage can be calculated with the Hooghoudt or Ernst equations with a table relating drainage flux and groundwater level or with drainage resistances per Alterra Report 1649 update02 11 drainage system In order to calculate proper residence times of solutes the drainage fluxes are vertically distributed according to so called discharge layers Chapter 4 The water balance of the surface water system can be calculated to analyse water management options Surface water levels can be imposed or derived by setting soil moisture criteria groundwater level pressure head minimum storage in combination with a weir Chapter 5 Macroporosity can be caused by shrinking and cracking of soil by plant roots by soil fauna or by tillage operations The macropore module in SWAP includes infiltration into macropores at the soil surface rapid transport in macropores to deeper layers lateral infiltration into and exfiltration out of the
110. 0 Plant Transpiration 25 82 Soil Evaporation 14 42 Runon 0 00 Runoff 0 00 Inundation 0 00 Infiltr Soil Surf 54 69 Infiltr Soil Surf 54 69 Exfiltr Soil Surf TED Exfiltr Soil Surf 7 57 Infiltr subsurf Drainage system 1 0 00 system 1 2 7 Upward seepage 0 00 Downward seepage 0 00 4p Sum 66 06 0 00 69 11 126 76 Sum 66 06 0 00 69 11 126 76 4 Storage Change 0 00 0 00 0 12 Balance Deviation 0 00 0 00 0 00 0 00 24 Alterra Report 1649 update02 Gross irrigation Interception PLANT Nett rainfall Nett irrigation Precipitation LA Gross rainfall Snowfall Sublimation Infiltration exfiltration Inundation Soil evaporation Up downward seepage Plant transpiration Runoff as dl Drainage Infiltration surface water Figure 1 3 Scheme of water fluxes between the subdomains plant snow ponding layer soil and surface water In this case also the cumulative and incremental fluxes are requested at the end of each month Box 1 7 shows the incremental water fluxes for the same year 1980 The actual transpiration rates are close to the potential transpiration rates due to the high rain amounts in the summer season and the relatively shallow groundwater level In May th
111. 0 0123 0 0138 The parameters of the Mualem van Genuchten model are explained in Chapter 2 246 Alterra Report 1649 update02 0 000 1 060 0 215 0 000 0 359 1 747 0 802 2 244 2 161 3 884 5 901 5 681 1 497 0 000 1 476 2 259 0 350 1 845 0 000 0 168 0 000 0 000 0 000 1 330 2 023 0 803 1 382 1 879 1 384 4 295 5 955 0 292 0 912 1 411 1 592 1 204 n 1 801 1 491 1 534 1 406 1 933 1 238 1 250 1 288 1 325 1 210 1 109 1 094 1 441 1 305 1 280 1 293 1 140 1 154 2 286 951 717 525 2 374 311 152 342 400 257 1 152 1 158 1 089 1 728 1 298 1 376 1 276 1 323 Appendix 8 Critical pressure head values for root water extraction After Taylor and Ashcroft 1972 Crop Vegetative crops Alfalfa Beans snap and lima Cabbage Canning peas Celery Grass Lettuce Tobacco Sugar cane tensiometer blocks Sweet corn Turfgrass Root crops Onions early growth bulbing time Sugar beets Potatoes Carrots Broccoli early after budding Cauliflower Fruit crops Lemons Oranges Alterra Report 1649 update02 1500 750 600 300 200 300 400 300 150 1000 500 240 1500 2000 700 500 300 1000 600 800 500 2000 1000 360 Crop Deciduous fruit Avocadoes Grapes early season during maturity Strawberries Cantaloupe Tomatoes Bananas
112. 0 cm R ISOILLAY1 ORES OSAT ALFA NPAR KSAT LEXP ALFAW H_ENPR I 0 01 0 43 0 0227 1 548 9 65 0 983 0 0454 0 0 2 0 02 0 38 0 0214 2 075 15 56 0 039 0 0428 0 0 end of table OR If SWSOPHY 0 the intro of additional saturated hydraulic conductivity ksatexm is possible Specify for each soil layer maximum MAHO KSATFIT and KSATEXM like the example below ISOILLAY1 ORES OSAT ALFA NPAR KSATFIT LEXP ALFAW H ENPR KSATEXM L 0 01 0 43 0 0221 1 548 9 65 0 983 0 0454 0 0 18 0 2 0 02 0 38 0 0214 2075 15 56 0 039 0 0428 0 0 30 0 KKK RK kk RK kk RK KK KK KA RK KR KK KKK ck ck ck ck ck ck kckckckckckckckckckck ck kckck ck k ck k ck k ck k ck k ck ck ck k ck k ck k ck k ck k ck KKK EK Alterra Report 1649 update02 45 Kk kk kk KKK KKK KKK KKK KK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KK KKK KKK ck kckck RARA RRA RRA RARA Part 6 Hysteresis of soil water retention function Switch for hysteresis SWHYST 0 0 no hysteresis YL hysteresis initial condition wetting LR hysteresis initial condition drying iT If SWHYST 1 or 2 specify TAU 0 2 Minimum pressure head difference to change wetting drying 0 1 cm R kk kk ke ke ke ce e ke kk ke ke ke ce ck kk ke ke KKK KKK KK KKK KKK KKK KK KKK KKK KKK KKK ke ce ck ck ko kk ck ck ck ck ck ck kk kc kk kk ck kv k k kckckok kk KK KKK KKK ck ck KKK KKK KK KKK KK KKK KKK KK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KAKA ckck ck k ck ck RARA RA Part 11 Numerical s
113. 1992 Monitoring and modelling forest hydrological processes in support of acidification research Diss Univ A dam 218 pp Braden H 1985 Ein Energiehaushalts und Verdunstungsmodell for Wasser und Stoffhaushaltsuntersuchungen landwirtschaftlich genutzer Einzugsgebiete Mittelungen Deutsche Bodenkundliche Geselschaft 42 294 299 Bresler E and G Dagan 1983 Unsaturated flow in spatially variable fields 2 Application of water flow models to various fields Water Resour Res 19 421 428 Bronswijk J J B 1988 Modeling of water balance cracking and subsidence of clay soils J Hydrol 97 199 212 Bronswijk J J B and J J Evers Vermeer 1990 Shrinkage of Dutch clay soil aggregates Neth J of Agric Sci 38 175 194 Bronswijk J J B W Hamminga and K Oostindie 1995 Field scale solute transport in a heavy clay soil Water Resour Res 31 517 526 Brooks R H and A T Corey 1964 Hydraulic properties of porous media Colorado State Univ Hydrology paper no 3 p 27 Bruin R A 1998 Micrometeorology Lecture notes 06252207 Wageningen University 156 p Brunt D 1952 Physical and dynamical meteorology Second edition University Press Cambridge 428 pp Burman R D M E Jensen and R G Allen 1987 Thermodynamic factors in evapotranspiration In Proc Irrig and Drain Spec Conf L G James and M J English Eds ASCE Portland Ore July p 28 30 210 Alterra Report 1649 update02 Carrera
114. 1994 SWAP2 0 was published by Van Dam et al 1997 and Kroes et al 2001 The latest version was published as SWAP3 0 3 by Kroes and Van Dam eds 2003 Main differences between the current version SWAP 3 2 and the previous version are e Source code was restructured e Numerical stability has been largely improved e MacroPore flow is operational e Detailed rainfall and evapotranspiration data is optional e Testing has been strongly intensified All reports together with the SWAP program and examples are available through the SWAP development group and the Internet www swap alterra nl The general reference to the SWAP model is Van Dam 2000 The reference to recent advances is Van Dam et al 2008 The reference to numerical algorithm is Groenendijk and Kroes in prep The reference to macropore flow is Hendriks et al in prep Alterra Report 1649 update02 9 10 Alterra Report 1649 update02 Summary SWAP simulates transport of water solutes and heat in the vadose zone in interaction with vegetation development In the vertical direction the model domain reaches from a plane just above the canopy to a plane in the shallow groundwater In this zone the transport processes are predominantly vertical therefore SWAP is a one dimensional vertically directed model In the horizontal direction SWAP s main focus is the field scale The SWAP model can be downloaded from site www swap alterra nl The model input ma
115. 2 5 00 0 0001378 1318 00 0 0 end of Table KOK ck ck ck ck KK KK KK KK KK KK KK KK KK kckckckckck ck ck kckckckckckckckckckckck kck kck kckck ck k ck ck ck k ck k ck k ck k ck k ck k ck k ck k ck k ck k ck k ck kckokck ck KK KK KK KK KA KK KA KA KA KA KA KA ck ck ckckckckckckckckckck kckckckckckckck kckck ck k ck k ck k ck k ck k ck k ck k ck k ck k ck k ck k ck k ck k ck kckokck Part 4 Diffusion constant and solute uptake by roots DDIF 0 0 Molecular diffusion coefficient 0 10 cm2 day R TSCE 0 0 Relative uptake of solutes by roots 0 10 R KOK KKK KKK KKK KKK KKK KK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK ck kckckckck ck kckck ck ck KKK KKK KKK KOK KK KK KKK KKK KK KK KK KK KK KK KKK KKK KKK KKK KKK KK kck k ck k ck k ck k ck k ck k ck k ck k ck k ck k ck k ck k ck KKK K EK Part 5 Adsorption SWSP Ml o Switch consider solute adsorption Y 1 N 0 In case of adsorption SWSP 1 specify FREXP 0 9 Freundlich exponent 0 10 R CREF 1 0 Reference solute concentration for adsorption 0 1000 mg cm3 R KKK KKK KKK KKK KKK KKK KKK KKK KKK KK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KK KKKKKKE KKK KKK KOK KK KK KK KK KK KK KK KK KK KK KK KKK KKK KK KKK KKK KK KKK KK KKK ck k ck k ck k ck k ck k ck k ck k ck k ck k ck k ck kck k ck kck Part 6 Decomposition SWDC 0 Switch consideration of solute decomposition Y 1 N 0 In case of solute decompos
116. 260 218 Alterra Report 1649 update02 Sidle R C S Noguchi Y Tsuboyama and K Laursen 2001 A conceptual model of preferential flow systems in forested hillslopes evidence of self organization Hydrol Process 15 1675 1692 Singh P G Spitzbart H H bl H W Weinmeister 1997 Hydrological response of snowpack under rain on snow events a field study Journal of Hydrology 202 1 20 im nek J T Vogel and M Th van Genuchten 1992 The SWMS 2D code for simulating water flow and solute transport in two dimensional variably saturated media Version 1 1 Res Rep 126 U S Salinity Lab Agric Res Ser U S Dept of Agric Riverside Calif Sim nek J K Huang M Sejna and M Th van Genuchten 1998 The HYDRUS 1D Software Package for Simulating the One Dimensional Movement of Water Heat and Multiple Solutes in Variably Saturated Media Version 1 0 IGWMC TPS 70 Int Ground Water Modeling Center Colorado School of Mines Golden CO 186 p Sim nek J R Kodesova M M Gribb and M T van Genuchten 1999 Estimating hysteresis in the soil water retention function from cone permeameter experiments Water Resour Res 35 1329 1345 Sim nek J M Sejna and M Th van Genuchten 2007 The HYDRUS Software Package for Simulating the Two and Three Dimensional Movement of Water Heat and Multiple Solutes in Variably Saturated Media User Manual Version 1 0 PC Progress Prague Czech Republic Skaggs T H
117. 3 where q is the flux across the bottom of the modelled soil profile and z the bottom depth 5 boundary fluxes drainage and bottom when the available air volume is very low When drainage does not occur and the available air volume is very low lt 0 01 cm cm the bottom flux is reduced to zero When drainage occurs and the available air volume is very low lt 0 01 cm cm the drainage fluxes of frozen soil compartments above the drainage level are reduced to zero Alterra Report 1649 update02 197 198 The available air volume in the soil Vair cm for a soil profile that becomes saturated equals m Vair 2 o x 0 Azj 10 14 where 0 is the saturated water content cm cm 0 is the actual water content cm cm i is a node number n is the node number of the bottom compartment m is the node number of the highest soil compartment with a temperature below Tmt Starting to count from the bottom compartment and Az is the nodal distance Zi Zia When a soil compartment is frozen T z lt T mi the pore volume of the total soil profile becomes smaller because only the compartments below this layer are used in the calculation An example is a soil in spring that is melting figure 10 2 The lower compartments were never frozen and the melting starts at the soil surface It is possible that the first 4 compartments have melted and only the compartments 5 8 are frozen Now the air volume is
118. 3 Dekker L W and C J Ritsema 1994 How water moves in a water repellent sandy soil 1 Potential and actual water repellency Water Resour Res 30 2507 2517 Dekker L W and C J Ritsema 1996 Preferential flow paths in a water repellent clay soil with grass cover Water Resour Res 32 1239 1249 Dekker L W 1998 Moisture variability resulting from water repellency in Dutch soils PhD thesis Wageningen University 240 p De Rooij G H 1996 Preferential flow in water repellent sandy soils Model development and lysimeter experiments Ph D thesis Wageningen Agricultural University The Netherlands 229 p Desbarats A J 1995 An interblock conductivity scheme for finite difference models of steady unsaturated flow in heterogeneous media Water Resour Res 31 2883 2889 De Smedt F and P J Wierenga 1979 A generalized solution for solute flow in soils with mobile and immobile water Water Resour Res 1137 1141 De Vries D A 1975 Heat transfer in soils In Heat and mass transfer in the biosphere I Transfer processes in plant environment De Vries D A and N H Afgan eds Scripts Book Company Washington D C p 5 28 De Wit C T et al 1978 Simulation of assimilation and transpiration of crops Simulation Monographs Pudoc Wageningen The Netherlands 100 pp Dirksen C 1979 Flux controlled sorptivity measurements to determine soil hydraulic property functions Soil Sci Soc Am J 43 827 834
119. 30 3 Specify day and month after which irrigation scheduling is allowed dd mm ENDIRR 31 12 Specify day and month after which irrigation scheduling is NOT allowed dd mm CIRRS 0 0 ISUAS 1 Switch for type of irrigation method 0 sprinkling irrigation l i solute concentration of scheduled irrig water 0 100 mg cm3 R T if rI surface irrigation Specify pressure head at field capacity required for timing options TCS 2 3 or 4 and depth option DCS 1 else dummy phFieldCapacity 100 0 soil hydraulic pressure head 1000 0 0 0 cm R KK KK KK kk kk KA KKK KKK KKK KK KKK KKK KK KK KKK KKK KK KKK KKK KKK KKK KKK kck ck ck k ck KKK ck k ck ck ck ck ckck ck k ck ck KKK AK Alterra Report 1649 update02 205 Box 11 3 Scheduled irrigation timing criteria in the CRP file IRRIGATION SCHEDULING part 2 KKK KKK KK KKK KKK KK KKK KKK KKK KKK KKK KKK KKK KK KKK KKK KKK KKK KKK KKK KKK KKK RARA RARA RRA RARA Part 2 Irrigation time criteria Choose one of the following 5 timing options TCS 1 Switch timing criterion EL so Y 1 Daily Stress Depletion of Readily Available Water Depletion of Totally Available Water Depletion Water Amount Pressure head or moisture content E I Fixed weekly irrigation rootzone to field capacity DUO wn Daily stress criterion TCS 1 If TCS 1 specify mimimum of ratio actual potential transpiration Trel 0 1 R
120. 325 0 h below which water uptake red starts at high Tpot 10000 100 cm R HLIM3L 600 0 h below which water uptake red starts at low Tpot 10000 100 cm R Alterra Report 1649 update02 165 HLIM4 8000 0 No water extraction at lower pressure heads 16000 100 cm R ADCRH 0 5 Level of high atmospheric demand 0 5 cm d R ADCRL 0 1 Level of low atmospheric demand 0 5 cm d R If SWROOTTYP 2 specify WILTPOINT 15000 0 Minimum pressure head at interface soil root 1 0d6 1 0d2 cm ROOTRADIUS 0 05 Root radius 0 0001 1 cm R ROOTCOEFA 0 53 Defines relative distance at which mean soil water content occurs 0 1 0 R KKK KKK KKK KKK KKK KKK KK KKK KKK KKK KK KK KKK KKK KK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK AK KKK ck kckck ck kckck ck k ck kck KK KKK KKK KKK KKK KKK KKK KK KKK KKK KKK KKK KKK KKK KKK KKK KK KKK KKK KKK KKK KK KKK KKK KKK KKK KKK KKK KKK k ck k ck kck k ck k ck ck ck KK KKK Part 8 salt stress linear relation between ECsat and crop reduction ECMAX 2 0 ECsat level at which salt stress starts 0 20 dS m R ECSLOP 0 0 Decline of rootwater uptake above ECMAX 0 40 dS m R non linear relation between salinity concentration and EC C2ECa 1 492 Coefficient a to convert salt concentration to electrical conductivity 0 0 1000 0 R C2ECb 1 0 Coefficient b to convert salt concentration to electrical conductivity 0 0 10 0 R
121. 35 T b age du with fag ZO 7 27 with Th ago the lower threshold temperature for physiologic ageing C which is crop specific and should be provided by the user The integral of the physiologic ageing factor over time yields the physiologic age P age d Pl P f At 7 28 age age age In order to correct for leaf senescence the specific leaf area of each day Sia ha kg the growth of the dry matter weight of leaves per day Wear and the physiological age Page are stored in 3 corresponding arrays The first element of the arrays represents the most recent day and the last element of the arrays represents the oldest day The weight of the leaves that have died during a day due to water stress or mutual shading is subtracted from the weight of the oldest leaf class When senescence is larger than the amount available in the oldest leaf class the remaining senescence is subtracted from the next oldest leaf class Emptying of the leaf classes continues Alterra Report 1649 update02 161 until the amount of senescence is dissipated completely or the remaining amount of leaves becomes zero Leaves may maximally attain the age defined by the crop specific life span WOFOST checks the leaf classes ages The first class younger than the defined life span becomes the oldest class 7 3 9 Net growth The initial amount of total dry crop weight should be provided by the user This amount is multiplied by the partitioning fa
122. 4 maximum MABBC records 01 jan 1980 1 0 30 jun 1980 0 15 23 dec 1980 1 2 End of table KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KK KKK KKK KAKA KKK KKK KKK ck ck k ck ck ck k ck ck KKK KKK ckckckckckckck KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KK KKK KKK KKK KKK KKK KKK ck k ck k ck k KKK KKK ck k ck KKK KKK AK SWBOTB 4 Calculate bottom flux as function of groundwater level Specify whether an exponential relation or a table is used to calculate the bottom flux from the groundwater level SWQHBOT 2 1 exponential relation 2 table In case of an exponential relation SWOHBOT 1 specify coefficients of relation qbot A exp B abs groundwater level COFQHA 0 1 Coefficient A 100 100 cm d R COFOHB 0 5 Coefficient B 1 1 cm R In case of a table SWOHBOT 2 specify groundwaterlevel Htab 10000 1000 cm R and bottom flux QTAB 100 100 cm d R Htab is negative below the soil surface Qtab is negative when flux is downward HTAB OTAB 0 1 0 35 105 0 60 05 125 0 0 01 KKK KKK KK KKK KK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK ck ckck ck kckck ck k ck k ck k ck k ckck ck ck ckck ck ck KKK KK KK KKK KKK KKK KKK KKK KK KKK KKK KKK KKK KK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK SWBOTB 5 Prescribe soil water pressure head of bottom compartment Specify DATE dd mmm yyyy and bottom compartment pressure
123. 7 14 154 Alterra Report 1649 update02 Similar expressions can be derived for the separate light components the diffuse flux the total direct radiation flux and the direct component of the direct radiation flux The absorbed diffuse component of the direct flux is obtained by subtracting the direct component from the total direct flux 7 3 4 Instantaneous assimilation rates per leaf layer The CO assimilation rate of a canopy layer is obtained by substituting the absorbed amount of light energy into the assimilation light response of single leaves Peat 1970 pan PAR a A Aus t 7 15 where Ar is the gross assimilation rate kg CO m leaf d Amax the gross assimilation rate at light saturation kg CO m leaf d 5 and pag the initial slope or light use efficiency kg CO J absorbed Two leaf classes are distinguished shaded leaves and sunlit leaves The shaded leaf area absorbs the diffuse flux and the diffuse component of the direct flux The sunlit leaf area receives diffuse and direct radiation At every horizon within the canopy the intensity of the unobstructed direct beam equals its intensity above the crop Illumination intensity of sunlit leaves varies strongly with leaf angle In the model the assimilation rate of the sunlit leaf area is therefore integrated over the leaf angle distribution The assimilation rate per unit leaf area in a canopy is the sum of the assimilation rates of sunlit and shad
124. 7 5 3 7 3 8 2 1 1 6 1 3 0 3 39 9 40 7 58 1 24 1 45 4 45 9 51 6 39 1 59 3 52 0 62 9 524 55 8 59 6 34 8 42 9 32 1 16 2 36 8 45 6 353 15 9 20 2 58 1 55 8 59 6 51 7 30 8 46 4 41 9 16 2 20 9 25 9 24 7 14 3 27 8 27 4 29 2 24 1 31 7 24 2 17 0 25 3 24 1 26 4 17 9 22 1 20 4 10 1 22 2 27 2 43 9 23 9 27 2 30 7 35 5 29 5 37 0 15 7 20 5 18 3 6 7 33 4 28 3 16 2 53 5 16 6 18 9 15 4 32 8 6 9 20 4 17 7 18 3 16 7 12 2 27 9 26 5 33 2 37 8 27 5 22 9 19 7 58 2 51 2 10 2 8 1 10 1 9 6 30 2 21 2 23 3 21 0 5 8 dl 1 1 8 1 10 2 6 8 3 8 4 0 2 1 3 4 2 4 4 0 3 4 1 8 19 5 8 5 142 36 0 13 5 4 3 11 2 0 1 4 1 0 0 6 0 8 1 7 23 3 11 9 15 5 56 1 0 45 0 37 0 43 0 56 0 52 0 46 0 48 0 50 0 50 0 49 0 50 0 55 0 58 0 57 0 52 0 53 0 82 0 79 0 48 0 56 0 68 1 10 1 10 0 30 0 34 0 37 0 40 0 43 0 45 0 40 0 40 251 1 0 0 6 0 7 0 7 0 8 0 9 0 9 0 9 0 9 0 7 0 8 0 8 1 0 1 0 1 0 0 9 12 1 0 0 8 0 8 1 2 2 0 2 1 0 9 0 9 0 5 0 8 1 0 0 8 1 3 13 0 0 0 0 0 0 0 0 0 2 0 0 0 1 0 1 0 05 0 2 0 2 0 1 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 05 0 0 0 0 0 0 0 0 252 Alterra Report 1649 update02 Appendix 11 Examples of shrinkage characteristics of peat Shrinkage characteristics of peat and peaty soils after Hendriks 2004 Black dots are measurements and lines are fits with E
125. 9 update02 49 SWBOTB 6 combined with a single drainage system where the drainage resistance is low Box 2 2 Bottom boundary section in main input file swp Ck kk kk KKK KKK KKK KKK KK KKK KKK KKK KK KKK KKK KKK KKK KKK KKK KKK KKK KK KKK KKK KAKA ck ck ck k ck ck ck k ckck ckok ckokck If SWBBCFILE 0 select one of the following options 1 Prescribe groundwater level 2 Prescribe bottom flux 3 Calculate bottom flux from hydraulic head of deep aquifer 4 Calculate bottom flux as function of groundwater level 5 Prescribe soil water pressure head of bottom compartment 6 Bottom flux equals zero 7 Free drainage of soil profile 8 Free outflow at soil air interface SWBOTB 6 Switch for bottom boundary 1 8 1 Options 6 7 and 8 require no additional bottom input data ES ck kk kc KKK KKK KKK KK KKK KKK KK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK ck ckck ck k ckck ck k ck ck ck kckck ck k ckok ckckckokok SWBOTB 1 Prescribe groundwater level specify DATE dd mmm yyyy and groundwater level cm 10000 1000 R DATE1 GWLEVEL max MABBC records 01 jan 1981 95 0 31 dec 1983 95 0 End of table ck KK KR KK KK ck ck KK KK RK KKK KKK KKK KKK KKK KK KKK KKK KK KKK kck ck KK KKK KKK KKK kckck ck ck ckck ck KKK ck k ckck ck k ck ck REK RK KK RK RK KK KK RK KK KKK KKK KKK KK KKK KKK KK KKK KKK KK KK KKK KKK KKK KKK KKK KKK ck k ck k ck k ck k ck k ck k KAKA KKK SWBOTB 2 Prescribe bottom f
126. Black or Boesten Stroosnijder method SWREDU 1 or 2 Default soil evaporation coefficient for Black equals 0 35 cm d and for Boesten Stroosnijder 0 54 cm Box 3 5 Soil data to derive actual soil evaporation in main file SWP KK KK KKK KK KKK KK KKK KK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK ck ck k ck ck ckck ck k ck k ck ck ck k ck k ck k KKK KK Part 3 Soil evaporation SWCFBS 0 Switch for use of a soil factor to derive soil evaporation Y 1 N 0 0 CFBS is not used 1 CFBS used to calculate potential evaporation from reference ET If SWCFBS 1 specify soil factor CFBS CFBS 1 0 Soil factor for potential soil evaporation 0 5 1 5 R SWREDU 1 Switch method for reduction of potential soil evaporation 0 reduction to maximum Darcy flux 1 reduction to maximum Darcy flux and to maximum Black 1969 2 reduction to maximum Darcy flux and to maximum Bo Str 1986 COFRED 0 35 Soil evaporation coefficient of Black 0 1 cm d1 2 R or Boesten Stroosnijder 0 1 cm1 2 R RSIGNI 0 5 Minimum rainfall to reset method of Black 0 1 cm d R KKK KKK KKK KKK KKK KKK KK KK KKK KKK KKK KKK KKK KKK KKK KK KKK KKK KKK KKK KKK k ck k ck k ck k ck k ck ck ck k ck k ck k ck KKK K 68 Alterra Report 1649 update02 4 Surface runoff interflow and drainage The interaction between soil water and surface water is of importance in lowland areas Dependent on the spe
127. D do oes Po enn 6 36 4 rad TK o U con where Qe cm is the groundwater elevation Zseep cm is bottom of seepage layer which equals depth of either bottom of macropores or macropore water level Dseep cm is thickness of seepage zone and Useep cm is thickness of seepage face which is set to 10 of Dseep Eq 6 36 b Eq 6 36 d are derived from Eq 4 20 Eq 4 22 Distribution of qi over MB and IC domains is according to their proportions Pmb and P at the specific depth z Lateral exfiltration out of the saturated matrix as interflow qli Lateral exfiltration di cm cm d out of the saturated soil matrix into macropores by interflow Section 4 2 out of a zone with perched groundwater occurs over the depth of perched groundwater This process is a special case of exfiltration of soil water from the saturated zone into the macropores and is described in a similar way using Eq 6 35 and Eq 6 36 but with an opposite sign due to its definition in Eq 6 24 If Amp gt Ami infiltration into the saturated matrix in the perched groundwater zone occurs according to Eq 6 35 A perched groundwater zone is here defined as a saturated zone above groundwater level that is separated from the saturated zone below groundwater level by an unsaturated zone which contains at least a critical value Vundsat cri default 0 1 cm of under saturated volume Vundsar 0 0 dz cm Distribution of qi over the MB and IC domains is accor
128. Drainage The input requirements for the simulation of a field scale drainage relation according to Hooghoudt and Ernst is given in Box 4 3 Alterra Report 1649 update02 91 Box 4 3 Field scale drainage relation according to Hooghoudt and Ernst in drainage file DRA KOK OK ROK RK RK RK RK RK ROK RK ck ck ck ckck ck ck ck ck ck ck ck ck ck ck RK RK RK RK RK RK RR RK RK RR RR RR OR OR OR ckckckckck ck kckck ck ck ck RK OK Part 0 General DRAMET 2 Switch method of lateral drainage calculation METHOD 1 Use table of drainage flux groundwater level relation METHOD 2 Use drainage formula of Hooghoudt or Ernst METHOD 3 Use drainage infiltration resistance multi level if needed KOK KK KK KK KK KK KK KK KK KK KK KK KK KK KKK KKK KK KKK KKK KKK KK KKK KKK KKK ck k ck KKK KKK k ck kck k RARA ck kckokckok METHOD 2 Part 2 Drainage formula of Hooghoudt or Ernst DRAMET 2 Drain characteristics LM2 11 Drain spacing 1 1000 m R SHAPE 0 8 Shape factor to account for actual location between drain and water divide 0 0 1 0 R WETPER 30 0 Wet perimeter of the drain 0 1000 cm R ZBOTDR 80 0 Level of drain bottom 1000 0 cm R neg below soil surface ENTRES 20 0 Drain entry resistance 0 1000 d R Soil profile characteristics IPOS 2 Switch for position of drain On top of an impervious layer in a homogeneous profile Above an impervious layer in a homogeneous profile At the interf
129. FORTRAN utility library TTUTIL v 4 Report 5 Plant Research International Wageningen Krammes J S and L F DeBano 1965 Soil wettability a neglected factor in watershed management Water Resour Res 1 283 288 Kraijenhoff van de Leur D A 1958 A study of non steady groundnwater flow with special references to a reservoir coefficient Ingenieur 70 B87 B94 Kroes J G and J Roelsma 1997 User s Guide ANIMO 3 5 input instructions and technical programme description Technical Document 46 DLO Winand Staring Centre Wageningen Kroes J G P J T van Bakel J Huygen T Kroon en R Pastoors 2001 Actualisatie van de hydrologie voor STONE 2 0 Rapport 298 Alterra Wageningen 68 p Kropff M J H H van Laar and H F M ten Berge Eds 1993 ORYZAI A basic model for irrigated lowland rice production IRRI Los Banos The Philippines Kujala K 1991 Factors affecting frost susceptibility and heaving pressure in soils Acta Univ Oul C 58 Department of Civil Engineering University of Oulu Finland 104 pag Kustas W A Rango 1994 A simple energy algorithm for the snowmelt runoff model Water Resources Research 30 1515 1527 Leij F J W J Alves M Th van Genuchten and J R Williams 1996 The UNSODA Unsaturated Soil Hydraulic Database User s manual Version 1 0 Soil Salinity Laboratory Riverside California Leistra M A M A van der Linden J J T I Boesten A Tiktak and F van den Berg 2001 PEARL model
130. IMO for nutrients SWAP simulates soil heat flow taking into account actual heat capacities and thermal conductivities The generic crop growth module WOFOST is incorporated to simulate leaf photosynthesis and crop growth The soil moisture heat and solute modules exchange status information each time step to account for all kind of interactions Crop growth is affected by the actual soil moisture and salinity status on a daily basis An extensive test protocol ensures the numerical code quality of SWAP In the vertical direction the model domain reaches from a plane just above the canopy to a plane in the shallow groundwater Fig 1 1 Rain Irrigation Transpiration Transport of soil water solutes fe gm soil heat Interception Evaporation Top soil Second aquifer Figure 1 1 SWAP model domain and transport processes In this zone the transport processes are predominantly vertical therefore SWAP is a one dimensional vertical directed model The flow below the groundwater level may include Alterra Report 1649 update02 15 lateral drainage fluxes provided that these fluxes can be prescribed with analytical drainage formulas The model is very flexible with regard to input data at the top and bottom of the soil column At the top in general daily weather conditions will suffice For Nordic conditions a simple snow storage module has been implemented In case of more focussed studies e g runoff or diurnal transpiration
131. If SWRAIN 3 then specify file name of file with detailed rainfall data RAINFIL WagRain File name of detailed rainfall data without extension YYY A16 Extension equals last 3 digits of year number e g 2003 has extension 003 An alternative to run SWAP is by directly executing Swap exe In that case the main input file should be named Swap swp and should be located in the same folder as Swap exe Three types of messages may occur e error messages generated by the utility library TTUTIL Kraalingen amp Rappoldt 2000 with respect to the format of the input data e warnings with the advise to adapt the combination of selected options because the specified combination is not feasible e fatal errors which stop the simulation Output files will be generated in the same directory as the main input file Also the log file of the most recent simulation run can be found here The Swap log file contains a copy of the swp file possible errors and warnings and in case of a successful simulation run Swap simulation okay 20 Alterra Report 1649 update02 1 5 Model output Output from SWAP is stored in general ASCII files Some of these files are always generated other files are optional output Box 1 4 provides an overview of the variables that are printed in each output file All output files have the same header with the project name file content file name model version date of generation period of calculations
132. In Water flow and solute transport in soils modelling and application D Russo and G Dagan Eds Springer Verlag Berlin p 211 231 Feddes R A M Menenti P Kabat and W G M Bastiaanssen 1993b Is large scale inverse modelling of unsaturated flow with areal average evaporation and surface soil moisture as estimated from remote sensing feasible J Hydrol 143 125 152 212 Alterra Report 1649 update02 Feddes R A and K J Lenselink 1994 Evapotranspiration In Drainage priciples and applications H P Ritzema ed ILRI publication 16 second ed Wageningen p 145 174 Fern ndez A 1998 An Energy Balance Model of Seasonal Snow Evolution Physical Chemistry of the Earth 23 5 6 661 666 Flury M and H Fl hler 1995 Tracer characteristics of Brilliant Blue FCF Soil Sci Soc Am J 59 22 27 Garnier P Rieu M Boivin P Vauclin M and Baveye P 1997 Determining the hydraulic properties of a swelling soil from a transient evaporation experiment Soil Sci Soc Am J 61 1555 1563 Gash J H C 1979 An analytical model of rainfall interception by forests Q J R Meteor Soc 105 43 55 Gash J H C C R Lloyd and G Lachaud 1995 Estimating sparse forest rainfall interception with an analytical model Journal of Hydrology 170 1995 79 86 Gelhar L W and J L Wilson 1974 Groundwater quality modeling Ground Water 12 399 408 Gerke H H and M Th van Genuchten 1993 A dual porosity mo
133. K KK KK KK KK KK KKK KK KKK KKK KKK KK KKK KKK kck KKK KKK KKK KKK k ck k ck k ck k ck k ck k ck kck k ck kck k ck kckok KKK KK KK KKK KK KK KK KK KK KK KK KK KK KK KK KK KK KK KKK KKK KKK KKK KK kckckckckck kck kck k KKK KK KKK KKK k ck k ck k ck k ck k ck k ck k ck kckok Part 7 Maintenance respiration Q10 2 0000 Rel increase in respiration rate with temperature 0 5 10 C R RML 0 0300 Rel maintenance respiration rate of leaves 0 1 kgCH20 kg d R RMO 0 0045 Rel maintenance respiration rate of st org 0 1 kgCH20 kg d R RMR 0 0100 Rel maintenance respiration rate of roots 0 1 kgCH20 kg d R RMS 0 0150 Rel maintenance respiration rate of stems 0 1 kgCH20 kg d R List reduction factor of senescence R as function of dev stage 0 2 R B DVS RFSE maximum 15 records RFSETB 0 00 1 00 2 00 1 00 End of table KKK KK KKK KKK KKK KK KK KK KK KK KK KK KK KK KK KK KK KK KK KK KKK KKK KK kck k ck kckck ck k ck ck ck k ck k ck k ck k ck k ck k ck k ck kck k ck kck kckok Alterra Report 1649 update02 169 KKK KK KKK KKK KK KK KK A KA KKK KKK KK KK KKK KKK KKK KKK KKK KK KK KKK KKK KK KKK KKK ck kckck ck ck KKK k ck ck ckck ck k ck k ck k ck k ck k ck k ck kckckckok Part 8 Partitioning List fraction of total dry matter increase partitioned to the roots kg kg R as function of development stage 0 2 R DVS FR maximum 15 records FRTB 0 00 0 20 14 00 0 20
134. KK KK KK KK KK KKK KKK KKK KKK KKK KK KKK KKK KKK KKK KK KKK ckck ck ck ckck ck ck ck k ck k ck k ck k ck k ck k ck k ck k ck k ck kckckckok 170 Alterra Report 1649 update02 KOR KK KK RK KK KK KK RK KK KR KK KKK KKK KKK AAA KKK KKK KKK KK KKK KKK KKK KKK RARA RARA RARA RARA ck kckck RA RARA RARA Part 10 soil water extraction by plant roots Switch for concept root water extraction swroottyp 1 1 Macroscopic concept Feddes et al 1978 2 Microscopic concept De Jong van Lier et al 2008 if swroottyp 1 specify HLIM1 10 0 No water extraction at higher pressure heads 100 100 cm R HLIM2U 25 0 h below which optimum water extr starts for top layer 1000 100 cm R HLIM2L 25 0 h below which optimum water extr starts for sub layer 1000 100 cm R HLIM3H 300 0 h below which water uptake red starts at high Tpot 10000 100 cm R HLIM3L 500 0 h below which water uptake red starts at low Tpot 10000 100 cm R HLIM4 10000 0 No water extraction at lower pressure heads 16000 100 cm R ADCRH 0 5 Level of high atmospheric demand 0 5 cm d R ADCRL 0 1 Level of low atmospheric demand 0 5 cm d R If SWROOTTYP 2 specify WILTPOINT 15000 0 Minimum pressure head at interface soil root 1 0d6 1 0d2 cm ROOTRADIUS 0 05 Root radius L0 0001 1 cm RI ROOTCOEFA 0 53 Defines relative distance at which mean soil water content occurs
135. KOK ROK ROK ROK RK ROK RK KOK RK RK ck ckck ck ck ck ck ck ck KK KK KK KK KK KK KK KK KK KK RK RR KR KK RR OK OK OK OK OK ck ckck ck OK OK Part 3b Drainage to level 2 DRARES2 100 INFRES2 100 SWALLO2 1 Drainage resistance 10 1E5 d R Infiltration resistance 0 1E5 d R Switch for allowance drainage infiltration 1 Drainage and infiltration are both allowed 2 Drainage is not allowed 3 Infiltration is not allowed Level of drainage medium bottom 1000 0 cm R Type of drainage medium 1 drain tube 2 open channel ZBOTDR2 SWDTYP2 If SWDIVD 1 drainage flux vertically distributed specify the drain spacing L2 20 Drain spacing 1 1000 m R In case of open channel SWDTYP2 2 specify date DATOWL2 dd mmm yyyy and channel water level LEVEL2 cm negative if below soil surface maximum MAOWL records DATOWL2 LEVEL2 12 jan 1981 90 0 14 dec 1981 90 0 End of table KOK ROK ROK RK RK RK ROK RK ROK RK ck ck ck ck ck ck ck ck ok KK RK KK RK KR RK KK KK RK KK RK RR KK RK OK OK ckckckckck ck ck ck ck ckck ck OK OK If the Number of drainage levels NRLEVS is larger than 2 then similar input is required for levels 3 5 94 Alterra Report 1649 update02 Box 4 6 Multi level drainage with surface water dependent resistances and simulated drainage levels in drainage file DRA EXTENDED DRAINAGE SECTION KOK ROK ROK RK RK RK RK RK RK RK RK RK
136. M Th van Genuchten P J Shouse and J A Poss 2006 Macroscopic approaches to root water uptake as a function of water and salinity stress Agric Water Man 86 140 149 Smith M 1992 CROPWAT a computer program for irrigation planning and management FAO Irrigation and Drainage Paper 46 Rome Italy Spitters C J T H van Keulen and D W G van Kraalingen 1989 A simple and universal crop growth simulator SUCROSS7 In R Rabbinge S A Ward and H H van Laar Eds Simulation and systems management in crop protection Simulation Monographs Pudoc Wageningen The Netherlands p 147 181 Stolte J J I Freijer W Bouten C Dirksen J M Halbertsma J C van Dam J A van den Berg G J Veerman and J H M W sten 1994 Comparison of six methods to determine unsaturated soil hydraulic conductivity Soil Sci Soc Am J 58 1596 1603 Stroosnijder L 1975 Infiltration and redistribution of water in the soil PhD thesis Wageningen University 213 p in Dutch Supit I A A Hooyer and C A van Diepen Eds 1994 System description of the WOFOST 6 0 crop simulation model implemented in CGMS Vol 1 Theory and algorithms EUR publication 15956 Agricultural series Luxembourg 146 p Taylor S A and G M Ashcroft 1972 Physical Edaphology Freeman and Co San Francisco California p 434 435 Ten Berge H F M 1986 Heat and water transfer at the bare soil surface aspects affecting thermal images PhD thesis Wageninge
137. O2 assimilation rate of the crop calculate lateral drainage rate and state variables calculate lateral drainage rate and state variables including surface water system calculate lower boundary conditions calculate top boundary conditions search for groundwater levels converts vertical discretization prescribed crop growth lateral drainage calculate soil thermal properties divide drainage flux to compartments calculate bottom and compartment fluxes detailed grass growth routine calculate hydraulic conductivity from water content calculate pressure heads at next time check hysteretic reversal and update scanning curve integrate intermediate and cumulative water fluxes initialize and calculate irrigation calculate crack shrinkage and swelling including fluxes read meteorological data and return values of actual day calculate moisture capacity from pressure head specify crop characteristics for bare soil formatted hydrological output for ANIMO PESTLA AFO unformatted hydrological output for ANIMO PESTLA AUN write overview balances BAL write total water balances BLC write drainage fluxes runoff etc DRF write final soil state variables for next initial condition write water balance increments INC write solute balance SBA write surface water balance SWB write soil temperatures TEM write water and solute profile data V AP write water balance WBA calculate potential evaporation a
138. P MADM MASTEQ NMETFILE Description number of years in the simulation period number of days in the simulation period number of crops number of compartments number of drainage systems number of horizons number of time dependent values for bottom boundary number of scaling factors number of rainfall records in case of detailed rainfall number of applied irrigations number of specified output dates number of open water levels basic drainage routine number of open water levels in primary system number of open water levels in secondary system number of surface water management periods number of macropore domains number of static equilibrium relations number of weather records in one year 48 per day Alterra Report 1649 update02 Array length 70 MAYRS 366 200 500 200 10 366 100 40000 10000 3000 10 366 10 366 10 366 10 366 20 10000 17568 255 256 Alterra Report 1649 update02 Appendix 13 Assim Bocodrb Bocodre Boundbottom Boundtop CalcGwl CalcGrid CropFixed Drainage DeVries DivDra Fluxes Grass HConduc HeadCalc Hysteresis Integral Irrigation MacroPore MeteoInput MoisCap NoCrop OutAfo OutAun OutBal OutBlc OutDrf OutEnd OutInc OutSba OutS wb OutTem OutVap OutWba Penmon Ponding PrHead Radiat ReadSwap ReducEva RootExtraction Snow SoilWater Solute Surface Water Temperature TimeControl Totass Warn WatCon WatStor List of main SWAP subroutines gross C
139. REXIT WIDTHR TALUDR 1 0 250 0 1093 0 350 0 150 0 4000 0 0 8 0 8 100 0 0 66 2 0 200 0 1150 0 300 0 150 0 1500 0 0 8 0 8 100 0 0 66 End of table Part 1b Separate criteria for highest shallow drainage system SWNRSRF 0 Switch to introduce rapid subsurface drainage 0 2 I no rapid drainage rapid drainage in the highest drainage system NRSRF implies adjustment of RDRAIN of highest drainage system rapid drainage as interflow according to a power relation implies adjustment of RDRAIN of highest drainage system When SWRNSRF 1 then enter realistic values for rapid drainage RSURFDEEP 30 0 maximum resistance of rapid subsurface Drainage 0 001 1000 0 d R RSURFSHALLOW 10 0 minimum resistance of Rapid subsurface Drainage 0 001 1000 0 d R When SWRNSRF 2 then enter coefficients of power function COFINTFL 0 1 coefficient of interflow relation 0 01 10 0 d 1 R EXPINTFL 0 5 exponent of interflow relation 0 1 1 0 R Switch to adjust the bottom of the model discharge layer in case of lateral swdivdra 1 interflow or rapid drainage Swnrsrf 1 or Swnrsrf 2 When the switch is on SwTopnrsrf 1 then the bottom of the highest order drainage system Zbotdr NumDrain represents the max depth of the interflow SwTopnrsrf 0 Switch to enable adjustment of model discharge layer 0 1 I Alterra Report 1649 update02 95 The input requirements to influence the distribution of drainage fluxes wi
140. RK ck ck ck KA KA KK KK KK RK KK RK KK KR KK RK KK RR KR OR OK RK OR ckckck ck ck ck RK RK Part 0 Reference level ALTCU 0 0 ALTitude of the Control Unit relative to reference level AltCu 0 0 means reference level coincides with surface level 300000 300000 cm R KOK ROK RK RK RK RK RK RK RK RK RK RK RK RK RK ck KA KK KK KK RR KK KR KK RK KK RK KK OR RK OK ck ckck ck OK OR OK Part la drainage characteristics RSRF 2 number of subsurface drainage levels 1 5 I Table with physical characteristics of each subsurface drainage level LEVEL drainage level number 1 NRSRF I SWDTYP type of drainage medium open 0 closed 1 L spacing between channels drains 1 1000 m R ZBOTDRE altitude of bottom of channel or drain ALTCU 1000 ALTCU 0 01 cm R GWLINF groundw level for max infiltr 1000 0 cm rel to soil surf R RDRAIN drainage resistance 1 100000 d R RINFI infiltration resistance 1 100000 d R Variables RENTRY REXIT WIDTHR and TALUDR must have realistic values when the type of drainage medium is open second column of this table SWDTYP 0 For closed pipe drains SWDTYP 1 dummy values may be entered RENTRY entry resistance 1 100 d R REXIT exit resistance 1 100 d RI WIDTHR bottom width of channel 0 100 cm R TALUDR side slope dh dw of channel 0 01 5 R El EV SWDTYP L ZBOTDRE GWLINF RDRAIN RINFI RENTRY
141. SWAP version 3 2 Theory description and user manual Update 02 August 2009 Updated items are marked with a red color in the text An overview of the updates since the first release of the manual in 2008 is given in the list below Updated item User Refers to Page Input Variable number Measured saturated hydraulic conductivity additional to optional Kat 45 fitted value in Van Genuchten relation Soil physical relation in tabulated form functions optional 0 K 45 Convergency criteria optional h 0 45 Switch to suppress the contribution of vertical resistance in mandatory bot 50 the phreatic aquifer to the total vertical resistance at the bottom boundary Derive Soil cover from a given LAI no Ej 54 Input of crop resistance for a wet canopy completely mandatory ET 58 covering the soil RSW Uniformity of fluxes to split ET over T and E no Tp Ep 60 Preferential root water uptake optional T 62 163 Time dependent threshold value for ponding optional Qpond 90 Adjust the lower boundary of the model discharge layer optional Qdrain 95 lateral drainage Introduction of an option to relate the position of the upper optional arain 96 boundary of the model discharge layer to the groundwater level lateral drainage Macropore flow 1 introduction of user defined resistance optional Gis 145 of rapid drainage system 2 specification of one of the drainage
142. SWRUNON 0 0 No input of runon data 1 Runon data are provided in extra input file If SWRUNON 1 specify name of file with runon input data This file may be an output inc file with only 1 header of a previous Swap simulation RUFIL runon inc File name with extension A80 ES 90 Alterra Report 1649 update02 4 5 2 Interflow For describing the interflow process a non linear relation can be used Such relation may useful for taking account for the horizontal flow in the saturated zone above drainage level may yield a non linear relation contrary to relation based on the assumption made in the derivation of the horizontal resistance in the Ernst equation Another reason to introduce a non linear relation for interflow may be the occurrence of hillslope Sometimes it is possible to relate the parameters Aj 4 and B to interflow a specific flow concept but most of the model user has to rely on expert judgement of model calibration Box 4 2 Information on interflow in drainage file DRA Option for interflow in highest drainage level shallow system with short residence time SWINTFL 0 Switch for interflow 0 1 I If SWINTFL 1 specify COFINTFLB 0 5 Coefficient for interflow relation 0 01 LOG 0 dy RY EXPINTFLB 1 0 Exponent for interflow relation Ou 10r RJ KKK KKK KKK KKK KK KK KOK KK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK ck k KKK KKK ck k ck k ck k ck k ck KKK KK KK 4 5 3
143. Surface runoff amounts of water stored in the canopy itself Therefore we will Rootwater _____ Z extraction A assume that root water Figure 3 1 Water fluxes near the soil surface extraction in the soil is equal to plant transpi ration While root water extraction may occur throughout the root zone soil evaporation occurs at the interface soil atmosphere The consequence is that during drying conditions evaporation fluxes decline much more rapidly than transpiration fluxes Water harvesting by leaving fields fallow during one or several seasons uses this phenomenon Because of the different physical behaviour of transpiration and evaporation SWAP will consider evaporation and transpiration separately In this chapter we will first discuss the rainfall interception as used for low vegetation and forests Next we discuss the simulation of potential evapotranspiration and its distribution into potential transpiration and evaporation for partly covered soils Then we will discuss the reduction of transpiration for wet dry and saline soil conditions and the reduction of evaporation for dry top soils In the last part the related model input is described Alterra Report 1649 update02 53 3 2 Rainfall interception Two methods are available in SWAP to simulate rainfall interception one for agricultural crops and one for trees and forests 3 2 1 Agricultural crops For agricultural crops and for grassland SWAP computes the interce
144. Switch for solute conversion factors for entire profile or per soil layer SWC2ECF 1 1 conversion factors for entire profile 2 conversion factors per soil layer If SWC2ECF 1 specify for entire soil profile cance 1 0 Factor f to account for over saturation of saturated paste 0 0 10 0 R If SWC2ECF 2 specify for each soil layer Q2ECGT 1 0 1 0 Factor f to account for over saturation of saturated paste 0 0 10 0 R FOI Kok kk Kk Koo I Kok ko Kok Kok Kk Kk e KK eK ko ok KK III kk ko kk oko koe Kok II III koe A e III II II II I Ik ee KKK KKK KKK KKK KKK KKK KK KK ck ck ck KKK KKK KKK ck ck ckck ckck ck ck KKK KKK ckckckck ck ckckckckckckckck ck ck ckck ck KKK KK KAKA KKK KK KKK KKK KKK KK KKK Part 9 interception SWINTER 1 witch for rainfall interception method 18 0 No interception calculated 1 2 Agricultural crops Von Hoyningen Hune and Braden Closed forest canopies Gash In case of interception method for agricultural crops SWINTER 1 specify COFAB 0 25 Interception coefficient Von Hoyningen Hune and Braden 0 1 mm R In case of interception method for closed forest canopies SWINTER 2 specify as function of time of the year T 0 366 d R maximum 36 records PFREE free throughfall coefficient 0 d0 1 d0 R PSTEM stem flow coefficient 0 d0 1 d0 R SCANOPY storage capacity of canopy 0 d0 10 d0 cm R AVPREC average rainfall intensity
145. This quotient is similar for using dix and dpoi 4 An 4 d mtx 2 a Actas E s Ayo ae dia 4 Aai 42 1 1 X 1 1 1 X l E ES EE Eum d mtx d mtx dis pol 2 2 2 Only in Eq 6 29 the calculation of the absorption A ya is used without dividing by xpo1 In that case A wal mtx is used for A wan Therefore A ya is corrected with Eq A2 9 according to das d ol J1 7 V Habs d Avan E Aa 417 V np Avan 42 12 pol pol 234 Alterra Report 1649 update02 Appendix 3 Examples of description of macropore geometry Static macropore volume cm3 cm 3 0 0 02 0 04 0 06 0 08 0 1 Depth cm t Zah 20 cm Zic 80 cm Zot 120 cm Vst 0 0 1 cm cm Pic 0 7 m 1 0 na 10 Static macropore volume cm3 cm 3 o 0 02 0 04 0 06 0 08 0 1 10 EEEE AHH 30 Dn a dl A E 1 J 40 A A PH HH E A EE E sr A Y D 90 A 110 F 120 4 m 0 25 Rza 0 2 Static macropore volume cm3 cm 3 0 02 0 04 0 06 0 08 o 1 Depth cm m 4 0 5 0 5 Alterra Report 1649 update02 Depth cm Depth cm VLMPSTSS ll lt st 0 PPICSS Pic NUMSBDM na POWM m RZAH Rzan SPOINT 8 SWPOWM SWpowm Static macropore volume cm3 cm 3 0 0 02 0 04 0 06 0 08 0 1 N c Static macropore volume cm3 cm 3 0 0 02 0 04 0 06 008 01 m 2 0 25
146. Yentr Yraa 8KD darain 2 4 6 y Y ag Darin entr rad 8KD and for regional applications Piai Pavg 7 O drain Pavg O drain Qdrain Yentr Y rad 12KD gt drain 7 2 4 7 drain Yentr Y rad 12KD By comparing Eq 4 5 with Eq 4 6 it can be seen that the two definitions of Yarain in the equations differ by the so called shape factor The shape factor a is the ratio between the mean and the maximum groundwater level elevation above the drainage base Pm Pavg O drain 4 8 9 gwl C drain The shape factor depends on the vertical horizontal radial and entrance resistances of the drainage system Ernst 1978 For regional situations where the horizontal resistance to flow plays an important role the shape factor is relatively small 0 7 The smaller the horizontal resistance becomes the more rectangular shaped the water table in the most extreme case with all the resistance concentrated in the direct vicinity of the channel the water table is level except for the abrupt decrease towards the drainage base In that case the shape factor approaches to unity It should be noted that the parameters chosen to describe the relation between discharge and groundwater elevation should be attuned to the hydrological schematization The combination of a Cauchy condition for the bottom boundary with a drainage relation for the lateral boundary may require an other formula De Lange 1999 than the one usually
147. a shape factor Power m 1 describes shallow IC systems while m 1 describes deep IC systems m 1 describes an intermediate system with a linear decline of functional IC macropores with depth Rzam is an optional parameter with which a linear increase of the R curve over the thickness of the A horizon can be described Its default value is zero Curve F in Figure 6 2 depicts the complement of R the cumulative frequency distribution of the depth at which IC macropores are not ended in the concept i e the fraction of IC macropores that is functional at that depth z Functional in the sense of downward transport and storage of water and lateral infiltration of macropore water into the soil matrix F 1 R 6 4 Alterra Report 1649 update02 115 The volumetric proportion of IC macropore volume as a function of depth can be written in terms of the constant Pi y and the function F P PNE GUI for 02z gt Z and O lt P lt l 6 5 a c 1 ic 0 cape ic 0 B 0 for z Zo and or for P 0 6 5 b 1c 1 The volumetric proportion of MB macropore volume as a function of depth is calculated from function Pi with Eq 6 2 This results in a proportion Py of 1 for depths below Zic where IC macropore volume is absent and all macropore volume is MB volume 6 1 1 2 Persistency With respect to persistency the macropore volume of each of the domains consists of 1 Static macropore volume expressed as volume fraction Vs cm
148. ace of a fine upper and a coarse lower soil layer In the lower more coarse soil layer In the upper more fine soil layer For all positions specify BASEGW 200 Level of impervious layer 1d4 0 cm R HTOP 25 Horizontal hydraulic conductivity top layer 0 1000 cm d R In addition in case IPOS 3 4 5 HBOT 10 0 horizontal hydraulic conductivity bottom layer 0 1000 cm d R ZINTF 150 Level of interface of fine and coarse soil layer 1d4 0 cm R In addition in case IPOS 4 5 VTOP 91 0 Vertical hydraulic conductivity top layer 0 1000 cm d R VBOT 10 0 Vertical hydraulic conductivity bottom layer 0 1000 cm d R In addition in case IPOS GEOFAC 4 8 Geometry factor of Ernst 0 100 R Ckokckckckckckckckckckckckckckckckckckck ck ck ck ck ckck ck ck ck ok ckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckck ck ck ck ck k ck ck ck ck ckck ck ck ckokok The input requirements for the simulation of a field scale drainage relation defined by a tabulated function is given in Box 4 4 Box 4 4 Field scale drainage relation defined by a tabulated function in drainage file DRA KOK OK ROK ROK RK RK ck ckckckckckck ck ck ckckckck ck ck ck ck ck ck KK KK KK KK KK KK RK KK KK RK KK KK KK RR KR OR ck ck kckckckck ck k ck k ck OK OK METHOD 1 Part 1 Table of drainage flux groundwater level relation DRAMET 1 If SWDIVD 1 specify the drain spacing LM1 30
149. acropore density is minimal dy as a function of depth is determined from a maximum dp ma and minimum dy min polygon diameter both input parameters and the relative macropore density M as a function of depth according to da d in SE CAM d si Ja xi M 6 23 a where M depends on the static macropore volume if present mala for V gt 0 6 23 b V st 0 st 0 If no static macropore volume is present M depends on the volumetric proportion of the IC domain P M A for Vico ic 0 0 and P ic 0 gt 0 6 23 c If no static macropore volume and no IC domain are present M can be defined as a function of depth with Zapmax as the depth below which dp equals dp max Z M max 0 1 for Vo 20 and P 0 6 23 d st 0 i dpmax 6 1 2 Water flow and balance In SWAP macropore water flow and balance comprise Fig 6 5 l storage of water in the macropore domains Smp cm 2 infiltration of water into macropores at soil surface by precipitation irrigation and snowmelt water falling directly into macropores J and by overland flow runoff into the macropores J cm d 3 lateral infiltration into the unsaturated soil matrix qi cm d lateral infiltration into and exfiltration out of the saturated soil matrix q s cm d Alterra Report 1649 update02 123 Main Bypass flow Internal Catchment Figure 6 5 Schematic representation of the soil profile with soil matrix drain groundwater perched g
150. actors are used The reference evapotranspiration rate can be determined in several ways such as pan evaporation the Penman open water evaporation Penman 1948 the FAO modified Penman equation Doorenbos and Pruitt 1977 the Penman Monteith equation applied for a reference crop Allen et al 1998 Priestly Taylor 1972 Makkink Makkink 1957 Feddes 1987 or Hargreaves et al 1985 In case of Priestly Taylor and Makkink only air temperature and solar radiation data are required Hargreaves requires solely air temperature data In SWAP the crop factors are used to convert the evapotranspiration rate of a reference crop fully covering the soil to the potential evapotranspiration rate of the actual crop fully covering the soil Fig 3 3 This is different from programs like CROPWAT Smith 1992 and CRIWAR Bos et al 1996 which use crop factors that depend on the crop development stage and soil cover Because the soil has generally a dry top layer soil evaporation is usually below the potential evaporation rate Hence these crop factors semi empirically combine the effect of an incomplete soil cover and reduced soil evaporation Instead SWAP uses the crop factor to relate uniform cropped surfaces Therefore crop factors in SWAP can be larger than those in CROPWAT and CRIWAR Alterra Report 1649 update02 59 3 4 Potential transpiration and evaporation fluxes of partly covered soils Until now we considered fluxes of uniform su
151. after 11 2 2 1 Back to Field Capacity specified amount The soil water content in the root zone is brought back to field capacity An additional irrigation amount can be defined to leach salts while the user may define a smaller irrigation amount when rainfall is expected This option may be useful in case of sprinkler and micro irrigation systems which allow variation of irrigation application depth 11 2 2 2 Fixed irrigation depth A specified amount of water is applied This option applies to most gravity systems which allow little variation in irrigation application depth 11 2 2 3 Limited depth With this option enabled the scheduled irrigation depth occurs only when the calculated irrigation depth lies between a minimum and maximum limit Lou sl g max 1 1 5 where min and Ig max are the threshold values for minimum and maximum irrigation depth mm respectively 204 Alterra Report 1649 update02 11 3 User instructions Fixed irrigation depths must be entered in the SWP file Box 11 1 Scheduled irrigation enters the model by means of timing and depth criteria in the CRP file see respectively Boxes 11 2 and 11 3 Box 11 1 Fixed irrigation in the input file SWP CROP Section part 2 KKK KKK KK KK KK KK KK KKK KK KK KK ck ck KKK KKK KKK KK KKK KKK KKK kck kck kck kck kck k ck k ck k ck k ck k ck k ck k ck k RARA Part 2 Fixed irrigation applications SWIRFIX 1 Switch for fixed irrigation
152. al 11 2 2 Depth criteria 11 2 2 1 Back to Field Capacity specified amount 11 2 2 2 Fixed irrigation depth 11 2 2 3 Limited depth 11 3 User instructions References Appendix 1 Application Penman Monteith method Appendix 2 Derivation of some macropore geometry equations Appendix 3 Examples of description of macropore geometry Appendix 4 Partial derivatives of F to pressure heads Appendix 6 Numerical solution heat flow equation Appendix 7 Parameters of soil hydraulic functions Staring series Appendix 8 Critical pressure head values for root water extraction Appendix 9 Salt tolerance data Appendix 10 Shrinkage characteristic data Appendix 11 Examples of shrinkage characteristics of peat Appendix 12 List of input array lengths Appendix 13 List of main SWAP subroutines Appendix 14 Description of output files afo and aun Appendix 15 Description of output files bfo and bun Appendix 16 Crop growth of grassland 202 202 203 203 203 203 203 204 204 204 205 209 225 231 235 237 241 245 247 249 251 233 255 257 239 261 265 8 Alterra Report 1649 update02 Preface SWAP Soil Water Atmosphere Plant is the successor of the agrohydrological model SWATR Feddes et al 1978 and some of its numerous derivatives Earlier versions were published as SWATR E by Feddes et al 1978 Belmans et al 1983 and Wesseling et al 1991 as SWACROP by Kabat et al 1992 and as SWAP93 by Van den Broek et al
153. al contributions is performed by multiplying S z S z by the proportion of the logarithmic value of each of the reduction factors ogla j yx log a i l Preferential root water uptake may be simulated using the concept described by De Jong van Lier et al 2008 Input requirements are given in paragraph 7 4 3 6 Actual soil evaporation At a wet soil soil evaporation equals its potential rate E This is also the case at ponded conditions during which SWAP will increase E to the evaporation rate of intercepted water When the soil becomes drier the soil hydraulic conductivity decreases which may reduce E to evaporation rate E cm d In SWAP the 62 Alterra Report 1649 update02 maximum evaporation rate that the top soil can sustain Emax cm d is calculated according to Darcy s law h ES EK Patos 2 70 max Ve Z1 where Ky is the average hydraulic conductivity cm d between the soil surface and the first node ham is the soil water pressure head cm in equilibrium with the air relative humidity h is the soil water pressure head cm of the first node and z is the soil depth cm at the first node Equation 2 70 excludes water flow due to thermal differences in the top soil and due to vapour flow as on daily basis the concerned flow amounts are probably negligible compared to isothermal liquid water flow Koorevaar et al 1983 Ten Berge 1986 Jury et al 1991 Note that the value of Emax in Eq
154. and 9 144 Alterra Report 1649 update02 Box 6 2 Macropore flow input water flow Case Andelst Scorza J nior et al 2004 KOR KK RK KK RK KK RK RK RK KK KK KKK KKK KKK KKK KKK KK KK KKK KKK KK KKK ck ck kck ck KKK KKK KKK KK KKK RARA RAR RAR Start of Tabel with sorptivity characteristics ISOILLAY4 Indicator number of soil layer as defined in part 4 1 MAHO I mon SWSorp Switch for kind of sorptivity function 1 2 I 1 calculated from hydraulic functions according to Parlange 2 empirical function from measurements SorpFacParl Factor for modifying Parlange function OPTIONAL default 1 0 0 100 R SorpMax Maximal sorptivity at theta residual 0 100 cm d 0 5 R SorpAlfa Fitting parameter for empirical sorptivity curve 10 10 R ISOILLAY4 SwSorp SorpFacParl SorpMax SorpAlfa 1 1 0 33 0 0 0 0 2 1 0 33 0 0 0 0 3 1 0 50 0 0 0 0 4 1 0 50 0 0 0 0 5 1 0 50 0 0 0 0 6 1 0 50 0 0 0 0 7 4 0 50 0 0 0 0 End of Tabel with sorptivity characteristics ShapeFacMp 1 0 Shape factor for lateral Darcy flow theoret 1 2 0 100 R CritUndSatVol 0 1 Critical value for under saturation volume 0 10 R SwDrRap 1 Switch for simulating rapid drainage Y 1 N 0 RapDraResRef 15 Reference rapid drainage resistance 0 1 E 10 d R RapDraReaExp 1 0 Exponent for reaction rapid drainage to dynamic crack width 0 100 R NumLevRapDra 1 Number of draina
155. area of the matrix polygon Am cm is a function of d according to Eq A2 2 A esc A2 5 4 232 Alterra Report 1649 update02 Amtx is also equal to the difference between basis polygon area Apo and crack area As 1 2 Aii Asa Ay Asa ai ai 1 E s Aver 1 n LAN Crd 42 6 Combining the right hands terms of Eq A2 5 and Eq A2 6 yields 1 2 1 2 nx 1 Vo ITA A2 7 and ae 2 d nx 1 Vs doa A2 8 so that l d nx ds Vii 42 9 And finally the crack width is expressed as Wa dy 7 da dpa 1 IV pp 42 10 Figure A2 3 shows the crack width wer as function of the macropore volume fraction Vmp for different polygon diameters dpa Polygon diameter 3 0 doi cm 25 700090 2 0 m a a a E 1 2t 27 30 o 5 on a m du oe ee Lupe 20 3 1 0 E o 10 0 0 02 0 04 0 06 0 08 0 1 macropore volume fraction V cm cm Figure A2 3 Crack width w as function of the macropore volume fraction Vi for different polygon diameters dy Alterra Report 1649 update02 233 Effect of crack width wa on calculation of area of vertical wall A wa and distance X pol Strictly speaking the vertical macropore wall area A wa and the horizontal distance Xpo Should be calculated on the basis of dmx instead of dpo However xpo is always used in combination with A wan as AF yan xpo Eq 6 32 Eq 6 35 and Eq 6 36
156. ariably saturated flow predictions In Advances in WaterResources 24 2001 133 144 Von Hoyningen H ne J 1983 Die Interception des Niederschlags in landwirtschaftlichen Best nden Schriftenreihe des DVWK 57 1 53 Voss C I and A M Provost 2002 SUTRA A model for saturated unsaturated variable density ground water flow with solute or energy transport U S Geological Survey Water Resources Investigations Report 02 4231 250 p Walker A 1974 A simulation model for prediction of herbicide persistence J Environ Qual 3 396 401 Warrick A W 1991 Numerical approximations of darcian flow through unsaturated soil Water Resour Res 27 1215 1222 Weir A H P L Bragg J R Porter and J H Rayner 1984 A winter wheat crop simulation model without water and nutrient limitations Journal of Agricultural Science 102 371 382 Wendroth O W Ehlers J W Hopmans H Kage J Halbertsma and J H M W sten 1993 Reevaluation of the evaporation method for determining hydraulic functions in unsaturated soils Soil Sci Soc Am J 57 1436 1443 Wesseling JG Wesseling J 1984 Influence of seepage on the depth of water tables in drainage J Hydrol 73 289 297 Wesseling J G 1987 Invloed van bodemsoort en vochtgehalte op de bodemtemperatuur Een theoretische beschouwing Cultuurtechnisch tijdschrift 27 2 117 128 Wesseling J G J A Elbers P Kabat and B J van den Broek 1991 SWATRE instructions for input I
157. ase the concept will lead to an over estimation to the surface water load relative to the results of 2D models The SWAP model provides an option to specify the top of the zone that contributes to surface water loading as a function of the average groundwater level and the drainage level Zip Fig 4 9 right according to Zip ap Pavg a fag C drain 4 17 Soil surface Q avg top det OQ arain Dian OT td Figure 4 9 2D schematization of the saturated flow domain with a hypothetical concentration profile indicated by gray shading left and the schematization of the top of the zone that contributes to surface water loading right Alterra Report 1649 update02 89 4 5 User instructions 4 5 1 Surface runoff The maximum height of ponded water stored Np ireshoja On the field surface is determined by the irregularities and the slope of the soil surface Also the extend to which local field depressions are connected to each other and are connected to the surface water affects the Np threshoa Value Typical values range from 0 5 to 2 cm for well maintained agricultural fields in the Netherlands Since it is impossible to measure the threshoia parameter directly a value should be established by expert judgement or model calibration As surface runoff is a rapid process the resistance y will typically take values of less than 1 d When the dynamics of surface runoff are relevant the
158. ation of Richards equation 34 Alterra Report 1649 update02 GIAO g HERE gee gps PEC eee At Az l V Az _ Az iia di Az Az 41 di 2 22 J J ju BE Sai 5 i m i where At t t and Az is compartment thickness The sink terms representing the root extraction S and the flow to drains S4 are evaluated at the old time level j explicit linearization The macro pore exchange rate Sm is evaluated at the new time jt level 1 and the internodal conductivity K can be evaluated at the old time level j jt x 0 or at the new time level 1 x 1 The internodal conductivity K 77 can be calculated as Arithmic mean Ki vk DEER ve 2 23 Weighted arithmic mean Dd c A 2 24 i Az Az G n j K _ jk Plpje k Y eometric mean Ke SK EEK 2 25 Azia Az Weighted geometric mean KS x E te Vie x 3 f 2 26 Starting in the saturated zone the groundwater table is simply found at h 0 Also perched water tables may occur above dense layers in the soil profile Since the SWAP model attempts to describe a wide range of layered soil types combined with different types of boundary conditions the nodal distance is made variable and should be specified by the user Calculations using a non weighted arithmic mean for the internodal conductivity show that for accurate infiltration and evaporation simulations the nodal distance should be in the order of centimetres near the soi
159. background and the implementation of this option is presented in Chapter 5 Alterra Report 1649 update02 71 Table 4 1 Options to simulate drain discharge at field scale and at regional scale Scale of y o of systems rainage flux relation rainage leve E No of sy D ge fl 1 D ge level application Hooghoudt or Ernst PE Single drainage system Specified in model input ud equation le Tabulated input Implicitly included in tabulated input Tabulated input Implicitly included in Single drai P plicitly ingle drainage system i died tabulated input Drainage resistance per Specified in model input Regional sub system per drainage system Multiple drainage system Drainage resistance per Specified in model input sub system dependent on P amp drainage system wetted perimeter of drains Simulated see Chapter 5 The options provided by the SWAP model are limited to lowland conditions Subsurface groundwater flow and drainage response of sloping fields can better be described by 2D or 3D models or Boussinesq equation based models Another limitation of the drainage equations involves the steady state assumption Hysteresis phenomena in the groundwater discharge relation as they can be observed in experimental data are attributed to the different possible shapes of the groundwater elevation surface pertaining to one groundwater level value Although there are possibilities to conceptualize the 2D groundwater dept
160. breakthrough curve of a field with fully penetrating drainage canals is identical to the breakthrough curve of a reservoir with complete mixing This is also valid if adsorption can be described by a linear isotherm and transformation occurs proportional to the existing concentration Van Ommen 1985 Alterra Report 1649 update02 179 Linear adsorption might be described by Q R a Cgs 8 23 where Kad is the linear adsorption coefficient in the saturated zone cm g Numerical analysis by Duffy and Lee 1992 showed that dispersion in the saturated zone has only a minor effect for Larain daquir Z 10 where Larain 18 the distance between the drainage canals cm and daquir the thickness of the aquifer cm Generally Larain daquit Will be around 10 or larger therefore SWAP ignores dispersion In order to derive the breakthrough curve the similarity is used between breakthrough curves of drained fields and mixed reservoirs Starting point is the solute transport equation of the unsaturated zone Eq 8 14 Replacement of non linear adsorption by linear adsorption and removal of dispersion and root water uptake results in the mass balance equation of the saturated zone 6 8 c PokaasCar darain t d Cin Cyr n 6 6 P e 8 24 aquif where 0 is the saturated water content cm cm arain 18 the drainage flux cm d Cin is the solute concentration of water percolating from the unsaturated zone g cm an
161. by lateral overland md 0 0 R QInTopLatDm1 flow runoff Exchange flux with soil matrix per compartment 1 numnod m d 1 ped E R InQExcMtxDm1Cp numno positive from macropores into matrix d Rapid drainage flux towards drain tube per compartment 1 md 0 0 4 R InQOutDrRapCp numnod numnod Average fraction of macropore wall in contact with md 0 0 i R FrMpWalWetDm 1 numnod macropore water during timestep per comp 1 numnod Dynamic part for macropores domain 2 Internal Catchment domain Areic volume at end of time interval Wm MO 5 R VIMpDm2 Areic volume of water stored at end of time interval WU OR R waSrDm2 Infiltration flux at soil surface directly by precipitation md O80 R QInTopPreDm2 Infiltration flux at soil surface indirectly by lateral overland md oom R IQInTopLatDm2 flow runoff Exchange flux with soil matrix per compartment 1 numnod md e t R InQExcMtxDm2Cp numno positive from macropores into matrix d Average fraction of macropore wall in contact with md 0 0 si R FrMpWalWetDm2 numnod macropore water during timestep per comp 1 numnod 264 Alterra Report 1649 update02 Appendix 16 Crop growth of grassland Author Iwan Supit Joop Kroes Crop Assimilation The maximum leaf CO assimilation rate in subroutine Grass is a function of the day number acronym amaxtb An afgen function with the day number as independent variable describes this dependenc
162. canopy is saturated mm h and S is the maximum storage of intercepted water in the canopy mm Integration of Eq 3 2 yields the amount of rainfall which saturates the canopy P mm Bou E E pa AP 1 x qualem sq 2 55 E mud Ve 17 P P mean For small storms Pgross lt Ps the interception can be calculated from B 1 p p P 2 56 gross For large storms Peross gt Ps the interception according to Gash 1979 follows from E a a e 2 57 gross mean Figure 3 2 shows the relation of Gash for typical values of a pine forest as function of rainfall amounts The slope OP OPgross before saturation of the canopy equals 1 KD after saturation of the canopy this slope equals Emean Pmean Alterra Report 1649 update02 55 SWAP uses mean intensities of rainfall and evaporation rate to calculate the amount of rainfall which saturates the canopy according to Eq 3 3 Next depending on the total amount of rainfall during a day the amount of interception is calculated according to either Eq 3 4 or Eq 3 5 3 3 Potential evapotranspiration of uniform surfaces Evapotranspiration refers to both transpiration of the plants and evaporation from the soil or of water intercepted by vegetation or ponding on the soil surface The addition potential refers to non limiting water supply from the soil The potential evapotranspiration flux is therefore only determined by atmospheric conditions and plant c
163. ccurs through large pores or macropores in the un saturated soil matrix Macropores are defined as pores with a diameter or width equal to or larger than 100 um Macroporosity can be caused by shrinking and cracking of soil by plant roots by soil fauna or by tillage operations Due to the very rapid flow through macropores water and solutes can reach large depths almost immediately after the start of a shower bypassing the capacity of the soil matrix for storage adsorption and transformation of potential pollutants This process is known as bypass flow or short circuiting Hoogmoed and Bouma 1980 Because of the great impact of macropores on water flow and solute transport through the vadose zone a concept has been implemented in SWAP for simulating preferential flow at the field scale Cracked clay soils reveal a large spatial variability of water contents and solute concentrations at given depth Beven and Germann 1982 Bronswijk et al 1995 Therefore instead of trying to describe water flow and solute transport at each location the field average behaviour may be easier to catch in a model In order to make the model suitable for process and scenario analysis concepts should be used that are generally applicable thus physically based Furthermore model calibration requires a limited number of parameters and preferably parameters that can be measured directly in the field The description of macropore flow in SWAP has been
164. cific setting in the landscape of the field studied different types of pathways and interconnections may play a role Surface runoff that occurs when the rainfall rate exceeds the infiltration rate is called Horton overland flow A second form of runoff occurs after the water storage volume of a soil has been exceeded which means that the groundwater table has reached the soil surface This runoff is commonly called the Dunne overland flow It occurs in areas with a shallow groundwater table and light rainfall of long duration Interflow can be defined as the near surface flow of water within the soil profile resulting in seepage to a stream channel within the time frame of a storm hydrograph Interflow involves both unsaturated and saturated flows the latter being in zones of limited vertical extent caused by soil horizons impeding vertical percolation The mechanisms by which subsurface flow enters streams quickly enough to contribute to streamflow responses to individual rainstorms are summarized in various publications Beven 1989 Infiltration excess moves slowly downwards and once it has reached the saturated zone it is called ground water Ground water moves downward and laterally through the subsurface and eventually discharges through tile drains field ditches or other open conduits A tile drain is a perforated conduit such as tile pipe or tubing installed below the ground surface to intercept and convey drainage water The SWAP m
165. ck ckckckckckckckckckckckck ck ck ck ckck ck RK OK OK Part 2c Surface water level of secondary system If SWSRF 20r 3 then the variable SWSEC must be entered SWSEC 2 option for surface water level of secondary system 1 2 I 1 surface water level is input ld 2 surface water level is simulated ES If the option is chosen to obtain surface water levels from input data SWSEC 1 the surface water level of the secondary watercourse has to be specified in the form of data pairs section 3 If the option is chosen to simulate surface water levels SWSEC 2 the user has to specify how the surface water system in the control unit functions and how it is managed section 4 Section 4 starts with some miscellaneous parameters section 4a the initial surface water level in the control unit the criterium for detecting oscillation of the surface water level the number of water management periods In the next section 4b the management period are defined as well as the type of watermanagent 1 fixed weir crest 2 automatic weir the water supply capacity and a tolerance value WLDIP The tolerance value WLDIP relates the water supply level to the target level preventing oscillations and too fast unrealistic responses of surface water management to the prevailing conditions This tolerance can be seen as the allowed dip of the surface water level and can take a value of e g 10 cm An appropriate setting of
166. condary water course Tertiary ater course Figure 4 4 Schematization of surface water system in a control unit It should be noted that contrary to the classification notation used in geo morphological sciences in this report the stream and canal order is dictated by the level of the stream bed or water level drainage level compared to the land surface level the deeper the drainage level the lower classification index The representative distance between drain devices Las m is derived by dividing the area of the subregion Areg m by the total length of the i order channels laraini m Are Laraini 7 4 23 laraini In the surface water model we assume that the different channels orders are connected in a dendritic manner Together they form a surface water control unit with a single outlet indicated by the weir in Fig 4 4 and if present a single inlet The surface water level at the outlet is assumed to be omnipresent in the subregion Friction losses are neglected and thus the slope of the surface water level is assumed to be zero This means that in all parts of the subregion the surface water level has the same depth below soil surface In the so called multi level drainage or sub irrigation approach employed by the SWAP model it is possible that more than one type of surface water channel become active simultaneously In the following we will refer to channels in terms of their 80 Alterra Report
167. ctors amp to yield the dry weight values at emergence The net growth rates of the plant organs We kg ha d result from the gross growth rates Section 7 8 and the senescence rates C kg kg d Wet E Werossi GW 7 29 By integrating Wnei over time the dry matter weight of organ i W kg ha is calculated An exception has to be made for the growth of leaves In the initial stage the rate of leaf appearance and final leaf size are constrained by temperature through its effect on cell division and extension rather than by the supply of assimilates For a relative wide range of temperatures the growth rate responds more or less linearly to tempera ture Hunt et al 1985 Causton and Venus 1981 Van Dobben 1962 The growth rate of the leaf area index war ha ha d in this so called exponential stage is described by Wear LAL Wy yp max ott 7 30 where wr Arma is the maximum relative increase of leaf area index ec q WOFOST assumes that the exponential growth rate of leaf area index will continue until it equals the assimilation limited growth rate of the leaf area index During this second source limited growth stage wrar is described by Wa 7 W S net leaf 7 51 la where Sj is the specific leaf area ha kg The green parts of stems and storage organs may absorb a substantial amount of radiation Therefore the so called green area index GAJ ha ha should be added to
168. d The maximum relative leaf death rate due to water stress Fmax w acronym perdl is crop specific and should be provided by the user Leaf senescence also occurs due to high leaf area index 1 e mutual shading In Grass a relative death rate due to self shading is defined which increases linearly from zero at a certain critical leaf area index to its maximum value which is set to 0 03 A value lower than 0 will be set to O and a value higher than 0 03 will be set to 0 03 The leaf death rate due to high LAT is calculated as LAI LAI AW W 0 03 LAI where AW Leaf death rate due to high LAI kg ha d Wy Leaf dry matter weight kg ha LAI Leaf area index ha ha LAI Critical leaf area index ha ha The critical leaf area index is defined as 2 LAI pd ky where LAI Critical leaf area index ha ha Kar Extinction coefficient for the diffuse radiation flux Alterra Report 1649 update02 275 Subsequently the highest value of the two calculated leaf death rates is selected for calculation of the dry matter weight increase reduction per time step The weight of leaves that died during the current time step is established by multiplying the death rate with the time step W max AW AW where Wa Weight of leaves that have died during current time step kg ha AW Leaf death rate due to water stress kg ha d AW leaf death rate due to high LAI
169. d ends dd mm yyyy SWMAN type of water management 1 2 I 1 fixed weir crest see part 4c and 4d 2 automatic weir see part 4e WSCAP surface water supply capacity 0 100 cm d R WLDIP allowed dip of surf water level before starting supply 0 100 cm R INTWL length of water level adjustment period SWMAN 2 only 1 31 d R IMPER 4b IMPEND SWMAN WSCAP WLDIP INTWL 1 21 Mar 1996 1 0 0 0 0 1 2 15 Jan 1997 1 0 0 0 0 1 33 29 Aug 2000 34 02 0ct 2000 End of table 106 Alterra Report 1649 update02 Dependent on the discharge relationship for the weir the user has to specify either Section 4c SWQHR 1 exponential relation or Section 4d SWOHR 2 relation given as table If an exponential relations is chosen then for each water management period with a fixed weir crest using weir characteristics the user should specify section 4c Size of the control unit catchment ha Atable with weir characteristics for each management period o Index for management period o Elevation H of the weir crest cm o dischargecoefficient Qinput m sb o discharge exponent p Head discharge relationships are given in SI units i e m for length and s for time and the discharge is computed as a volume rate m s To facilitate the input for the user we conformed to hydraulic literature This implies that the user has to specify the weir characteristics that define a relationship of the following form
170. d jig is the first order rate coefficient for transformation in the saturated zone d Eq 8 24 applies to a drainage situation Garain gt 0 In case of infiltration qais lt 0 SWAP assumes the infiltrating water from the drainage system to be solute free and Eq 8 24 transforms into 0 8 c Pasta darain at d Cer Hor 9 c Dikata 8 25 aquif Eq 8 24 and 8 25 are discretized as an explicit forward difference scheme The boundary conditions that apply to the saturated zone are included in Eq 8 24 and 8 25 180 Alterra Report 1649 update02 8 6 User instructions Box 8 1 lists the input data for solute transport which are divided over 7 parts 1 Main switch 2 Top and initial boundary condition 3 Miscellaneous parameters as function of soil depth 4 Diffusion coefficient and solute uptake by roots 5 Adsorption 6 Decomposition 7 Solute residence in the saturated zone In general the theorie description in Sections 8 2 8 6 in combination with the descriptions in the input file will be sufficient to guide the model user A few additional remarks are appropriate at this place In case conservative solute are simulated like salts are non reactive tracers we need only to consider the transport processes convection diffusion dispersion and passive uptake by plant roots At most field conditions we may neglect the effect of diffusion with respect to dispersion and therefore
171. d with Main input file swp File with daily meteorological data yyy e General section Radiation temperature vapour pressure wind Environment speed rainfall and or reference Timing of simulation period evapotranspiration Timing of boundary conditions rainfall intensities Processes which should be simulated Optional output files File with Detailed crop growth crp Meteorology section e Crop section Name of file with meteorological data Crop height Rainfall intensity Crop development Crop section Initial values Crop rotation scheme calendar and files Green surface area Crop data input file Assimilation Calculated irrigation input file Assimilates conversion into biomass Crop emergence and harvest Maintenance respiration Fixed irrigation parameters Amount and quality Dry matter partitioning of prescribed irrigation applications Death rates Soil water section Crop water use Initial moisture condition Salt stress Ponding Interception Soil evaporation Root growth and density distribution Vertical discretization of soil profile e Calculated Irrigation section Soil hydraulic functions General Hysteresis of soil water retention function Irrigation time criteria Maximum rooting depth Irrigation depth criteria Similar media scaling of soil hydraulic functions Preferential flow due to soil volumes with File with Simple crop growth crp immobile water e Crop section Preferential flow due to macro pore
172. dal points Next the coefficients a B y and f are explained for the intermediate nodes and for the top and bottom node Alterra Report 1649 update02 241 Intermediate nodes From Eq A6 2 and Eq A6 3 we may derive the coefficients NE waa dee ea A A6 4 i u 1 At j At iq B e CP iy hive A6 5 Az Az Az Az At i 44 1 hive A6 6 Az Az Tuy A6 7 Top node The temperature at soil surface is set equal to the daily average air temperature Tavg Therefore in case of the top node Eq A6 1 transforms to T Ac AE eg EE ur Sup opun cf n 7 Ph M Mee 3 A64 Az AZ Az which can be written as ci AA VEA pu Abu GILT Me La A6 9 Az Az AZAZ Az Az AZAZ Combination of Eq A6 9 and A6 3 gives the following coefficients 1 At ju At 1 B C Ad 2 A6 10 Az AZ Az Az At 1 y ies A6 11 Az Az nae At Va Ye f CH T N TL A6 12 1 u 242 Alterra Report 1649 update02 Bottom node SWAP adopts a heat flow rate qheat bot J cm d at the bottom of the soil profile At the bottom node the general heat flow equation Eq A6 1 transforms to edit a At as Te DI Ce p nS E E timana A6 13 n u which can be written as At ja j41 At TU j TU j At ar eaa E ug DADO T 2C T Ar deut 46 14 ZAZ Za AZ i u n Combination of Eq A6 14 and A6 3 gives the following coefficients AP ad a AU
173. defining factors determine the potential production that can be achieved in a given physical environment and for a plant species Radiation intensity carbon dioxide concentration temperature and crop characteristics are the major growth defining factors Their management at least in open non controlled environments is only possible through tactical decisions such as sowing date sowing density and breeding To achieve the potential production the crop must be optimally supplied with water and nutrients and completely protected against weeds pests diseases and other factors that may reduce growth 148 Alterra Report 1649 update02 defining factors defining factors defining factors CO radiation HH temperature limiting factors crop characteristics limiting factors physiology phenology canopy architecture 6 water n nutrients reducing factors nitrogen phophorus weeds e pests diseases pollutants Nutrient limited Production situation Figure 7 1 A hierarchy of growth factors production situations and associated production levels Van Ittersum et al 2003 Growth limiting factors comprise water and nutrients and determine water or nutrient limited production levels in a given physical environment Here management can be used to control availability of water and nutrients and may increase production towards potential levels Growt
174. del for preferential movement of water and solutes in structured porous media Water Resour Res 29 305 319 Goudriaan J 1977 Crop meteorology a simulation study Simulation monographs Pudoc Wageningen Goudriaan J 1982 Some techniques in dynamic simulation In Simulation of plant growth and crop production F W T Penning de Vries and H H van Laar Eds Simulation Monographs Pudoc Wageningen p 66 84 Granberg G H Grip M Ottoson Lofvenius I Sundh B H Svensson and M Nilsson 1999 A simple model for simulation of water content soil frost and soil temperatures in boreal mixed mires Water Resources Research 35 3771 3782 Greco R R F A Hendriks and W Hamminga 1997 Clay soil aggregate sorptivity measurements under different water contents Proceedings of the National Hydraulics Conference Turin Italy November 1996 Groen K P 1997 Pesticide leaching in polders Field and model studies on cracked clays and loamy sand PhD thesis Wageningen Agricultural University Wageningen The Netherlands 296 pp Groenendijk P L V Renaud and J Roelsma 2005 Prediction of Nitrogen and Phosphorus leaching to groundwater and surface waters Process descriptions of the ANIMO 4 0 model Alterra Report 983 Wageningen Groenendijk P and J G Kroes in prep Performance of the numerical implementation of the Richards equation and associated boundary conditions in the SWAP model Hadley P E H Roberts R J
175. density p g cm can be shown to depend on p and the virtual temperature Ty K p 23 486102 Pair where the virtual temperature is derived from T Tix 1 0 378 0 Pair 228 Alterra Report 1649 update02 The heat capacity of moist air Cair J g och follows from Cy 0 622 Th p air Aerodynamic resistance The aerodynamic resistance Yair depends on the wind speed profile and the roughness of the canopy and is calculated as Allen et al 1998 154 0574 m Zom Zoh air 2 Kcu where Zm is height of wind speed measurements m Zp is height of temperature and humidity measurements m d is zero plane displacement of wind profile m Zom is roughness parameter for momentum m and Zon is roughness parameter for heat and vapour m Ky is von Karman constant 0 41 u is wind speed measurement at height zm m s The parameters d Zom and Zon are defined as d 2h 3 crop Zan 70 123 h crop Zoh 0 1 Zom with Acrop the crop height cm A default height of 2 m is assumed for wind speed measurements Zm and height of temperature and humidity measurements Zn Meteorological stations generally provide 24 hour averages of wind speed measurements according to international standards at an altitude of 10 meter To calculate rar the average daytime wind 7 00 19 00 h should be used For ordinary conditions we assume Smith 1991 for the average daytime windspeed Uo day Un day 1 33
176. development a part of the living biomass dies due to senescence Chapter 7 SWAP may simulate transport of salts pesticides and other solutes that can be described with basic physical relations convection diffusion dispersion root uptake Freundlich adsorption and first order decomposition In case of advanced pesticide transport including volatilization and kinetic adsorption SWAP can be used in combination with PEARL In case of advanced transport of nitrogen and phosphorus SWAP can be used in combination with ANIMO Chapter 8 SWAP may simulate soil temperature analytically using an input sine function at the soil surface and the soil thermal diffusivity In the numerical approach SWAP takes into account the influence of soil moisture on soil heat capacity and soil thermal 12 Alterra Report 1649 update02 conductivity The top boundary condition can be input of air temperatures or soil surface temperatures Chapter 9 The snow module calculates the accumulation and melting of a snowpack when the air temperature is below a threshold value The water balance of the snow pack includes storage incoming snow and rain and outgoing melting and sublimation Melting may occur due to air temperature rise or heat release from rainfall When a snowpack is present the soil temperature top boundary condition is adjusted in order to account for the insulating effect of the snowpack In case of frost reduction factors can be calculated for the h
177. development stage 0 2 R DVS RD maximum 36 records RDTB 0 00 5 00 0 30 20 00 0 50 50 00 0 70 80 00 1 00 90 00 2 00 100 00 End of table KK KK KK RK RK RK RK RK RK KK KK KK RK KK KK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK ckck ck KKK ck k ck k ck k ck k ck k ck k ck kkk kkk KK RK RK RK RK RK RK RK KK kck KK KKK KKK KKK KK KKK KKK KKK KKK kck ck KKK KKK KKK KKK KKK KKK KKK KKK KKK kck k KKK KK KKK Part 6 yield response List yield response factor 0 5 R as function of development stage 0 2 R DVS KY maximum 36 records KYTB 0 00 1 00 2 00 1 00 End of table KKK KK RK KK KA KK KARA RAR KR AAA KKK KKK KK KK KK KK KKK KKK KKK KK KKK KK ck ckck ck ck ckck ck ck KKK ck ck KKK KKK k ck ck ck k RARA RARA RA ck KK RK RK ck ck ck ck ck ck KR KK RAR KK KKK KKK KK KK KKK KKK KK KKK KKK kck ckck kckckckck ck ck ckck ck ck ckck ck ck ckck ck k ck k ck k ck ck ck kck k ck k ck KKK KKK KKK Part 7 soil water extraction by plant roots Switch for concept root water extraction swroottyp 1 1 Macroscopic concept Feddes et al 1978 2 Microscopic concept De Jong van Lier et al 2008 if swroottyp 1 specify HLIM1 15 0 No water extraction at higher pressure heads 100 100 cm R HLIM2U 30 0 h below which optimum water extr starts for top layer 1000 100 cm R HLIM2L 30 0 h below which optimum water extr starts for sub layer 1000 100 cm R HLIM3H
178. diffusion may contribute to soil heat transport The rate of heat transfer by water vapour diffusion is small and proportional to the temperature gradient De Vries 1975 Therefore such diffusion can be taken into account by slightly increasing the soil thermal diffusivity This approach is followed in SWAP as well Apparent thermal properties rather than real thermal properties are assumed to account for both conductive and non conductive heat flow Alterra Report 1649 update02 185 9 2 Numerical solution The parameters Aneat and Cheat strongly depend on the soil moisture content Therefore in general Eq 9 3 can only be solved with a numerical solution SWAP employs a fully implicit finite difference numerical scheme to solve Eq 9 3 Ati pit TU TH Ti AP TELE a 94 Y i Ve Az Az Az 1 u C Hu T where superscript j denotes the time level subscript i is the node number Az Zi 1 zi and Az zi zii As the coefficients Cheat and Aneat are not affected by the soil temperature itself Eq 9 4 is a linear equation Both volumetric heat capacity and thermal conductivity depend on the soil composition The volumetric heat capacity is calculated as weighted mean of the heat capacities of the individual components De Vries 1963 Cheat Fea Ea f clay Camy f organic Coi F OC vater Rs F a Car 8 J where f and C on the right hand side of Eq 9 5 are the volume fraction cm cm and volumetric heat capacit
179. ding to their proportions Pmb and P at the specific depth z 128 Alterra Report 1649 update02 Rapid drainage q a Rapid drainage to drainage systems can occur via a network of lateral interconnected cracks or via otherwise nearly interconnected macropores Also when macropores are separated by just thin walls of soil matrix they can enhance drainage considerably Fed by macropore water the small matrix barriers will become saturated even when the soil matrix as a whole remains unsaturated They then form part of a saturated macropore soil matrix system that conducts water better in vertical and horizontal direction than the bulk of the soil matrix Nieber et al 2006 Sidle et al 2001 proposed the concept of a self organising network of preferential flow pathways where the connections in the network are controlled by moisture level In SWAP the complex process of rapid drainage is described with a drainage resistance This resistance may depend on the width of macropores and of shrinkage cracks in particular wider cracks have higher hydraulic conductivities It may also depend on macropore water level the higher this level the more macropore volume involved the higher the hydraulic conductivity and the lower the resistance Therefore the functional input parameter drainage resistance is considered as a reference drainage resistance it is valid for a defined reference situation The actual drainage resistance is derived from the r
180. e e comment in lines is allowed starting with or e blank lines are allowed In the input files of each parameter the symbolic name a description and an identification is given The identification between square brackets provides information on e range e unit e data type I Integer R Real Ax character string of x positions For example 5000 100 cm R means value between 5000 and 100 with a unit in cm given as a Real data type which means that in the input file a dot should be added 1 4 Modelrun The most common way to run SWAP is by executing a batch file which refers to the SWAP executable and the swp file The batch file and the swp file need to be present in the same directory The swp file contains the names and locations of other input files Therefore it is possible to have separate directories with meteorological crop and drainage data An example of the batch file is given in Box 1 1 In this case SWAP will use Hupsel swp as main input file If no name is specified behind the call Swap exe SWAP will use Swap swp as main input file The pause statement keeps the window box with screen messages open when runtime warnings or errors might occur Box 1 1 Example of batch file to run SWAP with input file Hupsel swp c Program Files SWAP Swap exe Hupsel swp pause 18 Alterra Report 1649 update02 Box 1 2 Summary of information in input files Optional files are denote
181. e swp kk KK KK KK KKK KKK ck ck ck KK KKK KKK KKK KKK KK KKK KKK KK KKK KKK KKK KKK KKK KKK ckckckckckckckck ck ck ckck ck KKK ckok ck ck ckokck Part 1 Initial soil moisture condition SWINCO 2 Switch type of initial soil moisture condition 1 pressure head as function of depth is input 2 pressure head of each compartment is in hydrostatic equilibrium f with initial groundwater level 3 read final pressure heads from output of previous Swap simulation If SWINCO 1 specify maximum MACP ZI soil depth 10000 0 cm R H initial soil water pressure head 1 d10 1 d4 cm R ZI H 0 5 93 0 195 0 120 0 End of table If SWINCO 2 specify GWLI 75 0 Initial groundwater level 10000 100 cm R If SWINCO 3 specify INIFIL result end name of final with extension END a200 kk KK KK KKK KKK KKK KKK KK KKK KKK KKK KKK KKK KK KK KKK KKK KKK KKK KKK KKK KKK AK KKK KKK KK k ck KKK ckok ckckckokok KKK KKK KKK KKK KKK KKK KKK KK KK KKK KKK KK KKK KKK KKK KKK KKK KKK KKK kck ck ck ck ckck ck kckck KKK KKK ck ck ck k ck ok ckok KKK Part 4 Vertical discretization of soil profile Specify the following data maximum MACP lines ISOILLAY number of soil layer start with 1 at soil surface 1 MAHO I ISUBLAY number of sub layer start with 1 at soil surface 1 MACP I FF O HSUBLAY height of sub layer 0 0 1000 0 cm R HCOMP height of compartments in this layer
182. e 2 1 Box 2 2 Table 2 1 Options for the lower boundary condition Lower boundary Description Type of Typical scale of condition condition application input switch SwBotB 1 Prescribe groundwater level Dirichlet Field 2 Prescribe bottom flux ot Neumann region 3 Calculate bottom flux from Cauchy region hydraulic head of deep aquifer 4 Calculate bottom flux as function Cauchy region of groundwater level 5 Prescribe soil water pressure head Dirichlet field of bottom compartment 6 Bottom flux equals zero Neumann Field region Free drainage of soil profile Neumann field 8 Free outflow at soil air interface Neumann field Dirichlet 46 Alterra Report 1649 update02 In case of options 1 2 3 5 and 6 in addition to the flux across the bottom of the modelled soil profile quo a drainage flux arain can be defined Chapter 4 In case of option 4 the lower boundary includes drainage to local ditches or drains so Qarain should not be defined separately In case of options 7 and 8 the simulated soil profile is unsaturated so lateral drainage will not occur We will discuss the 8 available bottom boundary conditions sequentially 1 Prescribed groundwater levels In this case a field averaged groundwater level avg is given as a function of time Box 2 2 SWAP will linearly interpolate between the dates and times at which the groundwater levels are specified SWAP w
183. e complicated Leaf senescence occurs due to water stress shading high LAI and also due to exceedance of the life span The potential death rate of leaves due to water stress Cleat water kg ha d is calculated as T e RS Wear i 7 3 oe 7 25 p 160 Alterra Report 1649 update02 where Wiear is the leaf dry matter weight kg ha T and T are the actual and potential transpiration rates cm de respectively and Gr is the maximum relative death rate of leaves due to water stress kg kg d The latter is crop specific and should be provided by the user A potential death rate due to self shading Cleatshade kg ha d is defined which increases linearly from zero at a critical leaf area index LAI to its maximum value at 2LAI LAI LAI LAI LAI 0 03 Wir with 0 lt _ 1 7 26 ade leaf LA I L A I with LAI 3 2 4f see section 7 4 Typical values for Ger and LAK are 0 03 d and 4 m m respectively Spitters et al 1989 WOFOST uses the highest value of Cleaf water and Giearsnaae for the combined effect of water stress and mutual shading Leaves that have escaped from premature death due to water stress or mutual shading inevitably die due to exceedance of the life span for leaves Life span is defined as the maximum time a leaf can live at a constant temperature of 35 C A physiologic ageing factor fage 18 calculated each day Iu Dus 7
184. e head further elaborated in 0 The calculation of the partial derivatives for the top and bottom compartment requires special attention The Jacobian coefficient for the first compartment reads as Flux controlled top boundary condition OF _ Au Git yay OSin Kt QUEE hi ni Oh Ari ee VOR AA Ana ETE Head controlled top boundary condition j 1 j 1 j K OF Au COR EAS OS nt a Kj 4 Ki Oh i RT ar aA Aza aK hi ni re Okie hi hi 53 ahi lo Az Oh a Az Az The internodal conductivity K l is irrespective the value of x always treated implicitly The Jacobian coefficient for the last compartment reads as Flux controlled bottom boundary OF _A CAM So eke OKs hit ni On A C on Az Az oni WORDS Alterra Report 1649 update02 237 Head controlled bottom boundary Sn Boop SE KEE KES andthe ai anit Azpa HAZ Y2Az j K j 1 j 1 jt j 1 OK hi h LE hi hyo 1 ahs Az Az any Ydz Predefined groundwater levels asi Kit m n n Y OF AZ jul IC CS FAZ ID K al o net ani V Az Az Ohi YA Az gt Az OK t ni ji a Ya n 1 n j k j K J l 4 nt E zy Ki K n E Za En Es 1 h 1 z TEWL JY Az Az i h z gwl JY Az Az Cauchy relation for the bottom boundary si K K Kt an E Az p AZ nr n2 n4 Dh Ap Oh VXAz Az VaAz t cK y OK Hk nj
185. e it takes for this particle to reach a depth y is given by t ty f a 4 8 E qyCy The travel time relation is governed by the vertical flux as a function of depth and the porosity It can be seen from Eq 4 26 that the vertical flux coheres with the drainage flux Alterra Report 1649 update02 85 4 4 2 Discharge layers The concept of the distribution of the drainage flux with depth for a single level drainage system can be very simple The Dupuit Forcheimer assumption involves disregarding the head loss due to radial flow and vertical flow in the largest part of the flow domain Based on this rule the groundwater movement towards drains in a non stratified aquifer is considered as an uni directional flow and the drainage flux is distributed uniformly with depth The distribution with depth for a multi level drainage system should ideally be based on the 3 D flow paths of water parcels migrating to drains But since such type of information is not available in the 1 D vertical model additional assumptions have to be made The concept of discharge layers has been introduced representing the flow systems associated with each of the drains Although the verification of the concept by comparing the depth of discharge layers with the streamline patterns generated by 2D models do not always agree the concept enables the accounting of the different types of water courses and the stratification of hydraulic properties in the implici
186. e layer is reached when the root tip reaches a soil compartment with a moisture content at or below wilting point or when the root tip reaches the groundwater table However in Grass the root extension stops when e no more assimilates are available but then the complete simulation process ceases e the maximum rooting depth is reached e after reaching a live weight of 2500 kg growth is balanced by dying root tissue i e death rate equals growth rate For the potential crop growth calculation water availability is assumed to be optimal and the soil moisture content is always at field capacity Alterra Report 1649 update02 277 Acronyms admi pot above ground dry matter increase kg ha d amax instantaneous gross assimilation at light saturation kg ha hr amaxtb list max CO assimilation rate as a function of day kg ha hr number asrc pot assimilates available for growth kg ha d cptrO accumulated potential transpiration cm ctrO accumulated actual transpiration cm crtO relative transpiration cvl efficiency of conversion into leaves kg kg cvs efficiency of conversion into stems kg kg cyr efficiency of conversion into roots kg kg dmi pot dry matter increase kg ha d dalv pot leaf death rate due to ageing kg d drrt pot root death rate roots kg ha d drst
187. e maize is not yet covering the soil The solar radiation fluxes are high which cause a high potential soil evaporation rate of 11 977 cm month Due to the low rainfall amounts the top soil becomes dry and the actual soil evaporation rate is only 1 107 cm month The simulated groundwater levels fluctuate between 71 6 and 112 9 cm depth Box 1 7 Example of Result inc output file for Hupsel case Project File content File name Generated at Model version Date Day 31 Jan 1980 31 29 Feb 1980 60 31 Mar 1980 91 30 Apr 1980 121 31 May 1980 152 30 Jun 1980 182 31 Jul 1980 213 31 Aug 1980 244 Hupsel water balance increments cm period Mesult inc Swap 3 2 revision 10 Date 02 May 2008 05 May 2008 15 57 06 Dcum Rain Snow Irrig Interc 31 4 690 0 000 0 050 0 000 60 4 650 0 000 0 000 0 000 91 5 490 0 000 0 000 0 000 121 4 060 0 000 0 000 0 000 152 0 930 0 000 0 000 0 013 182 6 620 0 000 0 000 0 796 213 14 570 0 000 0 000 1 424 244 4 640 0 000 0 000 1 076 Runon 0 ooooooo 000 000 000 000 000 000 000 000 Runoff 0 ooooooo 000 000 000 000 000 000 000 000 3 P 0000000 ot 000 000 000 000 068 629 362 502 DALODODOR act 000 000 000 000 068 521 328 895 Epot 563 642 316 371 977 680 056 757 Eact Drainage o K SNS 545
188. e red starts at low Tpot 10000 100 cm R HLIM4 3000 0 No water extraction at lower pressure heads 16000 100 cm R ADCRH 0 5 Level of high atmospheric demand 0 5 cm d R ADCRL 0 1 Level of low atmospheric demand 0 5 cm d R 282 Alterra Report 1649 update02 If SWROOTTYP 2 specify WILTPOINT 15000 0 Minimum pressure head at interface soil root 1 0d6 1 0d2 cm ROOTRADIUS 0 05 Root radius 0 0001 1 cm R ROOTCOEFA 0 53 Defines relative distance at which mean soil water content occurs 0 1 0 R OK kk kk I ko kk I OOOO II I II I IO IIR IRR IO A RR IO AR kkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkk Part 10 Salt stress linear relation between ECsat and crop reduction ECMAX 5 6 ECsat level at which salt stress starts 0 20 dS m R ECSLOP 7 6 Decline of rootwater uptake above ECMAX 0 40 dS m R non linear relation between salinity concentration and EC C2ECa 4 21 Coefficient a to convert salt concentration to electrical conductivity 0 0 1000 0 R C2ECb 0 763 Coefficient b to convert salt concentration to electrical conductivity 0 0 10 0 R Switch for solute conversion factors for entire profile or per soil layer SWC2ECF 1 1 conversion factors for entire profile 2 conversion factors per soil layer If SWC2ECF 1 specify for entire soil profile C2ECf 1 7 Factor f to accou
189. e shrinkage curve In order to construct this line parameter Py should be found so that eo 1 Pp eo and e 1 Pp e This can easily be done by trial and error in a spreadsheet or on paper When Py lt 0 Lz must start at point 0 2e9 instead of point 0 o e g samples A 15 and V 10 in Appendix 11 For values of IPyl lt 0 1 option 3 is recommended e g sample A 25 in Appendix 11 Input parameters are Table 6 1 eo Pu 9 moisture ratio at transition of near normal to subnormal shrinkage on L Fig 6 4 B 9 moisture ratio at intersection point of L and curve and 9p moisture ratio at tangency point of L5 to curve Values must be given with an accuracy of at least 1 of saturated moisture ratio 9 Option 3 requires the construction of three line pieces Lp1 Lp and Lp3 and one support line L in the graph of the shrinkage curve Fig 6 9 Ly connects the points 0 09 and 9 e Lp2 the points 9 e and 9 and Lj the points e and 9 e L connects the points 0 ep and 9 es Point 94 6 is situated on this line and represents the point of transition of near normal to subnormal shrinkage Point 9 e should be chosen in such a way that the three line pieces describe the shrinkage curve as accurate as possible For use in the model Lj and Lp3 are much more important than Lp So emphasis should be put on these two line pieces Input parameters are Table 6 1 eo 9 e
190. e soil porosity cm cm 174 Alterra Report 1649 update02 Variation within pores Variation due to pore network E gt Average flow direction Figure 8 1 Flow velocity variation within pores and within the pore network The bulk transport of solutes occurs when solutes are carried along with the moving soil water The mean flux of this transport is called the convective flux Jeon g cm d and can be calculated from the average soil water flux dn qc 8 3 When describing water flow we usually consider the Darcy flux q cm d which is averaged over a certain cross section In case of solute transport we have to account for the water velocity variation between pores of different size and geometry and also the water velocity variation inside a pore itself Fig 8 1 The variety of water velocities cause some solutes to advance faster than the average solute front and other solutes to advance slower The overall effect will be that steep solute fronts tends to smoothen or to disperse Solutes seem to flow from high to low concentrations If the time required for solutes to mix in the transverse direction is small compared to the time required for solutes to move in the flow direction by mean convection the dispersion flux Jas g cm d is proportional to the solute gradient Bear 1972 Oc Jas 0D dr 8 4 with Dais the dispersion coefficient cm d Under laminar flow conditions Dais itself is
191. e stage when air entry increases substantially an By and Py are dimensionless fitting parameters Alterra Report 1649 update02 121 Overburden pressure Shrinking and swelling behaviour in the field may deviate from that in the laboratory because of overburden pressure of overlaying soil layers in the field This may result in delayed horizontal shrinkage in favour of vertical shrinkage To account for this process a threshold moisture content 0 44 is introduced For moisture contents 0 gt Derack all shrinkage is vertical and for 0 lt 0 44 shrinkage is vertical and horizontal according to geometry factor rs This concept does not apply to swelling shrinkage cracks are not closed before saturation O racx is an input parameter 6 1 1 3 Horizontal distribution In the horizontal plane in the field macropore volume is distributed over different forms of macropores from holes with a diameter of 100 um to several centimetres wide several decimetres long cracks This distribution determines the functional horizontal shape of the macropores which forms the basis of the calculation of several important parameters 1 two parameters that affect lateral water exchange between macropores and soil matrix a the vertical area of macropore walls per unit of volume and b the distance from macropore wall to centre of matrix polygons 2 the lateral hydraulic conductivity of cracks in case of rapid drainage For simplicity and input parameter
192. e the geometric mean In their simulations the geometric mean increased the accuracy of calculated fluxes and caused the fluxes to be less sensitive to changes in nodal distance However the geometric mean has serious disadvantages too Warrick 1991 When simulating infiltration in dry soils or high evaporation from wet soils the geometric mean severely underestimates the water fluxes Other researchers proposed to use the harmonic mean of K or various kind of weighted averages Ross 1990 Warrick 1991 Zaidel and Russo 1992 Desbarats 1995 Van Dam and Feddes 2000 show that although arithmetic averages at larger nodal distances overestimate the soil water fluxes in case of infiltration and evaporation events at nodal distances in the order of 1 cm non weighted arithmetic averages are more close to the theoretically correct solution than geometric averages Also they show that the remaining inaccuracy between calculated and theoretically correct fluxes is relatively small compared to effects of soil spatial variability and hysteresis Therefore the SWAP development team has a preference for applying weighted arithmetic averages of K which is in line with commonly applied finite element models Kool and Van Genuchten 1991 Sim nek et al 1992 Therefore default choices are weighted arithmetic mean SWKMEAN 2 and explicit solution SWKIMPL 0 44 Alterra Report 1649 update02 Box 2 1 Information on soil water flow in main fil
193. ea per unit of horizontal area it is divided by the area of the polygon Thus the effective vertical area of the wall of the matrix polygons A aj per unit of depth and horizontal area which implies Alterra Report 1649 update02 231 per unit of volume equals the quotient of the polygons perimeter divided by their area which equals 4 dpoi cm Figure A2 2 Area A and diameter d of basis polygon pol and matrix polygon mtx Crack width Wer is equal to the difference between dol and dmi Effective crack width For even sided regular polygons it can be derived that their sides x Fig A2 1 can be expressed as C n dpo where C is a constant that depends on n For squares hexagons and circles C equals 4 23 and m respectively With C a general equation for the area Apo cm of an even sided regular polygon as function of d can be derived Aut n dy nd du C ds 42 2 For this equation we define dpo as the distance between the centres of two adjacent basis polygons Fig A2 2 The value of this diameter is fixed The value of the actual soil matrix polygon diameter dmx depends on the crack width which is not fixed in case of a shrinking matrix Thus the crack width wer can be calculated as Fig A2 2 w d d cr pol 42 3 mtx The horizontal area of the cracks A cm as fraction of Apo depends on the macropore volume fraction Vinp cm cm as A e A2 4 The horizontal
194. eached and the amount of external supply that is needed if any 3 the discharge that takes place if any and the surface water level at the end of the time step Two options for describing the functioning of a weir are available 1 the target level of a fixed weir coincides with the crest level which has a constant value within a certain management period or 2 the target level of soil moisture controlled weir is a function of a soil moisture state variable and is defined by a water management scheme 5 1 2 1 Fixed weir The fixed weir option employs a power function based stage discharge relationship Qais sur for which the parameters in the input are specified in SI units or a tabulated relationship The power function based stage discharge relationship reads as Qai Qus 0 Sz s yA vir lt is _ weir Vt sur weir 5 4 d dis A A C cu cu in which Qais is the volumetric discharge m s Acu is the area of the control unit m Zweir 1S the weir crest level m Qweir is the discharge coefficient m P d and literature values are often given in these units The conversion to internal units is handled by the SWAP model itself Alterra Report 1649 update02 99 Bweir is the discharge exponent For a broad crested rectangular weir wei 18 approximately given by a 1 7 x weir width weir The stage discharge relationship can optionally be specified by a table Then the relationship shou
195. eam By running the SWAP setup file a number of folders are created as depicted in Figure 1 2 These folders contain e Swap executable e Swap source code e User manual in Documents e Two examples Hupsel and CranGras e Additional input data 16 Alterra Report 1649 update02 o Daily weather data of Wageningen 3 O swap3 2 meteorological station of the period 1971 AdditionalData 2000 E C3 crops O detailed o Simple crop input data for grass fodder C3 detailed grass maize potato sugar beet and winter wheat simpel i O meteo o Detailed crop input data for winter wheat soi grain maize spring barley rice sugar C3 documents beet potato field bean soy bean winter r1 id zi ranGras oilseed rape and sunflower B Q3 Data O Crops After running the setup file SWAP can be gt iiri eatner automatically launched for the example Hupsel measured E C3 hupsel Data 1 3 Model input O Crops O Drainage O Weather The input data of SWAP are divided over 4 different executable file types licenses e Main input file swp source NA Figure 1 2 Installed folders by e Meteorological file yyy standard SWAP setup file e Crop growth file crp e Drainage file dra Box 1 2 provides an overview of the information in these input files The main input file and the meteorological data file are always required Input files of crop growth and drainage are optional The extensions of
196. easured levels into levels that are suitable for calibration of SWAP Alterra Report 1649 update02 93 Box 4 5 Multi level drainage with fixed resistances and imposed drainage levels in drainage file DRA OK OK RK ROK ROK ROK RK RK RK ck ckck ck ck ckck ck ck ckck ck ck ck ck ck ck ck ck ck ck ck KK KK KR ck ck ckckckckckckckckckckckckckckckckckckckckckckck ck kck ck ck ck ck OK OK METHOD 3 Part 3 Drainage and infiltration resistance DRAMET 3 NRLEVS Number of drainage levels 1 5 I KOK ROK ROK ROK ROK RK ROK RK ROK RK ck ckckckck ck ck ck ck ck ck KK RK KK KK KR KR RK KK RK KK RK RK AAA KA RK OK AAA KARA OK RK OK Part 3a Drainage to level 1 DRARES1 100 INFRES1 100 SWALLO1 1 Drainage resistance 10 1d5 d R Infiltration resistance 0 1d5 d R Switch for allowance drainage infiltration 1 Drainage and infiltration are both allowed 2 Drainage is not allowed 3 Infiltration is not allowed Level of drainage medium bottom 1000 0 cm R Type of drainage medium 1 drain tube 2 open channel ZBOTDR SWDTYP If SWDIVD 1 drainage flux vertically distributed specify the drain spacing L1 20 Drain spacing 1 1000 m R In case of open channel SWDIYP1 2 specify date DATOWL1 dd mmm yyyy and channel water level LEVEL1 cm negative if below soil surface maximum MAOWL records DATOWL1 LEVEL1 12 jan 1981 90 0 14 dec 1981 90 0 End of table
197. ed leaves taking into account their proportion in each layer The proportion of sunlit leaf area at depth L in the canopy equals the proportion of the direct component of the direct flux reaching that depth This proportion is calculated analogous to Eq 7 14 using the extinction coefficient of the direct radiation component Figure 7 4 shows the CO assimilation rate at different sunlight intensities as measured for different crops Striking are the higher assimilation rates of so called C4 crops in comparison to C3 crops The reason is that C4 plants are more effective in fixation of CO within the leaf The internal CO concentration amounts 120 ppm at C plants and 210 ppm at C plants Currently the CO concentration in the atmosphere is about 370 ppm This means that at C4 plants the gradient for diffusion of CO throught the stomata is 250 160 1 56 times as large as at C plants Alterra Report 1649 update02 155 on c C plants Maize sorghum sugar cane ul c Efficient C4 plants Soybean cotton lucerne p ce ww e Less efficient C4 plants Tobacco red clover cock s foot grass M o C plants growing in shade Ivy philodendron monstera o o ee we we ee a e AAA AAA C0 exchange rate mg dm leaf surface h t cf 20 40 60 80 100 Radiation of full sunlight Figure 7 4 CO exchange rate as function of radiation amount for C3 and C plants
198. ed to a homogeneous soil profile and Zarain 1 0 1 lt Kpbo Kntop lt 50 Zarain depends on the ratios Kpbo Kntop and Dpo Diop as given in Table Khbot Khtop gt 30 Zarain 4 Table 4 3 The geometry factor garain as obtained by the relaxation method after Ernst 1962 K hbov Khtop D bot D top 1 2 4 8 16 32 1 1 2 0 3 0 5 0 9 0 15 0 30 0 2 0 2 2 4 3 2 4 6 6 2 8 0 10 0 2 4 3 2 6 3 3 4 5 5 5 6 8 8 0 2 6 5 2 8 3 5 4 4 4 8 5 6 6 2 2 8 10 32 3 6 4 2 4 5 4 8 5 0 32 20 3 6 3 7 4 0 4 2 4 4 4 6 3 6 50 3 8 4 0 4 0 4 0 4 2 4 6 3 8 4 3 2 Field scale drainage relation defined by a tabulated function The SWAP model provides an option to specify a tabulated drainage flux relationship as a function of the groundwater level When this option is chosen one should specify a number of Pewi gt Q rain data pairs For a linear relation only two data pairs suffices but a non linear relation requires more data pairs A non linear relation can be either the result of e describing the drainage flux by the Hooghoudt equation e an analysis of the flux relation in a stratified profile by means of a numerical model e ananalysis of measured field data The general shape of such a relation is given in Fig 4 3 Specifying a non linear relation by means of a tabulated function involves a linearization since flux values are derived by linear interpolation Specifying more data pairs can reduce the inaccuracy which results from this type of l
199. eference resistance according to the deviations from the actual situation to the reference situation The reference situation is preferably an average situation at the field scale and should be based on a relevant reference level In this SWAP version it is fixed The reference level is chosen to be the drainage basis drain depth or surface water level The definition of the reference situation is soil moisture is in hydrostatic equilibrium with groundwater level at depth of drainage basis and with the water level in the MB macropores at a depth of three quarters of the drainage basis depth The actual drainage resistance Ya d is calculated from the reference drainage resistance Yrer d according to the ratio between actual and reference transmissivity KD of the MB macropores cm d KD Yact E kp 6 37 a ref where KD j K dz Ch ac Ya de 6 37 0 ZboiMB ZbotMB pol Zbomg POl with Kia cm de the lateral hydraulic conductivity of the macropores ZvomB and ZievMB cm the depths of the bottom of and the water level in the MB macropores C Alterra Report 1649 update02 129 is a constant that follows from the slit model for conductivity Eq 6 28 Its value is irrelevant because it is eliminated in Eq 6 37 a The exponent r a is a reaction coefficient that determines the effect of width we cm on Yact It varies between 0 and 3 When rya 0 Yac becomes independent of wer Rapid drainage flux q
200. efined as the daily amount of the living biomass which no longer participates in the plant processes In Grass stem and root death rate are considered to be a function of the day number This dependency is described using an AFGEN function with the day number as the independent variable Note that in Grass the both the stem and root death rate are set to zero The death rate of leaves is more complicated Leaves die due to shading high LAD water stress and due to exceeding the life span In Grass the initial dry weight values of the organs are calculated An initial value for the total crop dry weight acronym tdwi should be provided by the user This value is multiplied by the partioning factors pc at emergence yielding the initial dry weight values of the organs Leaf growth and leaf area extension The green leaf area is the major determinant for light absorption and crop photosyn thesis Under optimal conditions light intensity and temperature are the environmental factors influencing the leaf area expansion rate Light intensity determines the photosynthesis rate and hence the supply of assimilates to the leaves Temperature affects the cell division and extension rate During the early crop growth stages temperature is the overriding factor The leaf appearance rate and final leaf size are constrained by temperature through its effect on cell division and extension rather than by the assimilates supply The growth curve in the ea
201. eleton around the larger pores remain water filled 120 Alterra Report 1649 update02 Void ratio cm3 cm 3 A Void ratio cm cm 93 B 2 r i 14 P Zero Residual Normal Super Subnormal Near normal shrinkage shrinkage shrinkage is normal shrinkage 4 10 gt 8 H 1 P d 6r E Saturation 4 Saturation line line Jr uo 2 z j EH Li bt 0 1 Da 2 0 2 4 6 8 10 12 14 Moisture ratio cm3 cm3 Moisture ratio cm cm 3 Figure 6 4 Typical shrinkage characteristic of A clay modified after Bronswijk 1988 and B peat after Hendriks 2004 expressed as void ratio e as a function of moisture ratio 9 showing the three shrinkage stages Black dots in B are measurements while solid line is fit with Eq 6 19 3 Supernormal shrinkage volume reduction exceeds by far moisture loss small pores are emptied and the skeleton collapses so that air is driven out of the larger pores and the matrix reaches its final smallest volume when the moisture content is zero Hendriks 2004 equation for the shrinkage curve of peat and peaty soils reads 9 exp B 9 exp B gg 1 Pi for0 9 9 6 19 4 iz exp au exp Bu e e for 9 x9 9 6 19 b with 9 0 i ms gt 9 1 0 6 19 c 9 Oy 9 p for 0 lt a lt By 6 19 4 9 By where 9 is the moisture ratio at the transition of the near normal shrinkage stage to the subnormal shrinkag
202. eligman and R W Benjamin 1981 Simulation of water use and herbage growth in arid regions A re evaluation and further development of the model Arid Crop Agricultural systems 6 159 193 Van Keulen H and J Wolf 1986 Modelling of agricultural production weather soil and crops Simulation Monographs Pudoc Wageningen The Netherlands pp 479 Van Keulen H and N G Seligman 1987 Simulation of water use nitrogen nutrition and growth of a spring wheat crop Simulation Monographs Pudoc Wageningen The Netherlands 310 pp Alterra Report 1649 update02 221 Van Laar H H J Goudriaan and H van Keulen Eds 1992 Simulation of crop growth for potential and water limited production situations as applied to spring wheat Simulation reports CABO TT 27 CABO DLO WAU TPE Wageningen 72 pp Van Ommen H C M Th van Genuchten W H van der Molen R Dijksma and J Hulshof 1989 Experimental assessment of preferential flow paths in a field soil J Hydrol 105 253 262 Van Stiphout T P J H A J van Lanen O H Boersma and J Bouma 1987 The effect of bypass flow and internal catchment of rain on the water regime in a clay loam grassland soil J Hydrol 95 1 11 Van Wijk W R Ed 1966 Physics of plant environment North Holland Publ Comp Amsterdam The Netherlands 2nd edition 382 pp Vogel T M Th van Genuchten M Cislerova 2001 Effect of the shape of the soil hydraulic functions near saturation on v
203. emperature above which all precipitation is rain 0 0 5 0 oC R TePrSnow 2 0 Temperature below which all precipitation is snow 5 0 0 0 oC R SNOWCOEF 0 3 Degree day factor for snowmelt 0 0 10 0 cm oC d R SWFROST 1 Switch in case of frost stop soil water flow Y 1 N 0 If SWFROST 1 then specify soil temperature to start end end flux reduction tfroststa 0 0 Tfrz soil temperature below which soil water starts freezing 10 0 5 0 0C R tfrostend 1 0 Tmlt soil temperature above which soil ice starts melting and below which all soil water is frozen 10 0 5 0 oC R KK Ck ck KK KK KKK KKK KK KK KK KKK KKK KK KKK KK KKK KKK KK KKK KKK KKK KKK KKK KKK KKK kckck ck ck ck k ck k ck ck ck k ck ck KKK KK Alterra Report 1649 update02 199 200 Alterra Report 1649 update02 11 Irrigation The SWAP water balance simulations may be used to develop optimal irrigation schedules by evaluating alternative application strategies Irrigation strategies may be applied with a fixed or a scheduled regime The fixed regime is defined by the time and depth of irrigation application The scheduled regime is defined by different criteria for time and depth of an irrigation application A combination of a fixed and a scheduled regime is also possible This regime allows the evaluation of water productivity in relation to several degrees of water stress 11 1 Fixed irrigation regime At user defined dates a fixed ap
204. en application reltr ratio actual transpiration over potential transpiration rest pot death plant material in current time step kg ha rfsetb list senescence reduction factor as function of day number rgrlai maximum relative increase of LAI per day ha ha rid day number d rml rel maintenance respiration rate of leaves kg kg d rmres pot maintenance respiration at reference temperature of kg ha d 25 C rms rel maintenance respiration rate of stems kg kg d rmr rel maintenance respiration rate of roots kg kg d rr pot growth rate roots cm d rri maximum daily growth rate roots cm d rdrstb list relative stem death rates as function of day number kg kg d sla pot array that contains the specific leaf area classes ha kg slat pot specific leaf area at time step t ha kg slatb list specific leaf area as function of day number ha kg span life span of leaves under optimum conditions d ssa specific stem area ha kg tagp pot total above ground production stems leaves kg ha tagps pot total above ground death plant material kg ha tagptpt pot accumulated total above ground death plant material kg ha Alterra Report 1649 update02 279 tav average temperature C tbase lower threshold temperature for ageing of leaves C tdwi initial total crop dry weight kg ha teff temperature factor for the maintenance respiration tmnftb
205. ence criterion For this purpose SWAP employes the Alterra Report 1649 update02 43 number of iterations needed to reach convergence Ni in the following way Kool and Van Genuchten 1991 e Ni 3 multiply time step with a factor 2 e 3 lt Ny lt Maxi keep time step the same e Ni gt Max divide time step by a factor 2 where Max is a user defined maximum number of iterations allowed The maximum number of back track cycles should also be specified by the user A common value for this maximum is 3 Routinely SWAP uses three convergence criteria e the maximum difference of nodal water contents between iterations e the maximum difference of groundwater level fluctuations between iterations e the water balance error of a possible ponding layer For the initial time step SWAP will take At NA sin AM mas Depending on Ni the time step will be decreased maintained or increased for the following timesteps The timestep is always confined to the range Afin At Afmax When the actual time step in a certain part if the simulation period is at its minimum size At Afmin the maximum number of iterations allowed is set to 2 Max In the numerical solution section also a choice can be made with respect to spatial averaging of hydraulic conductivity and explicit implicit use of hydraulic conductivity in the numerical solution Haverkamp and Vauclin 1979 Belmans et al 1983 and Hornung and Messing 1983 proposed to us
206. ent static and light areas dynamic macropore volume Dark colour is the soil matrix Numbers are imaginary macropore volumes meaning Total Main Bypass Internal Catchment me fraction of static macropores Vs cm cm as a function of depth z is described with the constant Pico the function F Eq 6 4 and the two additional input parameters Vio describing the volume fraction of static macropores at the soil surface and Zs cm signifying the depth of static macropores In general all V in cm cm Va Vambo Vaie and thus Vii Vamo Vaio 6 7 4 where Verio Be oao and Va 1 ni B ida 6 7 b The static macropore volume fraction of the MB domain as a function of depth is calculated as Vas Vaio for 02 z gt Z 6 8 a az V cub Vianoo Z Z for Z 2 z Zy 6 5 0 Viso 0 for z lt La 6 8 c And the static macropore volume fraction of the IC domain as a function of depth Vaio F V st ic st ic O for 02 z gt Ze 6 9 a V st ic 0 for z Zi 6 9 b Alterra Report 1649 update02 117 Dynamic macropore volume The dynamic macropore volume originates from the shrinking of the soil matrix due to soil moisture loss In general this process is restricted to soils that contain substantial amounts gt 10 15 mass of clay minerals except kaolonite and or organic matter Mostly the shrinkage volume occurs as shrinkage cracks But shrinkage of the matrix may also enlarge cylinder shaped mac
207. entation 2 7 1 Richards equation 2 7 2 Numerical solution 2 7 3 Numerical implementation of boundary conditions 2 7 3 1 Top boundary condition 2 7 3 2 Bottom boundary condition User instructions 2 8 1 General 2 8 2 Bottom boundary conditions Evapotranspiration and rainfall interception 3 1 3 2 3 3 3 4 3 5 3 6 3 7 Introduction Rainfall interception 3 2 1 Agricultural crops 3 2 2 Forests Potential evapotranspiration of uniform surfaces 3 3 1 Penman Monteith method 3 3 2 Reference evapotranspiration and crop factors Potential transpiration and evaporation fluxes of partly covered soils Actual plant transpiration Actual soil evaporation User instructions 3 7 1 General information 3 7 2 Weather data Alterra Report 1649 update02 11 15 15 16 17 18 21 21 26 2 27 27 28 29 3l 32 34 34 25 38 38 39 43 43 46 33 53 54 54 55 56 57 59 60 61 62 64 64 66 3 7 3 Soil data 4 Surface runoff interflow and drainage 4 1 4 2 4 3 44 4 5 Surface runoff Interflow Drain discharge 4 3 Field scale drainage relation according to Hooghoudt and Ernst 4 3 2 Field scale drainage relation defined by a tabulated function 4 3 3 General aspects of regional scale drainage 67 69 70 71 71 75 78 79 4 3 4 Regional scale drainage relation defined by a tabulated function 81 4 3 5 Multi level drainage with fixed resistances and imposed drainage levels 82 4 3 6
208. eo Ga 9 i useful when limited information about the exact curves is available When just a rough sketch of a curve is available it may be possible to recognize these typical points For clay soils the typical points are the void ratio eo at 9 0 ax and the moisture ratio 9 at transition of normal to residual shrinkage Fig 6 4 A With these two input data SWAP generates the parameters of Kim s relationship For peat soils there are two options to use typical points of the shrinkage curve The first option 2 in Table 6 1 requires typical points with which the parameters of Hendriks curve can be generated The second option 3 in Table 6 1 enables to describe the shrinkage with three straight line pieces Alterra Report 1649 update02 143 os Saturation line Y Saturation line mo G a Figure 6 9 Construction of support lines and line pieces in the graph of the peat shrinkage curve to find values of input parameters for Option 2 of Table 6 1 typical points left and for Option 3 of Table 6 1 3 straight line pieces right Symbols in circles represent input parameters Option 2 requires the construction of three support lines L Ly and La in the graph of the shrinkage curve Fig 6 9 L connects the points 0 e0 and 9 e L is parallel to the saturation line and starts at point 0 e0 L5 connects the points 0 e 0 and Qey and is tangent to th
209. er may choose to define the soil as surface reference level by specifying zero for the altitude A flow chart of the input for the surface water module section 2 in the input file is given in figure 5 3 The user should make selections for the kind of surface water system SWSRF and the kind of control SWSEC The different parts of section 2 are described hereafter Alterra Report 1649 update02 103 Start section 2 ection 2a Select system SWSRF Section 2 urface water levels in rimary water course WLP ection 2 Select control SWSEC 1 Section Surface water levels in secondary water course WLS Section 4 Miscellaneous parameters Type of water management Parameters for fixed or automatic weir End Figure 5 3 Flow chart for input data of surface water system Section 2 starts with a switch section 2a variable SWSRF for three options 1 no surface water system is simulated 2 surface water system is simulated with no separate primary water course 3 surface water system is simulated with a primary water course level 1 separate from the control unit If the first option SWSRF 1 has been chosen the user may skip the rest of section 2 For the second or third option SWSRF 2 or 3 the user has also to specify how the surface water level in the control unit is determined section 2c variable SWSEC 1 the surface water level is si
210. er repellent soils J Hydrol 184 153 173 Van Dam J C J Huygen J G Wesseling R A Feddes P Kabat P E V van Walsum P Groenendijk and C A van Diepen 1997 Theory of SWAP version 2 0 Simulation of water flow solute transport and plant growth in the Soil Water Atmosphere Plant environment Wageningen University and Alterra Technical Document 45 Van Dam J C 2000 Field scale water flow and solute transport SWAP model concepts parameter estimation and case studies PhD thesis Wageningen Universiteit 167 p Van Dam J C and R A Feddes 2000 Simulation of infiltration evaporation and shallow groundwater levels with the Richards equation J of Hydrol 233 72 85 Van Dam J C P Groenendijk R F A Hendriks and J G Kroes 2008 Advances of modeling water flow in variably saturated soils with SWAP Vadose Zone Journal in press Van de Pol R M P J Wierenga and D R Nielsen 1977 Solute movement in a field soil Soil Sci Soc Am J 41 10 13 Van den Berg F and JJ T I Boesten 1998 PEsticide Leaching and Accumulation model PESTLA version 3 4 description and user s guide Technical Document 43 Alterra Green World Research Wageningen 150 p Van den Broek B J J C van Dam J A Elbers R A Feddes J Huygen P Kabat and J G Wesseling 1994 SWAP 1993 input instructions manual Report 45 Dep Water Resources Wageningen Agricultural University Van der Molen W H and J Wesseling 1991 A
211. es for variables ingdra1 ingdrab is determined by the variable nrlevs The value of nrlevs determines the number of drainage systems for which flux densities must be given postive from soil to drainage system Flux of drainage system of 1st order e g canal Flux of drainage system of 2nd order e g ditch Flux of drainage system of 3rd order e g trench Flux of drainage system of 4th order e g tube drain Flux of drainage system of 5th order e g rapid drainage Soil cover LAI Rooting Depth Alterra Report 1649 update02 md md md m d 1 m d 1 m m m m m sal l zl zu 0 0 1 0 s 0 0 10 0 0 0 numnnod TJ 20mm v D inqdra 1 numnod inqdra 2 numnod ingdra 3 numnod inqdra 4 numnod inqdra 5 numnod soco lai drz 263 Crop Factor or crop height orcm 0 0 R cf Average daily air temperature E 50 0 50 0 R tav Average daily soil temperature of compartments 1 NUMNOD C 50 0 50 0 R tsoil numnod Dynamic part for macropores domain 1 Main Bypass Flow domain Water level at end of time interval m surf 0 0 Es R WaLevDm1 Areic volume at end of time interval rf O MO R VIMpDm1 Areic volume of water stored at end of time interval mm 0 0 R WaSrDm1 Infiltration flux at soil surface directly by precipitation md 0109 R QInTopPreDm1 Infiltration flux at soil surface indirectly
212. ess can be allowed by specifying f gt 1 11 2 1 3 Allowable depletion of totally available water Depletion of water in the root zone can also be evaluated relative to the total amount of water available in the root zone as given by the difference between the field capacity and the wilting point Irrigation is then applied whenever the depletion of water in the root zone exceeds fraction f of the available water Us U Je f Usa Una 11 4 where Uy cm is the root zone water storage at h ha the pressure head at which root water extraction is reduced to zero f is a user defined factor depletion fraction 202 Alterra Report 1649 update02 11 2 1 4 Allowable depletion of field capacity water In case of high frequency irrigation systems drip it may be useful to specify the maximum amount of water that may be extracted below field capacity AU max cm Irrigation is then applied if SU 7 AU 11 5 max 11 2 1 5 Critical pressure head or moisture content The user may specify a soil moisture threshold value nin cm cm or pressure head threshold value Amin cm and a corresponding depth for which the threshold values are valid This option may be used to simulate irrigation with automated systems relying on soil moisture measurements Irrigation is then applied whenever a threshold is exceeded P dr lt O in or T ur hain 11 6 where Qsensor and Asensor are the threshold values for soil moisture and pr
213. essure head respectively 11 2 1 6 Fixed interval By default an irrigation interval has a minimum of one day and the length of the interval is variable and determined by the moment when one of the previously mentioned timing criteria becomes valid The user may optionally choose a fixed interval of one week between possible irrigation events Irrigation events occur weekly during crop growth when the required amount of water to bring the rootzone to field capacity exceeds a given threshold value This threshold value is input to the model 11 2 1 7 Minimum interval The length of the interval between irrigation events may also be variable and be determined by the moment when one of the timing criteria becomes valid The user may select this option in addition to one of the previous five criteria par 11 2 1 1 11 2 1 5 to have a minimum time interval between irrigation applications 11 2 2 Depth criteria Scheduled irrigation results in gross irrigation depths Interception of irrigation water may occurin case of sprinkling irrigation pec 11 7 Two option are available for the amount of irrigation Alterra Report 1649 update02 203 e An application depth which is brings the root zone back to field capacity e A fixed application depth In addition to one of these 2 options the actual depth of the application may be limited by a minimum and a maximum level The 2 criteria and the option for limited depth will be explained here
214. expressed in development stage D having the value 0 at seedling emergence 1 at flowering and 2 at maturity Van Heemst 1986a 1986b The most important phenological change is the one from vegetative 0 lt D lt 1 to reproductive stage 1 D 2 which changes drastically the dry matter allocation to organs WOFOST starts crop growth 81 simulation at emergence of which the date should be specified by the user A crop passes through m a f m o L Effective temperature gt m 1 successive phenological development a f stages of which the length depends on the development rate 0 0 5 10 15 20 25 30 35 40 Development rates before floral Daily average temperature initiation or anthesis D 1 are Figure 7 3 Example of effective temperature for controlled by day length and temperature sum as function of daily average temperature After anthesis only temperature temperature will affect development rate Higher temperatures accelerate the development rate leading to shorter growing periods It has often been demonstrated that over a wide range of temperatures the development rate increases more or less linearly with temperature Van Dobben 1962 Van Keulen and Seligman 1987 Therefore WOFOST uses the temperature sum to account for the effect of temperature on the development stage An effective temperature 7 C is calculated as function of daily average temperature 7 C For species or
215. f the groundwater elevation as one of the driving forces of groundwater discharge and to the lower boundary condition one wants to impose The general formulation of the drainage equation Of Qao O drain qu at 9T Pave 7 Parain 4 5 Y drain where Pam Phreatic groundwater level midway between the drains or ditches cm 94 averaged phreatic groundwater level midway between the drains or ditches cm Parain drainage level cm Yarain drainage resistance d Drainage relations are generally derived from the groundwater elevation as a function of distance An example is given in Figure 4 2 qy x 0 X L grain 2 x Larain X 2KD Parain i Q x Parain Udrain Y entr 7 rad ddrain D K Figure 4 2 Groundwater elevation as a function of distance as the basis for drainage equations For drainage design purposes one may be interested in the maximum groundwater elevation 9 but for the analysis of regional water management the average groundwater elevation 9 is often a key variable to be studied The different backgrounds reveals itself in the manner the drainage flux is calculated For field applications the relation between the drainage flux and the groundwater elevation can be expressed by the Ernst equation modified with respect to the introduction of an additional entrance resistance Alterra Report 1649 update02 73 Lih P owl O drain owl O rain Qdrain
216. f water flow PhD thesis Wageningen University 169 p Booltink H W G and J Bouma 1993 Sensitivity analysis on processes affecting bypass flow Hydrol Process 7 33 43 Boons Prins E R G H J de Koning C A van Diepen and F W T Penning de Vries 1993 Crop specific simulation parameters for yield forecasting across the European Community Simulation Rep 32 CABO DLO and SC DLO Wageningen The Netherlands Bos M G J Vos and R A Feddes 1996 CRIWAR 2 0 A simulation model on crop irrigation water requirements ILRI publ 46 Wageningen The Netherlands Bouma J and J L Anderson 1973 Relationships between soil structure characteristics and hydraulic conductivity p 77 105 In R R Bruce ed Field soil moisture regime SSSA Special Publ no 5 Am Soc of Agron Madison Wis Bouma J and L W Dekker 1978 A case study on infiltration into a dry clay soil I Morphological observations Geoderma 20 27 40 Bouma J C Belmans L W Dekker and W J M Jeurissen 1983 Assessing the suitability of soils with macropores for subsurface liquid waste disposal J Environ Qual 12 305 311 Bouma J 1990 Using morphometric expressions for macropores to improve soil physical analyses of fields soils Geoderma 46 3 11 Bouman B A M H van Keulen H H van Laar and R Rabbinge 1996 The School of de Wit crop growth simulation models a pedigree and historical overview Agric Systems 56 171 198 Bouten W
217. fluence can be ignored by choosing an appropriate temperature sum which leads to an equivalent crop life cycle The simulation of crop growth stops when the development stage reaches the stage at which the crop will be harvested The development stage at harvest time should be provided by the user 7 3 2 Radiation fluxes above the canopy Measured or estimated daily global radiation wavelength band 300 3000 nm is input for the model Incoming radiation is partly direct with the angle of incidence equal to the angle of the sun and partly diffuse with incidence under various angles The sine of solar elevation as a function of the day hour can be calculated with 2n t 12 sin p 20 ED n J 7 5 sun sin L sin o cos L COS O pun zl 24 with Byun the solar elevation degrees Osun is solar declination degrees Ly is geographic latitude degrees and f is hour of the day Only about 50 percent of the global radiation is photosynthetically active PAR Photosynthetically Active Radiation wavelength band 400 700 nm The daily incoming PAR J m d is calculated by multiplying half of the daily global radiation with the ratio of the actual effective solar elevation and the integral of the effective solar height taking into account reduced atmospheric transmission at low solar elevations sin p 1 t 0 4 sin B PAR 0 5 R sin p 7 6 mod sun 152 Alterra Report 1649 update02 where R is daily global
218. for F h is then solved for the unsaturated compartments The bottom boundary condition for this set of equations is defined by A j _ pj hit _ pit F n o oi KIE nA n ggj ghe on pg n At n n n YAAZ Az n H V Az Az 2 38 n 1 Az si S 45 a an dn mn The groundwater level is situated between the nodal points n and n The pressure head of nodal point n 1 is approximated his by wl z quic pnr ww 2 39 n 1 n ze gwl 40 Alterra Report 1649 update02 where z is the height of the node in compartment n and gwl is the groundwater level Substitution into Eq 2 30 yields el Ay u judo y j l n PO F Bee os o KIS he ue 1 KI ave EA ent 1 At j a AAZ Azp TE VA AZ E Az a 2 40 Az loh S s After iteratively solving the set of equations for i lt n the pressure head profile of the compartments i gt n can be calculated from the pressure head of the two adjacent upward nodes 2 41 nit a Kj Az hi K jy Az Az Kin l ek il He Y Az Az Da mm Ki Az Az Ki Az Az i Kj Az Azi Kit i s oj Aclsz SS Cauchy relation for the bottom boundary The flux through the bottom boundary is defined by the difference the hydraulic head at the lower boundary and the hydraulic head 9 cm of the regional groundwater specified by the user divided by a flow resistance c d The hydra
219. for every management period The minimum level of management scheme should identical to the minimum level of the discharge relationship 5 2 User instructions 5 2 1 Example case The Wildenborch case is presented to explain the capabilities of the SWAP model to simulate surface water levels and to impose different options of water management Input data were derived from the results of a monitoring program which was carried out in several fields surrounding the Wildenborch estate in the eastern part of The Netherlands Data series were collected on meteorology soil groundwater and surface water during several years Here we focus on a field with a groundwater observation point GWL in Fig 5 1 and measurements in the adjacent surface water SWL and weir in Fig 5 1 The SWAP model was applied assuming a seepage flux at the lower boundary described as a Cauchy condition due to regional flow and local flow to surface water systems at the lateral boundary The surface water system was schematized in two systems The first system has a weir with a movable crest and a depth of 1 0 meter below the soil surface The second system has a depth of 0 6 meter below the soil surface The drainage resistances of the two systems were calibrated with PEST Doherty et al 1995 The crest level was specified according to monitored data Alterra Report 1649 update02 101 102 Alterra Report 1649 update02 5 2 2 Input instructions The
220. function of depth is a crucial property of macropore geometry in the concept It determines the distribution of macropore volume and water flow over both domains It is expressed in the volumetric proportion Pam of each domain dm Views Veg P gt and P 6 1 V st V Vis tV st mb stic st mb st ic and P 1 P 6 2 where subscripts mb and ic refer to MB and IC domains respectively In the concept static macropore volume is not necessary always present But even in the absence of this volume the volumetric proportions are required to partition the dynamic volume over the domains Therefore the calculation of the volumetric proportions as a function of depth is independent of the magnitude of the dynamic macropore volume This calculation provides the blueprint of the macropore domains In order to visualize this blueprint it is more illustrative to show only the static macropore volume as is done in Figure 6 1 B Since the dynamic volume changes with time and depth depending on shrinkage characteristic and soil moisture status that may differ at each depth it would distort the image of the blueprint The volumetric proportion of each domain as a function of depth is described by analytical equations with four basic input parameters two depths cm Zan representing the bottom of the A horizon and Zi representing the bottom of the IC domain proportion Pico of the IC domain at soil surface and po
221. ge system connected to rapid drainage 1 NRLEVS 1 Threshold value for ponding cm on soil surface before overland flow into macropores starts PNDMXMP 0 0 t 0 0 10 05 El R If there is no information available to decide otherwise ThetCrMP could be taken at 90 100 0 4 GeomFac as 3 0 and ZnCrAr around 5 0 cm Measured shrinkage characteristics of seven clay profiles in the Netherlands as described by Bronswijk and Evers Vermeer 1990 are listed in Appendix 10 Yule and Ritchie 1980a 1980b described shrinkage characteristics of eight Texas Vertisols using small and large cores Garnier et al 1997 propose a simple evaporation experiment to determine simultaneously the moisture retention curve hydraulic conductivity function and shrinkage characteristic Measured shrinkage characteristics of four peat soil profiles in the Netherlands as described by Hendriks 2004 are listed in Appendix 11 6 3 2 2 Water flow The input parameters of the water flow concept are listed in Box 6 2 They are discussed below The sorptivity parameters can be obtained by fitting Eq 6 30 against measured values to derive a relationship between sorptivity and initial moisture content The advantage of measured sorptivities is that they may reflect the influence of water Alterra Report 1649 update02 145 repellent coatings on the surface of clay aggregates which often hamper infiltration into these aggregates Thoma et
222. groundwater flow and when an implicit handling of gbor in the iterative computation scheme is required The flux through the bottom boundary is defined by the difference of the hydraulic head z and the hydraulic head y cm of the regional groundwater outside the flow domain described by the model divided by a flow resistance c d dvor br deas o 2 18 C 4 Special cases Two special cases involve the option to define a seepage face at the lower boundary and to define free drainage The seepage face is meant to simulate moisture flow in a lysimeter which is composed of a combination the head controlled condition and the zero flux controlled condition ho lt 0 gt bot 0 O h z 2 19 hoyo FO gt dbo K S y z bot Oz The free drainage results from the assumption that the hydraulic head gradient equals the elevation head gradient thus so that the magnitude of qbo equals the hydraulic conductivity of the lowest compartment E 2 Oz 1 gt qy K 2 20 z bot Alterra Report 1649 update02 33 During frost conditions por will be modified according to Vor fr 2 dis 2 21 but can be reduced even to a lower value in case of the presence of frozen layers see Chapter 10 2 7 Numerical implementation Accurate numerical solution of Richards partial differential equation is difficult due to its hyperbolic nature the strong non linearity of the soil hydraulic functions and the rapid changing bou
223. gt ji R inq numnod 1 The presence of values for variables inqdra1 inqdra5 is determined by the variable nrlevs The value of nrlevs determines the number of drainage systems for which flux densities must be given Flux of drainage system of 1st order e g canal md Flux of drainage system of 2nd order e g ditch md Flux of drainage system of 3rd order e g trench md Flux of drainage system of 4th order e g tube drain md Flux of drainage system of 5th order e g rapid drainage md 260 0 0 00 gt P R ingdra 1 numnod 0 0 00 gt d R inqdra 2 numnod 0 0 co gt i R inqdra 3 numnod 0 0 co gt A R inqdra 4 numnod 0 0 co gt R inqdra 5 numnod Alterra Report 1649 update02 Appendix 15 Description of output files bfo and bun This annex describes the content of the output files with extension bfo and bun The content of both files is identical they only differ in format one file is binary and unformatted bun and the other file is ascii and formatted bfo Differences between the bfo bun and aun afo 0 are indicated with a vertical line next to the text Part of the content of this file is optional and indicated with grey shading of the corresponding rows The optional content is indiced with the switch SWOP see section File Options The temperature parameter Tsoil has a value of 99 9 when temperature processes were not simulated The snow parameters Ssnow Igsnow
224. h discharge relation for nonsteady state conditions Kraijenhoff van de Leur 1957 Wesseling and Wesseling 1984 such relation is not implemented These relations consider only one over all value for the storage coefficient and neglect the influence of the pressure head variations in space and time on the storativity If such phenomena are of interest for drainage flow simulations the reader is referred to 2D and 3D models as MODFLOW VSF Thoms et al 2006 SUTRA Voss and Provost 2002 FEMWATER Lin et al 1997 and HYDRUS Sim nek et al 2007 The drainage flux are incorporated in the numerical solution to the Richards equations see Chapter 2 by specifying it as a sink term The drainage relations presented in Section 4 3 are conceptualizations of 2D and 3D saturated groundwater flow to surface water systems and are based on the head difference between groundwater elevation and drainage level Assignment of drainage sink term values in the Richards equation involves a conceptualization of the 2D and 3D flow field which is briefly explained in chapter 4 4 Optionally to provide possibilities to compare the SWAP model with other 1D soil moisture models as HYDRUSID 72 Alterra Report 1649 update02 Sim nek et al 1998 the drain flux can be described as a vertical flow in the model which leaves the flow domain at the bottom It should be noticed that the calculation of drainage resistance should be attuned to the definition o
225. h reducing factors reduce or hamper growth and comprise biotic factors such as weeds pests and diseases and abiotoc factors such as pollutants and Al toxicity Crop protection aims at effective management of these growth factors In the actual production situation the productivity achieved is usually the results of a combination of growth limiting and reducing factors Van Ittersum et al 2003 Alterra Report 1649 update02 149 The model WOFOST Van Keulen and Wolf 1986 Spitters et al 1989 Supit et al 1994 Hijmans et al 1994 Boogaard et al 1998 has been developed to simulate potential production and limited production due to water and or salinity stress Figure 7 2 shows the processes and relations incorporated in WOFOST The radiation energy absorbed by the canopy is a function of incoming radiation and crop leaf area Using the absorbed radiation and taking into account photosynthetic leaf characteristics the potential gross photosynthesis is calculated The latter is reduced due to water and or salinity stress as quantified by the relative transpiration and yields the actual gross photosynthesis Radiation E t Light interception Leaf area Potential photosynthesis Important Eye feedback Actual rud photosynthesis increase Partitioning alive Stems Storage organs Leaves alive alive alive Death Figure 7 2 Overview of crop growth processes incorporated in WOFOST Part of the
226. haracteristics In SWAP we assume the atmospheric conditions to be external conditions which are representative for the area for which the simulations are performed Starting point in the calculations is the determination of the potential evapotranspiration of different uniform surfaces The model offers two methods to calculate this potential evapotranspiration see Fig 3 3 the Penman Monteith method and the reference evapotranspiration method The last method may be combined with the use of crop factors Input of basic meteorological data _ Input of refererence evapotranspiration Apply Penman Monteith with reference crop data and crop factor Mr Apply Penman Monteith with actual crop data Apply crop factor Evapotranspiration of dry and wet uniform canopy and of wet soil Divide over soil and crop using either leaf area index or soil cover interception Potential transpiration T Potential soil evaporation E Water stress Reduce to maximum soil water flux Salinity stress If selected in addition reduce with empirical Soil evaporation method Figure 3 3 Method used in SWAP to derive actual transpiration and soil evaporation of partly covered soils from basic input data 56 Alterra Report 1649 update02 3 3 1 Penman Monteith method Using similar physics as Penman 1948 Monteith 1965 derived an equation that describes the evapotransp
227. he subsoil is less than in the situation with drainage the groundwater table becomes concave instead of convex Especially if the conductivity is larger in the subsoil above the drainage base than in the deeper subsoil Yint will be substantially higher than Yarane To deal with such cases the model has the option for using sub irrigation resistances that differ from the ones for drainage e g Js 3 2 yan in Figure 4 5 When calibrating SWAP against measured groundwater levels it should be realised that SWAP calculates a field average groundwater level Measured groundwater levels represent a point of the convex or concave shaped groundwater table depending on the position of the piezometer in the field in relation to the drains Piezometers in the middle of two parallel drains will display stronger fluctuations of the groundwater level than the field average level Calibrating SWAP against these strong fluctuating groundwater levels will result in a calibrated model that deviates strongly from groundwater behavior at the field scale To overcome this inaccuracy it is advised to measure groundwater level movement in a row of piezometers perpendicular to the drain starting at a close 0 5 m distance of the drain including the drain level From these measurements a shape factor can be calculated that represents the relationship between the measured convex or concave groundwater table and the field average This shape factor can be used to convert m
228. he theorie description in Section 7 3 in combination with the descriptions in the input file will be sufficient to guide the model user However a few additional remarks should be made here In part 4 a choice should be made between input of crop factors or crop heights Crop factors should be used when ET values are used as input or when the Penman Monteith method is used to calculate ET ef Crop heights should be specified if the potential evapotranspiration fluxes are derived directly for the actual crop see Table 3 2 In that case also the reflection coefficient and stomatal resistance of the crop should be defined In part 8 the user should specify the partitioning factors as function of crop development stage As explained in Section 7 3 7 WOFOST first divides the gross dry matter among roots and shoots leafs stems and storage organs together using the partitioning factor for roots Next WOFOST divides the gross dry matter directed to the shoots among leafs stems and storage organs using the partitioning factors for these plant organs At any development stage the sum Ejeart amp Estem Sstor must equal one The theoretical background of Parts 10 12 Crop water use Salt stress and Interception applies to both the simple and detailed crop model and has been explained in Chapter 3 Preferential root water uptake may be described using an input option swroottyp when left out a default value swroottype 1 is assumed Alterra Report
229. he year R is calculated with R Ssa Lo sin sin 5 cos q cos 8 sin 0 Alterra Report 1649 update02 227 where G is the amount of solar radiation striking a surface perpendicular to the sun s rays at the top of the Earth s atmosphere called the solar constant J m d d is the inverse relative distance Earth Sun is the sunset hour angle rad is the latitude rad and 6 1s the solar declination rad The inverse relative distance Earth Sun and the solar declination are given by 3 512003900 E 365 5 0 409 sin 2 7 1 39 365 where J is the number of the day in the year 1 365 or 366 starting January 1 The sunset hour angle expresses the day length and is given by o arccos tan tan 8 Aerodynamic term Latent heat of vaporization A J g depends on the air temperature T C Harrison 1963 A 2501 2 3617 Saturation vapour pressure e 4 kPa also can be calculated from air temperature Tetens 1930 17 27 T T es air e 0 611 el The slope of the vapour pressure curve A kPa C is calculated as Murray 1967 4098 e O T 42373y The psychrometric constant Yair kPa C follows from Brunt 1952 p R 1 63 Y air x with Pair the atmospheric pressure kPa at elevation zo m which is calculated from Burman et al 1987 5 256 T 0 0065 ES 101 4 air K Zo l air K Employing the ideal gas law the atmospheric
230. head HBOT5 1 d10 1000 cm R DATES HBOT5 maximum MABBC records 01 jan 1980 954 0 30 jun 1980 1105 0 23 dec 1980 70 0 End of table KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KK KKK KKK KKK KAKA KKK KKK KKK KKK KKK KKK RRA RR RARA Alterra Report 1649 update02 51 52 Alterra Report 1649 update02 3 Evapotranspiration and rainfall interception 3 1 Introduction In contrast to rainfall measurement of reliable evapotranspiration fluxes is far from trivial and strongly varies with the local hydrological conditions Therefore SWAP simulates evapotranspiration fluxes from basic weather data or reference crop evapotranspiration data as discussed in this chapter Rainfall and irrigation minus the sum of transpiration evaporation and interception determine the amount of infiltration in the soil Fig 3 1 and groundwater fluxes In general the sums of rainfall irrigation and transpiration evaporation interception are large compared to their difference which equals the infiltration This means that relative errors in these sums will magnify in relative errors in the infiltration and groundwater fluxes Therefore reliable soil water and groundwater fluxes require accurate simulation of evapotranspiration and interception fluxes Rainfall In general the daily Interception Transpiration water fluxes passing Irrigation Sy Surface runon through a canopy are large compared to the
231. her than a hydrological conductivity of the soil The air entry value option should be switched off thus he 0 see Sections 2 3 and 2 8 1 Time step It is recommended to take 10 or 10 d for the minimum time step and 10 d or less for the maximum time step Output Macropore simulation provides the option of output of a macropore water balance in the file BMA For this option switch SWBMA should have value 1 see Box 1 4 Automatically generated are output files MacroGeom csv and SoilShrinkChar csv which contain a tabular representation of the macropore geometry and the shrinkage characteristics as computed by the model on basis of the user s input 6 3 2 Macropore input parameters The typical macropore input parameters are discussed in this Section They are listed in Boxes 6 1 Section 6 3 2 1 Macropore geometry and 6 2 Section 6 3 2 2 Water flow The presented values concern a field experiment on water bromide tracer and pesticide transport in a tile drained field on clay soil Scorza J nior et al 2004 The field was located in the riverine area in the central part of the Netherlands The soil concerned light to moderate clay 30 55 mass clay and the crop was winter wheat At 320 cm depth the clay soil was underlain by a coarse sand aquifer The presented values are the first results of a calibration of SWAP against the dataset 6 3 2 1 Macropore geometry The input parameters of the macropore geometry are listed
232. iable is used to describe these factors Note that in Grass fixed defined in input file partitioning factors are applied Figure B16 5 Alterra Report 1649 update02 269 Dry matter increase stems 0 4 Total above ground dry matter Increas 0 7 Total dry matter increase AO 1 increase leaves 0 6 Dry matter increase roots 0 3 Figure B16 5 Partitioning factors applied in the grassland module Carbon balance check The actual gross CO assimilation rate has to be identical to the amount of structural plant material produced plus the amounts used for maintenance respiration and conversion The carbon balance has to be zero R R ar R e pc a PCy Pea 0 R where Rg Growth respiration rate kg ha d Ra Actual daily CHO assimilation rate kg ha d Rar Maintenance respiration rate kg ha d pci Partitioning factor of organ i kg kg 1 Leaves lv stems st roots rt It is assumed that maintenance respiration cannot exceed the actual gross assimilation rate However in case the daily CH O assimilation rate comes close to zero the maintenance respiration rate and the growth respiration rate also become small and a situation may occur that the numerator of the above mentioned equation becomes very small and negative and the crop simulation should be stopped Introducing a division by Rg in the carbon check will identify such an event
233. ical approach to Eq 2 3 yielding a steady state solution requires an implicit treatment of the hydraulic conductivity This implies the use of the derivative of the hydraulic conductivity to the pressure heads Expressions are given in 0 2 3 Modification for near saturation conditions A modification to the Mualem Van Genuchten function Schaap and Van Genuchten 2006 has been implemented in SWAP The modification is based on the introduction of a small minimum capillary height h causing a minor shift in the retention curve Vogel et al 2001 We follow Ippisch et al 2006 by defining the relative water content as A aar h lt h S Se 2 9 1 h gt h where S is the relative saturation at the cut off point h in the classical Van Genuchten model given by E kaa 2 10 The hydraulic conductivity is then given by 28 Alterra Report 1649 update02 1 1 S S m K sat s l lt lt S 1 1 d S n Sor K sat Se z1 This model reduces to Eq 2 6 for he 0 We refer to Vogel et al 2001 Schaap and Van Genuchten 2006 and Ippisch et al 2006 for a detailed discussion of the above equations They showed that the modification affects the shape of the retention curve only minimally relative to the original function However the effects on the unsaturated hydraulic conductivity of fine textured soils can be significant To prevent for numerical instabilities of the solution scheme the soil moisture
234. ig 2 2A Based on its wetting and drying history at a certain time and depth the soil shows an actual water content 0 at the soil water pressure head hac The valid drying scanning curve should pass through the point Q hac and approach the main drying curve at smaller water contents A B E Main wetting curve awet N Gres Asat x 1 8 Main drying dd Gary M Gress g ix Main wetting curve awet 1 Ares Osat c Asat e p g Drying scanning curve Ary N Aes o Main drying curve ay n Gress o sat a a i i 9 sat 2 o f amp i Oma a B fe A A h 5 e Current status c c gt E Current status o 77 Wetting scanning curve wet M Gres gt Qa 0 0 i gt 0 Gres Gact Isat Asat Water content q 0 Gres Ges Qact Asat gt A Water content q Figure 2 2 A Linear scaling of the main drying water retention curve in order to derive a drying scanning curve B Linear scaling of the main wetting water retention curve in order to derive a drying wetting curve 30 Alterra Report 1649 update02 We may define Oma as the water content of the main drying curve at hac and Osat as the saturated water content of the drying scanning curve Linear scaling of the main drying curve with respect to the vertical axis O 0 4 gives Fig 2 2A 9 0 0 0 n 0 0 sat res _ act res gt 0 0 ES 0 Li act res 2 12 9 gt B Oa T O
235. iginating from temperate regions Teg 0 at Tar 0 3 C while for species of subtropical and tropical origins Teg O at Tair 9 14 C Angus et al 1981 In a table the WOFOST user should specify the relation between Tere and Tair An example is given in Fig 7 3 Within a species cultivars may vary substantially in their temperature requirements Therefore the temperature sum is characteristic for each cultivar and is input to WOFOST Accordingly the development stage D is calculated as m Dj D 7 3 sum i where superscript j is the day number and Ti is the temperature sum required to complete either the vegetative or the reproductive stage Alterra Report 1649 update02 151 For some species or cultivars during the vegetative stage the effect of day length should be taken into account Approaches that describe such effects quantitatively are given amongst others by Weir et al 1984 Hadley et al 1984 and Reinink et al 1986 In the model a reduction factor for the development rate as function of day length fiday is computed L day m Lay L L oday zi cday fua with DET ac 7 4 with Lay the actual day length d Loday the shortest day length for any development d and Loday the minimum day length for optimum development d Note that in modern cultivars photosensitivity is much less pronounced than in traditional cultivars and that for the purpose of modelling the day length in
236. ill read times according to the following format 05 jan 2005 14 30 00 00 denotes January 5 2005 at 2 30 PM If only dates and no times are specified as in Box 2 2 SWAP will assume time 0 00 The main advantage of this boundary condition is the easy recording of the phreatic surface in case of a present groundwater table A drawback is that at shallow groundwater tables the simulated phreatic surface fluctuations are very sensitive to the soil hydraulic functions and the top boundary condition If the top and bottom boundary condition not properly match or the soil hydraulic functions deviate from reality strong fluctuations of water fluxes across the lower boundary may result Especially when the output of SWAP is used as input in water quality calculations it is recommended to use another type of lower boundary condition The option of prescribed groundwater levels is disabled for macropore flow simulations 2 Prescribed bottom flux In this case the bottom flux qoo might be given as function of time with linear interpolation between the data pairs or as a sine function Box 2 2 This option has a similar disadvantage as the previously described option with the prescribed groundwater level at the field scale When a mismatch occurs between boundary conditions e g drainage leakage to deep aquifer exceeds net precipitation excess the result may be a continuously declining or increasing groundwater level In particular in cases where the
237. in Yer e int Parin Fout Bladwijzer niet gedefinieerd 4 17 vtop vbot with Zin the level of the transition cm between the upper and lower soil layer and Kytop and Kyo the vertical saturated hydraulic conductivity cm d of the upper and lower soil layer respectively The horizontal resistance is calculated as fa Me Da hbot bot Fout Bladwijzer niet gedefinieerd 4 18 with Dio the depth of the contributing layer below the drain level cm which is calculated as the minimum of arain Zimp and 1 4 Laraine The radial resistance is calculated using Lirain Dy 4 19 Y rad T y K sbot K wot Urain with Uarain the wet perimeter cm of the drain Case 5 Heterogeneous soil profile drain in top layer Again the approach of Ernst 1956 with later extensions for the entrance resistance is applied The resistances are calculated as Yver Powl Parain 4 20 K vtop pom Y hor 8K htop Prop ps 8K not Poot 4 21 Larrain C drain Zint Yrad h 8 drain SO TA Ko K vot drain 4 22 Alterra Report 1649 update02 77 with Diop equal to 94 Zint and Zarain is the drain geometry factor to be specified in the input The value of Zaan in Eq 4 21 depends on the ratio of the hydraulic conductivity of the bottom Kyo and the top Ky layer Ernst 1962 distinguished the following situations KhboKhtop lt 0 1 the bottom layer can be considered impervious and the case is reduc
238. in Box 6 1 They are discussed below 138 Alterra Report 1649 update02 F 0 0 0 5 1 0 ZAh 80 Zic 100 Figure 6 6 Fraction of functional IC macropores F as a function of depth is described by a power law function with power m m 1 describes a linear decline while m lt 1 represents shallow IC systems and m 1 deep IC systems Illustration of the effect of parameters on macropore geometry Curve F in Figure 6 6 illustrates the effect of shape factor m in combination with other macropore geometry parameters on the fraction of IC macropores that is functional at depth z in case that Rzam 0 For m 0 1 0 4 1 0 2 5 and 10 respectively depth z at which fraction F of functional IC macropores has declined to 0 5 equals 25 1 35 6 55 70 5 and 81 cm respectively In general m lt 1 describes shallow IC systems while m gt 1 represents deep IC systems m 1 describes an intermediate system with linear decline of functional IC macropores with depth Optionally two more shape parameters can be used to describe IC macropores in more detail The symmetry point parameter SPOINT allows for standing m 1 and laying m gt 1 S shaped F curves In combination with switch SWPOWM turned on these curves can be modified into double convex m 1 or double concave m gt 1 curves see Appendix 3 for examples This allows for a functional description of macropore vo
239. including the main wetting the main drying and the scanning curves especially in the dry range For instance a generally applied soil hydraulic data base in The Netherlands known as the Staring series W sten et al 1994 contains only O h data of the main drying curve Nevertheless it is obvious that the simulation of infiltration events with the main drying curve can be inaccurate The scaling method of Scott et al 1983 who derived scanning curves by rescaling the main wetting or the main drying curve to the actual water content has been implemented into SWAP The main drying and main wetting curve are described analytically with the Mualem van Genuchten parameters a n Ores Osa Ksa and A Some of the parameters describing the main wetting and main drying curve are related We assume 0 and Osa to be equal for both curves Usually the K 0 function shows only minor hysteresis effects which can be achieved by choosing for the main wetting and main drying curve a common value for n Ultimately the two curves only differ in the parameter a as depicted in Fig 2 1 The scanning curves are derived by linear scaling of either the main wetting or main drying curve such that the scanning curve includes the current 0 combination and approaches the main wetting curve in case of a wetting scanning curve and the main drying curve in case of a drying scanning curve The scaling principle in case of a drying scanning curve is depicted in F
240. inearization 78 Alterra Report 1649 update02 1 eet linearization of gwl non linear relation data pair to be specified in the input Fig 4 3 Linearization of a non linear drainage flux relation 4 3 3 General aspects of regional scale drainage Schematization The groundwater surface water system is described at the scale of a horizontal sub region A network of drainage devices consists of a hierarchical system of different order and incision depth but only a single representative groundwater level is simulated for a sub region which is stretched over a scale that in reality involves a variety of groundwater levels In the following due consideration will be given to the schematization of the surface water system the simulation of drainage sub irrigation fluxes and the handling of an open surface water level The regional surface water system consists of a hierarchical system of different order drainage devices Fig 4 4 each with its own with bed level bed width side slope and spacing conveyance capacity The drainage devices can be connected to each other in different ways In the man made the ditches of the network systems act as perennial streams connected to larger canals with a nearly equal surface water level In the alluvial sandy areas of the Netherlands the smaller streams may have intermittent character which only discharge water in periods with rainwater excess Alterra Report 1649 update02 79 Se
241. inkage characteristic data e Tables with shrinkage characteristic data for peat soils e List of subroutines e List of fixed ranges of array lengths e Listing of formatted and unformatted binary output files e Description of WOFOST crop growth routine for grassland 26 Alterra Report 1649 update02 2 Soil water flow 2 1 Basic equations Gradients of the soil water potential induce soil water movement Darcy s equation is commonly used to quantify these soil water fluxes For one dimensional vertical flow Darcy s equation can be written as O h z K h q h d 2 1 where g is soil water flux density positive upward cm d K h is hydraulic conductivity cm d h is soil water pressure head cm and z is the vertical coordinate cm taken positively upward Water balance considerations of an infinitely small soil volume result in the continuity equation for soil water 00 Ot S h 40 S 00 22 where is volumetric water content cm cm t is time d S h is soil water extraction rate by plant roots cm cm d S h is the extraction rate by drain discharge in the saturated zone d and 5 A is the exchange rate with macro pores d Combination of Eqs 2 1 and 2 2 provides the general water flow equation in variably saturated soils known as the Richards equation af Oz 2 at Oz S h S h S j A 2 3 SWAP applies Richards equation integrally for the unsat
242. input data are insufficient Section 7 2 provides a description of the simple module In the footsteps of De Wit and co workers De Wit et al 1978 Goudriaan 1977 Penning de Vries and Van Laar 1982 in the 1980s a wide range of scientists in Wageningen became involved in the development and application of crop growth models The generic crop model SUCROS for the potential production situation was developed Spitters et al 1989 SUCROS formed the basis of a range of Wageningen crop models as reviewed by Bouman et al 1996 and Van Ittersum et al 2003 One of the developed models is the WOFOST model which simulates in detail photosynthesis and crop development taking into account growth reductions due to water and or salt stress WOFOST has been implemented in SWAP and is described in Section 7 3 The detailed module for grass is a modified version of WOFOST The only species occuring in the sward is supposed to be perennial ryegrass Lolium perenne L The sward is regular mowed and remains vegetative No grazing takes place and the grassland is permanent The settings for regrowth after grass cutting have a large effect on the LAI development and the application of this module requires expert judgement For more information of this module we refer to the SWAP source code subroutine GRASS 7 2 Simple crop module The simple crop growth model represents a green canopy that intercepts precipitation transpires water vapour and shades
243. ion rates for uniform surfaces Uniform surface Input ET ves Input basic weather data use PM Reference grass Actual crop Wet canopy ET wo Ko ET veg ET yo ke ET wo grass ET wo Dry canopy ET 9 ke ET vor ET vo ke ET p0 grass ET o Bare soil Use soil factor Epo Koi ET ror Epo Ksoit ETyo grass Epo Koi ET po No soil factor Epo ET ree Epo Epo 58 Alterra Report 1649 update02 3 3 2 Reference evapotranspiration and crop factors Application of the Penman Monteith equation requires daily values of air temperature net radiation wind speed and air humidity which data might not be available Also in some studies other methods than Penman Monteith might be more appropriate For instance in The Netherlands the Makkink equation is widely used Makkink 1957 Feddes 1987 Therefore SWAP allows the use of a reference evapotranspiration rate ET cm d see Fig 3 3 In that case the potential evapotranspiration rate for the dry canopy ETyo is calculated by ET k ET ref 2 59 where k is the so called crop factor which depends on the crop type and the method employed to obtain ET ef In a similar way the potential evapotranspiration rate for the wet canopy ETyo is derived ET k ET 2 60 The evaporation rate of a wet bare soil can be derived with a soil factor K oii Ebo a kou ET 2 61 Without soil factor Epo is set equal to ETef Table 3 2 provides an overview of the SWAP options when ET er and crop f
244. iration from a dry extensive horizontally uniform vegetated surface which is optimally supplied with water This equation is known as the Penman Monteith equation Jensen et al 1990 analyzed the performance of 20 different evapotranspiration formula against lysimeter data for 11 stations around the world under different climatic conditions The Penman Monteith formula ranked as the best for all climatic conditions Therefore this equation has become an international standard for calculation of potential evapotranspiration Allen et al 1998 and is applied by SWAP For a closed canopy with insignificant evaporation from the soil the Penman Monteith equation can be written as Monteith 1965 1981 air Coat ze a A R G Dip A A r ET y air 2 58 P r A Y air r air where ET is the transpiration rate of the canopy mm d A is the slope of the vapour pressure curve kPa Sce Aw is the latent heat of vaporization J kg R is the net radiation flux at the canopy surface J m d G is the soil heat flux J m d pi accounts for unit conversion 286400 s d Pair is the air density kg m Cair is the heat capacity of moist air J kg eget esat 1S the saturation vapour pressure kPa e is the actual vapour pressure kPa Yair is the psychrometric constant kPa oC Terop 18 the crop resistance s m and r4 is the aerodynamic resistance s m The FAO has proposed a clearly defined and
245. isture content in the saturated paste extract is about twice of that at field capacity and about four times that at wilting point The factor fis independent of the soil type for which simulations are performed It rather characterizes the experimental conditions of the salt tolerance experiments used for deriving the Maas Hoffman relationship A default value of 2 is recommended for f For optimal flexibility and to enable downward compatibility the factor f is an input parameter for each soil horizon Some examples of coefficients are given in Table 8 1 Table 8 1 Some examples of coefficients for the relation between ECsat and solutes Case Solute a b f Source 1 TDS 1 492 1 0 1 0 FAO 48 2 Chloride 21 7 0 763 1 0 CT Vademecum 1988 SWAP supports two methods to account for the residence time of solutes in the saturated zone The first one by proper distribution of the lateral drainage flux over the saturated compartments Chapter 4 In that case we may set SWBR 0 and specify the solute concentration in the groundwater as boundary condition for upward flow Box 8 1 Part 7 The second method has been described in this chapter and views the saturated zone as one mixed reservoir Section 8 5 In that case we should set SWBR 0 and provide the effective transport properties of the saturated zone Box 8 1 Part 7 Box 8 1 Information on solute transport in main file SWP ES Part 1 Specify whether simulation includes solute tra
246. isture loss equals air volume increase of the aggregates Rigid soils like sands only show this stage A fourth shrinkage stage that precedes normal shrinkage may be recognized structural shrinkage When saturated soils dry large water filled pores may be emptied As a result aggregates can get a somewhat denser packing Overall the volume changes in this stage are negligible but water losses can be considerable In SWAP structural shrinkage is explicitly accounted for in the form of the static macropores e g structural shrinkage cracks The first three real shrinkage stages are computed as a function of moisture content with the equation of Kim 1992 9 1 0 S e ay exp p 9 y 9 for 0 lt 9 lt 9 where 9 6 18 with a cm cm equals ey the void ratio at 9 0 Bx and yx are dimensionless fitting parameters and 9 is void ratio at saturation Using Eq 6 18 e may become smaller than eo in which case the model sets e to eo zero shrinkage Shrinkage characteristic of peat and peaty soils According to Hendriks 2004 for peat soils three shrinkage stages can be distinguished as well Fig 6 4 B 1 Near normal shrinkage volume reduction equals nearly moisture loss little air enters the pores and the peat matrix remains close to saturation 2 Subnormal shrinkage upon drying moisture loss exceeds volume reduction air enters the relatively large pores while the small pores in the organic fibres that form the sk
247. ition SWDC 1 specify GAMPAR 0 0 Factor reduction decomposition due to temperature 0 0 5 C R RTHETA 0 3 Minimum water content for potential decomposition 0 0 4 cm3 cm3 R BEXP 0 7 Exponent in reduction decomposition due to dryness 0 2 R List the reduction of pot decomposition for each soil type 0 1 R ISOILLAY7 FDEPTH maximum MAHO records 1 1 00 2 0 65 End of table KOK KK KK kk ck KKK KK KKK KKK KK KKK KK KKK KKK KK KK KKK KKK KKK KKK KKK KKK KKK KKK KKK k ck k ck k ck k ck k ck k ck ck KKK AK KOK KK KK KK KKK KK KKK KK KK KK KK KKK KKK KKK KKK KKK KKK KKK k ck k ck k ck k ck k ck k ck k ck k ck k ck k ck k ck kck k ck k ck KK EK Part 7 Solute residence in the saturated zone SWBR 0 Switch consider mixed reservoir of saturated zone Y 1 N 0 Without mixed reservoir SWBR 0 specify CDRAIN 0 1 solute concentration in groundwater 0 100 mg cm3 R In case of mixed reservoir SWBR 1 specify DAQUIF 110 0 Thickness saturated part of aquifer 0 10000 cm R POROS 0 4 Porosity of aquifer 0 0 6 R KFSAT 0 2 Linear adsorption coefficient in aquifer 0 100 cm3 mg R DECSAT 1 0 Decomposition rate in aquifer 0 10 d R CDRAINI 0 2 Initial solute concentration in groundwater 0 100 mg cm3 R KOK KKK KKK KKK KKK KKK KKK KK KK KKK KKK KK KKK kckckck ck ck kck k ck k ck k ck k ck k ck k ck k ck k ck k ck k ck k ck k ck k ck kcko
248. itude cm and period d of the hydraulic head sinus wave in the semi confined aquifer and is a time d X at which aquif reaches its maximum The SWAP model comprises option for the implicit treatment of pressure head in lowest compartment by substitution of by h z and considering the vertical avg resistance within the model domain only between the lowest node and the lower boundary Another option involves the possibility to specify a groundwater flux additional to q to facilitate the coupling of the SWAP model to a regional groundwater model 48 Alterra Report 1649 update02 4 Calculate bottom flux as a function of groundwater level The relation between q and Pay can be given as an exponential relation or as a table Box 2 2 The exponential relationship is formulated as Qa 2 50 diot A abot explo where dgbot cm d and babor cm are empirical coefficients This kind of exponential relationships was derived for deep sandy areas in The Eastern part of The Netherlands Massop and De Wit 1994 Special care should be taken with respect to the distinction between drainage and bottom boundary flux The relationship that may be used to compute drainage Chapter 4 can conflict with the relation for quo It may then be appropriate to apply another type of boundary condition When the relation between qbo and ay is given as a table gp results from an interpolation between groundwater le
249. kck Alterra Report 1649 update02 183 184 Alterra Report 1649 update02 9 Soil temperature Soil temperature affects many physical chemical and biological processes in the top soil for instance the surface energy balance soil hydraulic properties decomposition rate of solutes and growth rate of roots Currently SWAP uses the soil temperatures only to adjust the solute decomposition rate but other temperature relations may readily be included SWAP calculates the soil temperatures either analytically or numerically In the following sections the heat flow equations and the applied analytical and numerical solutions are discussed 9 1 Temperature conductance equation If we consider heat transport only by convection the one dimensional soil heat flux nea J cm d can be described as OT LC am 9 1 heat Oz dheat s where Aneat 18 the thermal conductivity J ene C d and T is the soil temperature C Conservation of energy results in oT E e 2z 9 2 heat t Oz where Cheat is the soil heat capacity J cm oct Combination of Eq 9 1 and 9 2 yields the differential equation for soil heat flow oT 0 Z gole ec 9 3 heat a t Oz In general in the liquid phase radiation and convection will also transport heat As the contribution of radiation and convection to soil heat transport in general is small compared to conductance SWAP only considers conductance In the vapour phase
250. kkkkkkkkkkkkkkkkkkkkkkk kkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkk Part 6 Maintenance respiration Q10 2 0000 Rel increase in respiration rate with temperature 0 5 10 C R RML 0 0300 Rel maintenance respiration rate of leaves 0 1 kgCH20 kg d R RMR 0 0150 Rel maintenance respiration rate of roots 0 1 kgCH20 kg d R RMS 0 0150 Rel maintenance respiration rate of stems 0 1 kgCH20 kg d R List reduction factor of senescence R as function of daynumber 1 366 d R DNR RFSE maximum 15 records RFSETB 1 00 1 0000 366 00 1 0000 End of table FI III III ICI III III III ISIC III III III III III III ICI RII RI a ak FI ok kk Kok kk kk I I I II OOOO I IR I IR IO I OR IO RAR Part 7 Partitioning List fraction of total dry matter increase partitioned to the roots kg kg R as function of daynr 1 366 d R DNR FR maximum 15 records FRTB 1 00 0 3000 366 00 0 3000 End of table List fraction of total above ground dry matter incr part to the leaves kg kg R as function of daynumber 1 366 d R DNR FL maximum 15 records FLTB 1 00 0 6000 366 00 0 6000 End of table List fraction of total above ground dry matter incr part to the stems kg kg R as function of daynumber 1 366 d R DNR FS maximum 15 records FSTB 1 00 0 4000 366 00 0 4000 End of table ek HE E E III ICI KOC A
251. kkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkk Part 4 Assimilation KDIF 0 60 Extinction coefficient for diffuse visible light 0 2 R KDIR 0 75 Extinction coefficient for direct visible light 0 2 R EFF 0 50 Light use efficiency of single leaf 0 10 kg ha hr Jm2s R List max CO2 assimilation rate kg ha hr R as a function of daynumber 1 366 d R je DNR AMAX maximum 15 records AMAXTB 1 00 0 00 50 00 10 00 60 00 20 00 95 00 40 00 200 00 35 00 275 00 20 00 300 00 5 00 366 00 0 00 End of table List reduction factor of AMAX R as function of average day temp 10 50 C R TAVD TMPF maximum 15 records TMPFTB 0 00 0 00 5 00 0 70 15 00 1 00 25 00 1 00 40 00 0 00 End of table List reduction factor of AMAX R as function of minimum day temp 10 50 C R TMNR TMNF maximum 15 records TMNFTB 0 00 0 00 Alterra Report 1649 update02 4 00 1 00 End of table FI III III ICI III III III III III III III III III ICI RII Ra ak FI I I I I ORO I II I III I IO I IR IO RR IO RR IO A ee Part 5 Conversion of assimilates into biomass CVL 0 6850 Efficiency of conversion into leaves 0 1 kg kg R CVR 0 6940 Efficiency of conversion into roots 0 1 kg kg R CVS 0 6620 Efficiency of conversion into stems 0 1 kg kg R kkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkk
252. l surface Van Dam and Feddes 2000 2 7 Numerical solution The discrete form of the Richard s equation is solved iteratively using the pressure heads as state variables Taylor expansion of the new moisture fraction at a new iteration level with respect to the moisture fraction at the preceding iteration step is defined by j l p 00 1 p 1 1 1 j 1 j 1 p 1 1 0 p h 0 Ph PY h p hj P Em T hj 1 2 27 Ignoring the second and higher order terms of the Taylor series yields an expression which can substitute the moisture fraction variable at the new time level The first order derivate of the moisture fraction to the pressure head is identical to the water j Lp capacity C In fact the basis first order approximation of the new moisture Alterra Report 1649 update02 35 fraction of the method proposed by Celia et al 1990 complies with the assumptions made in the Newton Raphson iteration procedure An improvement to this method is made by defining F based on the closure term of the water balance as a function of hae pito E pito i F DG gigi gites Pii _KiteKe E AUT i i Vo i Ati Ya Az _ Az E 2 28 Ke hj P hj 7 j K K j K p j 1 KID e KJ Ae SL HAZ SS i HAZ Shi i 2 i 2 Ya Az AzZ41 where the superscript p 1 points to the solution of iteration round p This discrete form of the Richards equation allows for a straightforward evaluation of the storage ter
253. l conductivities of snow and soil Granberg et al 1999 EN T aT l a T SS 10 54 where Alterra Report 1649 update02 195 de m OIE T 10 50 nAz snow with A J cm C d and Az cm are thermal conductivity and thickness of the first soil compartment Thermal conductivity of the snowpack Asnow J em C d depends on density Psnow Kg cm of the snowpack Granberg et al 1999 dre Ae 10 6 Snow snow snow where Know is a thermal conductivity parameter for snow 24 710 8 J cm kg Con d For Psnow the average value of 17010 kg cm is taken Granberg et al 1999 so that Asnow equals 71 4 J em C d 15 of Awater Thickness of the snowpack AZsnow cm is calculated from storage and density of snow and density of water 1000 10 kg cm 1 AZ now P water Sai n SNOW 10 7 P snow 10 2 Frost If the option for frost is switched on SWAP simulates freezing of soil water when soil temperature drops below a threshold value Tg C Soil ice has a markedly impact on water flow and storage in the soil To express this impact in simulations where soil ice occurs some transport parameters are adjusted This is achieved by using a factor fr z which introduces a correction when soil temperatures are below Tg at depth z This correction factor is assumed to be linear related to the fraction of soil ice ficelz at depth z fr 1 fu 10 8 where ficelz is the
254. lation of heat transport Y 1 N 0 KKK KKK KK KK KA KA KK KK KK KK KK KK KK KK KKK KK KKK KKK KKK ck k ck k ck k ck k ck k ck k ck k ck k ck k ck k ck k ck k ck kckokck KKK KKK KKK KKK KK KA KA KA KK KK KK KK ck ck ck ck kckckckckckckckckckckckckckckck kckckck k ck k ck k ck k ck k ck k ck k ck k ck k ck k ck kck k ck AKA KEK Part 2 Heat flow calculation method SWCALT 2 Switch for method 1 analytical method 2 numerical method KKK KK ck ck ck kk KA KA KK KA KA KA KA A KK ckckckckckckckckckckckckckckckckckckckck kckck ck k ck k ck k ck k ck k ck k ck k ck k ck k ck k ck k ck KKK KEK EK KK KK KKK KK KKK KA KK KK KK KK KK KK KK KKK KKK KKK KKK KKK KKK k ck k ck k ck k ck k ck k ck k ck k ck k ck k ck k ck k ck KKK KEK Part 3 Analytical method If SWCALT 1 specify the following heat parameters TAMPLI 10 0 Amplitude of annual temperature wave at soil surface 0 50 C R TMEAN 15 0 Mean annual temperature at soil surface 5 30 C R TIMREF 90 0 Time in the year with top of sine temperature wave 1 366 d R DDAMP 50 0 Damping depth of temperature wave in soil 0 500 cm R KKK KKK KKK KKK KKK KK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KK KKK kck kck kck kckck ck k KAKA ck k ck ck ck k ck ck KAKA KKK KKK KKK KKK KKK KKK KKK KK KK KKK KKK KKK KKK KKK KK KKK KKK KKK KK kck kck kck kck ck ckck ck KKK KKK ck ck k KKK KKK KKK AK Part 4 Numerical method If SWCALT 2 specify the following heat parame
255. layer are defined which describe the water retention and hydraulic conductivity functions Caution should be exercised with the use of the air entry value concept he The effects of even a small value of lhe on the unsaturated hydraulic conductivity of fine textured soils can be significant The introduction of the air entry value concept requires the re fitting of the other parameters of the classical Mulaem Van Genuchten model on the original experimental data In part 6 the inclusion of hysteresis in the water retention function can be selected In case of hysteresis the parameter ALFAW of the wetting curve part 5 should be properly defined Whether the initial condition is wetting or drying may have a large effect on the water balance In general the simulations are not sensitive to the minimum head difference to change from wetting to drying scanning curves and vice versa TAU The parameter TAU is usually set equal to 0 2 cm In part 11 various parameters are defined that may affect the numerical solution of the Richards equation In general the default values will garantuee an accurate numerical solution of the highly non linear Richards equation In extreme cases different input values might be required The user should specify a minimum and a maximum time step Afmin and Afg4 d SWAP will determine the optimal time step which minimizes the computational effort of a simulation while the numerical solution still meets the converg
256. ld be defined for each management period 5 1 2 2 Soil moisture controlled weir management This model option assumes the target level of a weir to be controlled by one or more soil moisture state variables The so called water management scheme defines the setting of the water level fur tar aimed for in relation to a soil moisture state variable The target level is defined as a combinational function of three state variables related to soil moisture 1 the average groundwater level 9 Lower target levels a higher groundwater levels may prevent waterlogging and can contribute to minimize crop yield reduction 2 the soil water pressure head h cm at a certain depth A soil water pressure value appears to be a better indicator for water logging in nature reserves than a groundwater level criterium 3 the capacity of the unsaturated soil profile to store water Vuns cm This state variable is an indicator for the possibility of buffering extreme rainfall events Maintaining a certain minimum amount of storage reduces the risk of flooding and subsequent discharge peaks During the simulation the SWAP model selects the target level for which all three criteria are met A scheme maintained by a soil moisture controlled weir is illustrated in Table 5 1 The minimum target level is specified in the first column The second third and fourth column represent values for the corresponding groundwater level soil water pressure head and soil wate
257. led meteorological records of both ET and rainfall Y 1 N 0 In case of detailed meteorological weather records SWMETDETAIL 1 NMETDETAIL 10 Number of weather data records per day 1 96 I In case of daily meteorological weather records SWMETDETAIL 0 SWETSINE 0 Switch distribute daily Tp and Ep according to sinus wave Y 1 N 0 SWRAIN 0 Switch for use of actual rainfall intensity SWRAIN 0 Use daily rainfall amounts SWRAIN 1 Use daily rainfall amounts mean intensity SWRAIN 2 Use daily rainfall amounts duration SWRAIN 3 Use actual rainfall amounts and times as supplied in separate file If SWRAIN 1 then specify mean rainfall intensity RAINFLUX 0 d0 1000 d0 cm d R as function of time TIME 0 366 d R maximum 30 records TIME RAINFLUX 1 0 2 0 360 0 2 0 End of table If SWRAIN 3 then specify file name of file with detailed rainfall data RAINFIL WagRain File name of detailed rainfall data without extension YYY A16 Extension equals last 3 digits of year number e g 2003 has extension 003 For many applications daily input of solar radiation air temperature air humidity and wind speed is preferred In that case SWAP applies the Penman Monteith method to determine ET If some of these data are missing or unreliable alternative methods to determine ET in combination with crop factors are advised Input of daily rainfall amoun
258. lei Leem Zandige leem Siltige leem Moerig Venig zand Zandig veen en veen Venige klei Kle g veen Dutch nomenclature Zand Leemarm zeer fijn tot matig fijn zand Zwak lemig zeer fijn tot matig fijn zand Sterk lemig zeer fijn tot matig fijn zand Zeer sterk lemig zeer fijn tot matig fijn zand Grof zand Keileem Beekleem Zavel Zeer lichte zavel Matig lichte zavel Zware zavel Kli Lichte klei Matig zware klei Zeer zware klei Leem Zandige leem Siltige leem Veen Oligotroof veen Mesotroof en eutroof veen Moerige tussenlaag Alterra Report 1649 update02 Clay Silt 50 pum o 4 10 11 18 18 29 30 50 5 39 60 75 85 95 1 10 10 16 20 32 36 47 5 40 35 45 60 75 85 92 Clay lt 2um 0 10 12 12 16 18 25 26 35 35 50 51 77 2 6 1 7 30 80 10 80 8 11 12 17 18 22 28 33 35 48 50 77 Organic matter 6 1 4 1 10 3 13 2 5 3 8 6 0 4 8 6 3 15 3 5 1 8 0 6 15 22 28 80 20 30 30 65 0 3 1 3 0 2 0 2 0 2 1 7 1 3 0 2 0 2 0 3 1 3 0 3 0 3 0 2 1 3 40 96 60 80 15 30 M50 um 140 170 125 175 105 165 118 160 350 500 150 400 105 205 105 175 114 172 128 170 220 400 150 400 100 140 245 Dry bulk density z cm 1 4 1 7 1 2 1 6 1 1 1 5 1 1 1 5 1 3 1 6 1 1 1 6 1 2 1 8 1 2 1 6 1 2 1 6 1 1 1 6 0 9 1 7 0 9 1 3 1 0 1 6 1 1 1 6 1 0 1 3 0 2 1 0 0 9 1 2 0 4 0 8
259. limitation cracks and hole shaped macropores are not explicitly distinguished Instead they are implicit in an effective functional horizontal macropore shape that is described by an effective matrix polygon diameter dy cm as a function of depth Assuming effective regular soil matrix polygons the effective vertical area of macropore walls per unit of volume sil cm cm gt is equal to the quotient of the perimeter divided by the area of the polygons For all even sided regular polygons from square to circle this quotient equals see Appendix 2 for derivation 4 Avai PN 6 20 pol The effective horizontal distance xpo cm from macropore wall to matrix polygon centre is taken equal to x siy o 6 21 pol 2 pol The effect of horizontal macropore shape on rapid drainage is expressed through the effect on the lateral hydraulic conductivity of cracks which depends on the effective 122 Alterra Report 1649 update02 crack width wa cm see Section 6 1 2 3 This width is calculated from the effective polygon diameter and the volume fraction V4 of macropores in the MB domain see 0 for derivation Wer d pol 1 41 Vas 6 22 It is assumed that the effective diameter dp of the soil polygons is a function of depth with its minimum value at the soil surface where macropore density is maximal and consequently distances between macropores are relatively small and its maximum value deeper in the profile where m
260. list AMAX reduction factor as function of minimum day temperature tmpftb list AMAX reduction factor as function of average day temperature tra actual transpiration rate cm d twlv pot total weight leaves living death kg ha twst pot total stems leaves living death kg ha wrt pot dry matter weight roots kg ha wlv pot dry matter weight leaves kg ha wst pot dry matter weight stems kg ha 280 Alterra Report 1649 update02 Example of an input file GrassG_field16_600N crp kkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkk Filename GrassG crp Contents SWAP 3 Data for detailed grass model FEI III III III E E E H E III H K E H ICI IIIS IIIS II III III III K KKK Ak Demo data set detailed grass model FEI III III III III III III ISIC III IIIS IIIS III III III ISI RI I ak PLANT GROWTH SECTION FI I I II II I OOOO IO I IR I IR IO A ROR IO AR Part 1 Crop factor or crop height SWCF 2 choice between crop factor 1 or crop height 2 Choose crop factor if ETref is used either from meteo input file SWETR 1 or with Penman Monteith Choose crop height if Penman Monteith should be used with actual crop height albedo and resistance Tf SWCE 1 list crop factor CE 0 5 1 5 RI as function of day number DNR 0 366 R If SWCF 2 list crop height CH 0 1000 cm R as function of day number DNR 0 366
261. low soil surface R OR X ACACIA IMPER_4E1 DROPR HDEPTH 0 0 15 0 End_of_table e 2 index of management period 1 NMPER I index per management period 1 10 I surface water level of phase IPHASE ALTCU 500 0 ALTCU cm R groundwater level of phase IPHASE max value 500 0 cm below soil surface R critical pressure head max value at HDEPTH see above for allowing surface water level 1000 0 cm neg R critical unsaturated volume min value for all surface water level 0 20 cm R otes 1 The zero s for the criteria on the first record are in fact dummy s because under all circumstances the scheme will set the surface water level at least to wlsman imper 1 The lowest level of the scheme must still be above the d eepest channel bottom of the secondary surface water system 2 IMPER 4E2 IMPPHASE WLSMAN GWLCRIT HCRIT VCRIT 2 1114 0 0 0 0 1124 80 1124 90 1154 100 1114 0 1124 80 1124 90 1154 100 BwWNHRPBWNHE Oooo 00 000 o0ooooooo o0ooooooo 3 End_of_table Ckckckckckckckckckckckckckckckck ck ck ckckckck ck ck ckck ck ck ck ck ck ck ck ck ckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckck ck k ck ck ck ck ckckckockok Alterra Report 1649 update02 109 110 Alterra Report 1649 update02 6 Macropore flow In structured soils such as clay and peat preferential flow o
262. ls PhD thesis Wageningen University 213 p Ritzema H P 1994 Subsurface flow to drains In Drainage principles and applications H P Ritzema Ed in Chief ILRI publication 16 second edition Wageningen p 263 304 Ross P J 1990 Efficient numerical methods for infiltration using Richards equation Water Resour Res 26 279 290 Russo D E Bresler U Shani and J Parker 1991 Analysis of infiltration events in relation to determining soil hydraulic properties by inverse problem methodology Water Resour Res 27 1361 1373 Saxena R K N J Jarvis and L Bergstr m 1994 Interpreting non steady state tracer breakthrough experiments in sand and clay soils using a dual porosity model J Hydrol 162 279 298 Schaap Marcel G and Martinus Th Van Genuchten 2006 A Modified Mualem van Genuchten Formulation for Improved Description of the Hydraulic Conductivity Near Saturation In Vadose Zone Journal 5 27 34 Scorza J nior R P J H Smelt J T I Boesten R F A Hendriks and S E A T M van der Zee 2004 Preferential flow of bromide bentazon and imidacloprid in a Dutch clay soil J Environ Qual 33 1473 1486 Scott P S G J Farquhar and N Kouwen 1983 Hysteretic effects on net infiltration In Advances in infiltration American Society of Agricultural Engineers St Joseph Mich p 163 170 Shalhevet J 1994 Using water of marginal quality for crop production major issues Agric Water Man 25 233
263. lume for a wide range of macropore geometries Default value of Rzag is 0 0 In Figure 6 2 Rza 0 2 implying that at the bottom of the A horizon z 25 cm 20 of the IC macropores has ended If Rzay 0 no IC macropores end above the bottom of the A horizon This option may be used to describe effects of tillage of the A horizon Data of a dye tracer experiment from Booltink 1993 for an A horizon in a clay soil in Flevoland the Netherlands point out that this option may be relevant Alterra Report 1649 update02 139 Box 6 1 Macropore flow input geometry Case Andelst Scorza J nior et al 2004 KKK ck kk KKK KKK KKK KK KK KK KK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK ck k ck k ck ck ck k ck ck ck k ck k ck KKK KKK AK Part 10 Preferential flow due to macro pores SwMacro 1 Switch for macro pores 0 1 I If SwMacro 1 specify parameters for macropore flow Z_AH 26 0 Depth bottom A horizon 1000 0 cm R Z_IC 90 0 Depth bottom Internal Catchment IC domain 1000 0 cm R Z_ST 180 0 Depth bottom Static macropores 1000 0 cm R VlMpStSs 0 04 Volume fraction of Static Macropores at Soil Surface 0 0 5 cm3 cm3 R PpIcSs 0 6 Proportion of IC domain at Soil Surface 0 0 99 R NumSbDm 4 Number of Sub domains in IC domain 0 MaDm 2 I PowM 0 8 Power M for frequency distrib curve IC domain OPTIONAL default 1 0 0 100 R RZah 0 0 Fraction macropo
264. lux Specify whether a sine or a table are used to prescribe the bottom flux SW2 2 1 sine function 2 table In case of sine function SW2 1 specify SINAVE 0 1 Average value of bottom flux 10 10 cm d R upwards SINAMP 0 05 Amplitude of bottom flux sine function 10 10 cm d R SINMAX 91 0 Time of the year with maximum bottom flux 1 366 d R In case of table SW2 2 specify date dd mmm yyyy and bottom flux QBOT2 100 100 cm d R positive upwards DATE2 QBOT2 maximum MABBC records 01 jan 1980 0 1 30 jun 1980 0 2 23 dec 1980 0 15 End of table KKK KKK KK KKK KKK KKK KKK KKK KK KKK KKK KKK KKK KKK KKK RA RARA RA RARA ck ck ckck ck kckck ck ck ckck ck ck KKK KK ck RA RAR ok ke ok e ok e ok e ok e soe sk oe koe ok oe koe koe ok oe koe koe oe oe koe koe oe soe koe ke ke e ke ke ke ke oe e ke ke oe e ke eoe ke ke ke ok e ke eoe eoe e ke e ok e ok e e e e e e e e e SWBOTB 3 Calculate bottom flux by using a Cauchy relation from hydraulic head in deep aquifer Switch to suppress the vertical resistance in the phreatic aquifer between groundwater level and the bottom of the model profile 0 default 1 suppress SWBOTB3RESVERT 0 Switch to suppress vertical resistance of phreatic aquifer 0 1 I Switch for implicit treatment of pressure head in lowest compartment while applying a Cauchy boundary condition 0 explicit 1 implicit SWBOTB3IMPL 0 Switch for i
265. m 6 65 E 1 TT ida x Nubia sais d 4A pf where dpo cm is the effective polygon diameter dy cm is the actual average polygon diameter in the field dc and dc cm are the diameters of two classes of hole shaped macropores in the field and N and N are their numbers per area Ayr cm If we assume that dy 15 cm that there are two classes of hole shaped parameters with an average diameter of 0 4 and 1 0 cm and with numbers per dm of 3 and 1 then the effective polygon diameter will be 11 9 cm Shrinkage characteristics The SWAP user needs to specify either the parameters of Kim s or Hendriks relationship see Section 6 1 1 2 or the values of typical points of the shrinkage characteristic curve The different options and required parameters are listed in Table 6 1 The option to specify the original parameters of both relationships is especially relevant for the development of pedotransfer functions for shrinkage characteristics Alterra is working on pedotransfer functions for shrinkage characteristics of clay and peat soils The options to use typical points of the shrinkage characteristic curves are 142 Alterra Report 1649 update02 Table 6 1 Overview of required shrinkage parameters for clay and peat soils Fig 6 4 A and 6 9 Soil Input option Shrinkage parameters ShrParA ShrParB ShrParC ShrParD ShrParE Clay 1 ax eo Bx YK i 2 ax eo 94 E Peat 1 eo 94 OH Bu Pu 2 o 94 9 Op Py 3
266. m and is flexible with the respect to adding of hj dependent source and sink terms Solving the set of non linear equations numerically implies root finding of the function F 0 for i N The Newton Raphson iteration scheme for the set of equations is written as follows OF OF 0 0 0 One Login gn apor 2 OR TEN Oh P Ohj p NT EN yino 2 0 OF OF CET 2 29 i TES ahit angst omo A l x OF 4 OF 4 pir pi 0 0 one anithe E 0 0 OF OF OP gni The starting values are the results of the previous iteration round indicated by the superscript p The solution of the second part of the right hand side is found by solving a tri diagonal system of equations which can be solved efficiently Press et al 1989 The coefficients of the Jacobian are listed in 0 The contribution of the j l p ay is discussed Oh 1 partial derivative of the macro pore exchange to the pressure head in Chapter 6 If the option to treat the hydraulic conductivities implicitly is used x 1 the contribution of the partial derivates of the internodal conductivity relation to the pressure head should also accounted Expressions for these terms are given in 0 Newton s method for solving nonlinear equations might wander off into the wild blue yonder if the initial guess is not sufficiently close to the root 36 Alterra Report 1649 update02 F hi hip 1 I Fig
267. mass WOFOST calculates a weighted average C kg kg 1 of these organ specific conversion factors by multiplying the organ specific values with the partitioning factors C i 7 22 Gini T a T Bd 1 Eu St Cor oan e stem O where amp j is the partitioning factor for organ i The gross dry matter growth rate Weross kg ha d is related to the net assimilation rate Anet by Weross E CA mes 7 23 Gross dry matter growth is first partitioned between shoots leafs stems and storage organs together and roots Woross root Su Weross and Weross sh 1 z osi Weross 7 24 where 5 is the partitioning factor for roots and Weross root and Weross sh are the gross growing rates kg ha d of the roots and the shoots respectively The gross growth rate of leaves stems and storage organs is simply the product of the gross dry matter growth rate of the shoots and the fraction allocated to these organs The partitioning factors are a function of development stage and are crop specific Figure 7 5 gives a typical example of the partitioning 7 3 8 Senescence The death rate of storage organs is assumed to be zero The death rate of stem and roots is crop specific and is defined as the daily amount of the living biomass that no longer participates in the plant processes The death rate of stems and roots is considered to be a function of development stage as specified by the user The death rate of leaves is mor
268. me is present the horizontal area fraction of the matrix equals 1 V4 cm cm and consequently the dynamic macropore volume fraction is calculated as Vy 1 v s Vo 6 12 iy 6 12 118 Alterra Report 1649 update02 The vertical shrinkage component is determined from the overall matrix shrinkage as Bronswijk 1988 1 where exponent r is the geometry factor Rijniersce 1983 In case of three dimensional isotropic shrinkage rs 3 When cracking dominates subsidence r gt 3 when subsidence dominates cracking lt r lt 3 In case of subsidence only r 1 The geometry factor is an input parameter The matrix shrinkage volume fraction Vs is a function of volumetric moisture content and shrinkage characteristic A shrinkage characteristic describes the relationship between soil volume and soil moisture content Many forms of shrinkage characteristics exist A very convenient one is the characteristic that takes the constant volume fraction of the solid soil fraction V as reference for all variable volume fractions and expresses the soil matrix volume fraction Vm in terms of pore volume fraction V relative to Vso Bronswijk 1988 all V in cm cm V V sol V 1 eV 6 14 where e cm cm is the void ratio ga 6 15 The shrinkage volume fraction V is equal to the fraction of volume loss of the matrix that in its turn equals the fraction loss of pore volume The latter is expressed in terms
269. meter of soil polygons dyo cm for compartment i is calculated with Eq 6 23 by substituting Vs 1 P and z for Vs Pic and z respectively z cm is the depth of node i which is in the middle of compartment i The effective vertical area of macropore walls per unit of horizontal area A wan cm cm is obtained by multiplying the vertical area of macropore walls per unit of volume A wail with compartment thickness Az 4 Avani AvanAz 7 3 Az 6 50 poli The effective horizontal distance xpo cm is calculated with Eq 6 21 by substituting dpo1 for dy The effective crack width we cm in the MB domain for compartment i is calculated from Eq 6 22 as V np l i Weri d poli 1 a 1 gt EU 6 50 1 Alterra Report 1649 update02 133 6 2 2 Water flow and balance The water balance of macropore domain j 1 MB domain for time step Ar d reads in accordance with Eq 6 24 nib nub ndb S E ST o PGE Qu j AZ 2d 5A B 2 dis AZ a 6 52 i nit i l i nub 1 Water balance equations of all other domains j gt 1 are equal to Eq 6 52 but with exclusion of the rapid drainage term qra that only applies to domain 1 the MB domain The compartment numbers nit nib nub and ndb refer to the top and bottom compartment with interflow from perched groundwater the bottom deepest unsaturated compartment and the compartment with bottom of domain j respectively Storage S is always limited
270. mparison between simulated and required soil moisture criterium HCRIT The three state variables GWLCRIT HCRIT VCRIT that define the target weir level are given in a separate table Box 5 5 Relation between groundwater and surface water levels in drainage file DRA TKK ROK RK ROK RK RK RK RK ROK ROK RK ck ckck ck ck ck ck ck ck ck ck KK KK KK KK KK KK KK KK KK KR ck ck ckckckckckckckckckckckck ck ck ck ck k ck RK OK OK choice for type of discharge relationship SWOHR 1 option for type of discharge relationship 1 2 I 1 exponential relationship see part 4c 2 table see part 4d TKK ROK OK ROK RK RK ROK RK RK RK RK ck ckck ck ck ck ck ck ck ckck ck ck KK KK RK KK RK RK RK KK KR KK RK RK OK OK OR OK OK ck ck k ck Rk OK OK Part 4c exponential discharge relation weir characteristics If SWOHR 1 and for ALL periods specify SOFCU 100 0 Size of the control unit 0 1 100000 0 ha R IMPER index of management period 1 NMPER I HBWEIR weir crest levels above soil surface are allowed but simulated surface water levels should remain below 100 cm above soil surface the crest must be higher than the deepest channel bottom of the Secondary system ZBOTDR 1 or 2 ALTCU ZBOTDR ALTCU 100 cm R If SWMAN 2 HBWEIR represents the lowest possible weir position ALPHAW alpha coefficient of discharge formula 0 1 50 0 R BETAW beta coefficient of discharge formula 0 5 3 0 R IMPER 4c HBWEIR
271. mplicit explicit 0 1 I Specify SHAPE 0 79 Shape factor to derive average groundwater level 0 0 1 0 R HDRA 110 0 Mean drain base to correct for average groundwater level 10000 0 cm R RIMLAY 500 0 Vertical resistance of aquitard 0 10000 d R Specify prescribe hydraulic head of the deep aquifer by either a sine function or as a tabulated time series SW3 1 1 sine function 2 table In case of sine function SW3 1 specify AQAVE 140 0 Average hydraulic head in underlaying aquifer 10000 1000 cm R AQAMP 20 0 Amplitude hydraulic head sinus wave 0 1000 cm R AQTMAX 120 0 First time of the year with maximum hydraulic head 1 366 d R AQPER 365 0 Period hydraulic head sinus wave 1 366 d I 50 Alterra Report 1649 update02 In case of table SW3 2 specify date dd mmm yyyy and average hydraulic head HAQUIF in underlaying aquifer 10000 1000 cm R DATE3 HAQUIF maximum MABBC records 01 jan 1980 95 0 30 jun 1980 110 0 23 dec 1980 10 0 End of table Specify an additional bottom flux to be added to the Cauchy relation by a tabulated time series this option is only meant to facilitate the coupling of the SWAP model to a regional groundwater model sw4 0 0 no extra flux 1 include extra flux If SW4 1 specify date dd mmm yyyy and bottom flux QBOT4 100 100 cm d R positive upwards DATE4 QBOT
272. mputed for each time step Ar by substituting Eq 6 13 in Eq 6 12 and multiplying with compartment thickness Az 1 Vi Vai gy 1 V Js 1 m M mousse The shrinkage volume fraction Vs cm cm is calculated from actual moisture V dy i 6 48 i content and shrinkage characteristic of compartment i at the beginning of Ar 132 Alterra Report 1649 update02 6 49 a 0 e f 9 9 s e 9 and V 1 0 6 49 b s i s i soli si soli soli with 0 is the actual and 0 the saturated volumetric moisture content cm cm of compartment i In order to correctly model infiltration into the soil matrix at soil surface thin model compartments in the order of 1 cm thick are advised for the top of the soil profile Van Dam and Feddes 2000 Because of the dynamical conditions at soil surface and the small storage capacity of the thin compartments moisture contents may change rapidly As a result shrinkage volume at soil surface may appear and disappear faster than in reality Because the quantity of shrinkage volume at the soil surface is crucial for determining the amount of precipitation water infiltrating into the macropores shrinkage volume of the first compartments is calculated on the basis of moisture content of the compartment that contains a reference depth Zerack Where moisture conditions are less dynamical Zeracx is an input parameter 6 2 1 3 Horizontal distribution Effective dia
273. mulated 2 the surface water level is obtained from input data If the third option SWSRF 3 has been chosen the user should also specify section 2b the time variation of the surface water level in the primary water course The specification is done in terms of data pairs date water level To obtain levels at intermediate dates the model performs a linear interpolation 104 Alterra Report 1649 update02 Box 5 2 Global options for interaction with surface water in drainage file DRA KKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKK KKK KKKKKK KKK KKK KKK KK ARA AAA KARA AAA KK AAA k ko kckckok Part 2a Specification and control of surface water system SWSRF 2 option for interaction with surface water system 1 3 I 1 no interaction with surface water system 2 surf water system is simulated with no separate primary system 3 surf water system is simulated with separate primary system EEES Part 2b Surface water level of primary system Only if SWSRF 3 then the following table must be entered Table with Water Levels in the Primary system max 52 no levels above soil surface for primary system Water level in primary water course WLP ALTCU 1000 ALTCU 0 01 cm R as function of DATEI dd mmm yyyy DATEI WLP 02 jan 1980 100 14 jun 1980 80 24 oct 1980 1 20 End_of_table TKK ROK OK RK RK RK ROK RK RK ck ckck ck ck ckck ck ck KK ck ck ck ck KK KK KK KK RK KK KK KK KK KK ck
274. n g cm which is used to make N dimensionless The solute sink term S can be written as S u 0c p Q K Sc 8 10 where u is the first order rate coefficient of transformation d K is the root uptake preference factor and S the root water extraction rate d At the right hand side of Eq 8 10 the first term accounts for linear decomposition and the second term for root uptake proportional to water uptake K accounts for positive or negative selection of solute ions relative to the amount of soil water that is extracted 176 Alterra Report 1649 update02 The coefficient u is affected by soil temperature water content and depth Analogous to Boesten and Van der Linden 1991 SWAP calculates u from H fr fo f Mier 8 11 in which fr is a soil temperature factor f and f are reduction factors accounting for the effect of soil water content and soil depth and hef d is u at reference conditions e g soil from the plough layer at 20 C and at soil water pressure head h 100 cm The factor fr is described according to Boesten 1986 as ducem 8 12 where yr is a parameter C 5 and T is the soil temperature in C Wolfe et al 1990 describe the importance of the water content in transformation processes Realizing that it is a large simplification in SWAP we adopt the relation as proposed by Walker 1974 B hF lo with f lt 1 0 8 13 ref where Oef is 0 at h 100 cm and Bis a consta
275. n Agricultural University Wageningen The Netherlands Tetens O 1930 Uber einige meteorologische Begriffe Z Geophys 6 297 309 Alterra Report 1649 update02 219 Thoma S G D P Gallegos and D M Smith 1992 Impact of fracture coatings on fracture matrix flow interactions in unsaturated porous media Water Resources Res 28 1357 1367 Thoms R B R L Johnson and R W Healy 2006 User s guide to the variability saturated flow VSF process for MODFLOW USGS Techniques and Methods 6 A18 Reston Virginia U S Geological Survey Tiktak A F van den Berg JJ T I Boesten M Leistra A M A van der Linden and D van Kraalingen 2000 Pesticide Emission at Regional and Local scales Pearl version 1 1 User Manual RIVM report 711401008 report 29 Alterra Green World Research Wageningen Van Bakel P J T 1986 Planning design and operation of surface water management systems a case study PhD thesis Wageningen Agricultural University Van Dam J C J M H Hendrickx H C van Ommen M H Bannink M Th van Genuchten and L W Dekker 1990 Water and solute movement in a coarse textured water repellent field soil J Hydrol 120 359 379 Van Dam J C J N M Stricker and P Droogers 1994 Inverse method to determine soil hydraulic functions from multi step outflow experiments Soil Sci Soc Am J 58 647 652 Van Dam J C J H M W sten and A Nemes 1996 Unsaturated soil water movement in hysteretic and wat
276. n the canopy 7 3 4 Instantaneous assimilation rates per leaf layer 7 3 5 Daily gross assimilation rate of the canopy 7 3 6 Maintenance respiration 7 3 7 Dry matter partitioning and growth respiration 7 3 8 Senescence 7 3 9 Net growth 7 3 10 Root growth 7 4 User instructions 7 4 1 Simple crop module 7 4 2 Detailed crop module Solute transport 8 1 Introduction 8 2 Basic equations 8 2 1 Transport processes 8 2 2 Continuity and transport equation 8 3 Boundary conditions 8 4 Crack solute transport 8 5 Residence time in the saturated zone 8 6 User instructions Soil temperature 9 Temperature conductance equation 9 2 Numerical solution 9 3 Analytical solution sinus wave 9 4 User instructions Snow and frost 10 1 Snow 10 1 1 Snowfall 10 1 2 Snowpack 10 2 Frost 10 3 User instructions Irrigation 11 1 Fixed irrigation regime 11 2 Scheduled irrigation regime 11 2 1 Timing criteria 11 2 1 1 Allowable daily stress Alterra Report 1649 update02 138 145 147 147 147 148 151 152 153 155 156 158 158 160 162 163 163 163 167 173 173 174 174 176 178 179 179 181 185 185 186 189 190 193 193 193 194 196 199 201 201 201 201 202 11 2 1 2 Allowable depletion of readily available water 11 2 1 3 Allowable depletion of totally available water 11 2 1 4 Allowable depletion of field capacity water 11 2 1 5 Critical pressure head or moisture content 11 2 1 6 Fixed interval 11 2 1 7 Minimum interv
277. n the unsaturated zone In irrigated areas the long term salinity in the root zone will depend on the amount of percolation from the unsaturated zone Whereas in the unsaturated zone the transport of solutes is predominantly vertical once being in the groundwater solutes may diverge in any direction threatening surface waters nature reserves and drinking wells Using an analytical model Beltman et al 1995 show the importance of the transport processes in the unsaturated zone as compared to the transport processes in the saturated zone It is clear that a thorough understanding is needed of the processes that govern the transport adsorption root uptake and decomposition of the solutes in the unsaturated zone in order to analyse and manage soil and water related environmental problems SWAP is designed to simulate basic transport processes at field scale level Although for management purposes most farmers try to have more or less the same soil and drainage condition per field still the existing soil spatial heterogeneity within a field may cause a large variation of solute fluxes Biggar and Nielsen 1976 Van de Pol et al 1977 Van der Zee and Van Riemsdijk 1987 Most of this variation is caused by spatial variation of the soil hydraulic functions preferential flow due to macropores in structured soils or unstable wetting fronts in unstructured soils In many cases it will not be possible to determine the variation including the correlati
278. nd transpiration rates calculation of runoff calculate pressure head from water content calculate fluxes of diffuse and PAR radiation read SWAP main input file calculate actual soil evaporation calculate potential and actual water extraction by roots snow submodel calculate soil water rate state variables calculate solute transport calculate rate state variables of surface water system calculate soil temperatures handles time variables switches and flags calculate daily total gross assimilation output of warnings to screen and log file calculate water content from pressure head calculate water storage in soil profile and cracks Alterra Report 1649 update02 257 Wofost detailed crop growth routine WriteHead write header with model version project name etc 258 Alterra Report 1649 update02 Appendix 14 Description of output files afo and aun This annex describes the content of the output files with extension afo and aun The content of both files is identic they only differ in format one file is binary and unformatted aun and the other file is formatted afo The description given in this annex uses the following symbols Unit units as applied in these output files units differ from those applied in Swap R data are written to a new record DT datatype R means Real 4 I means Integer 2 Mnemonic the name of the variable as applied in the source code of Swap Description
279. ndary conditions near the soil surface Calculated soil water fluxes can be significantly affected by the structure of the numerical scheme the applied time and space discretizations and the procedure for the top boundary condition Van Genuchten 1982 Milly 1985 Celia et al 1990 Warrick 1991 Zaidel and Russo 1992 The numerical scheme chosen in SWAP solves the one dimensional Richards equation with an accurate mass balance and converges rapidly This scheme in combination with the top boundary procedure has been shown to handle rapid soil water movement during infiltration in dry soils accurately At the same time the scheme is computationally efficient Van Dam and Feddes 2000 2 7 1 Richards equation The current numerical scheme of SWAP to solve Richards equation is the implicit backward finite difference scheme with explicit linearization of hydraulic conductivities as described by Haverkamp et al 1977 and Belmans et al 1983 but with the following adaptations e The numerical scheme applies to both the unsaturated and saturated zone and the flow equations are solved in both zones simultaneously e The water storage term Tis evaluated instead of using an approximation for t C a where C is the water capacity cm t e There are several options for calculating the internodal conductivity The implicit backward finite difference scheme of Eq 2 23 with explicit linearization yields the following discretiz
280. nding reservoir cm d prec is the precipitation flux subtracted with interception cm d iri 1s the irrigation flux subtracted with interception cm d q is the flux from the first model compartment to the ponding layer cm d mett is snowmelt cm d Grunon 18 the runon flux of water which enters the field from an upstream adjacent field cm d dina 18 the inundation or flooding from surface water to the field cm d Grunorr 1S surface runoff flux cm d and qe pona 18 the evaporation flux of the open water stored on the soil surface cm d and J is the runoff into the macropores cm d see section 6 1 2 Surface runoff occurs when the water storage in the ponding layer exceeds the critical depth of ho threshoa CM 70 Alterra Report 1649 update02 1 runoff Y max 0 ho CE dioecesi 4 2 where ho is the ponding depth of water cm on the soil surface y is a resistance parameter cm d and B is an exponent in the empirical relation Inundation of the field from an adjacent water course can be simulated when the surface water level exceeds both and Jena This option is only available when the so called extended drainage option is chosen see Chapter 5 4 2 Interflow In some applications one may wish to describe an interflow system which has a rapid discharge with short residence times of the water in the soil system If the groundwater level is higher than the reference level arainn the i
281. ng to Boesten Stroosnijder Alterra Report 1649 update02 63 In order to take account for the dependence of the Black parameter B on Ep Boesten and Stroosnijder 1986 proposed to use the sum of potential evaporation XE cm as time variable NE E for NE lt B3 NE B NE fr XE gt p where f is a soil parameter cm which should be determined experimentally The 2 72 parameter p determines the length of the potential evaporation period as well as the slope of the XE versus CE relationship in the soil limiting stage Boesten and Stroosnijder suggest the following procedure with respect to updates of XE On days with no excess in rainfall Pret lt Ey XE follows from Eq 2 72 X5 X amp E 5 273 in which superscript j is the day number XE is calculated from ZE with Eq 2 72 and E is calculated with SAME E did On days of excess in rainfall Pret gt Ej ELSE 2 75 and the excess rainfall is subtracted from XZ E NE B E 2 76 Next EE is calculated from ZE Y with Eq 2 72 If the daily rainfall excess is larger than CEJA then both LE and EE are set to zero SWAP will determine E by taking the minimum value of Ej Emax and if selected by the user one of the empirical functions 3 7 User instructions 3 7 1 General information Box 3 1 lists the general input data with respect to evapotranspiration The name of the meteorological files is generic and
282. nitrogen application 0 8 4 0 6 4 0 4 4 0 2 4 0 200 300 400 600 800 Nitrogen application kg Figure B16 4 Reduction factor for influence of nitrogen supply on on AMAX Source Nitriogen fluxes in intensive grassland systems Van der Meer H G Ryden J C Ennik G C 1986 Maintenance respiration Grass assumes that the maintenance requirements are approximately proportional to the dry weights of the plant organs to be maintained 3 R nr gt CmiW i l where Rint Maintenance respiration rate at ref temp of 25 C kg CH20 ha 4 Cmi Maintenance coefficient organ i kg CH O kg d Wi Dry matter weight organ i kg ha 1 Leaves stems or roots The maintenance respiration rate has to be corrected for senescence This correction factor is crop specific and is defined as a function of the day number An AFGEN table Alterra Report 1649 update02 267 acronym rfsetb with the day number as independent variable is used to describe this dependency However in Grass this factor is set to unity Higher temperatures accelerate the plant tissue turnover rates and hence the maintenance costs An increase of 10 C increases maintenance respiration by a factor of about 2 To be more flexible a variable Qi is introduced which is defined as the relative increase of the respiration rate per 10 C increase Qio should be provided by the user The maintenance respiration rate at a certain temperature
283. nsport SWSOLU 1 Switch for simulation of solute transport Y 1 N 0 KKK KKK KK KKK KKK KK KKK KKK KKK KA KKK KK KK KKK KKK KKK KKK KKK KKK KKK ck ck kckck RARA RARA RRA RRA RRA KK RK RK RK RK RK RK RK KK RK KKK KKK KKK KKK KKK KK KKK KKK KKK ckck kck ckck kck ck ck k ck KK KKK ckck ck k ck ck KKK KKK KK KKK Part 2 Top boundary and initial condition CPRE 0 0 Solute concentration in precipitation 0 0 100 0 mg cm3 R If SWINCO 1 or 2 list initial solute concentration CML 0 0 1000 0 mg cm3 R as function of soil depth ZC 10000 0 cm R max MACP records ZC CML 10 0 0 0 95 0 0 0 End of table KKK RK RK KK KK ck ck RK RK KK KK RK KKK KKK KKK KKK KK KKK KKK KK KK KKK ck ck kck ck ck ck ckck ck ck KKK KKK ck k ck k ck k ck k ck ck RAR 182 Alterra Report 1649 update02 KK ck ck KKK KKK KK KA KA KA KKK KKK KK KK KK KK KK KK KKK KKK KKK ck k ck k ck k ck k ck k ck k ck k ck k ck k ck k ck k ck k ck kck k ck kck Part 3 Miscellaneous parameters as function of soil depth Specify for each soil layer maximum MAHO ISOILLAY6 number of soil layer as defined in soil water section part 4 1 MAHO I LODES dispersion length 0 0 100 0 cm R KF Freundlich adsorption coefficient 0 0 100 0 cm3 mg R BDENS dry soil bulk density 500 0 3000 0 mg cm3 R DECPOT potential decomposition rate 0 0 10 0 d R ISOILLAY6 LDIS KF BDENS DECPOT 1 5 00 0 0001389 1315 00 0 0
284. nt The transformation reduction factor for soil depth f should be derived from in situ measurements The user may specify f as function of soil depth in the input file Combination of Eq 8 6 8 7 8 8 and 8 10 yields the transport equation applied in SWAP which is valid for dynamic one dimensional convective dispersive mass transport including non linear adsorption linear decay and proportional root uptake in unsaturated saturated soil Van Genuchten and Cleary 1979 Nielsen et al 1986 Boesten and Van der Linden 1991 Oc l 0 D D 0 0c p Q gc ait t us Ot Oz Oz u 0c p Q K Sc 8 14 An explicit central finite difference scheme is used to solve Eq 8 14 Alterra Report 1649 update02 177 07g P Q 0c P Q _ At PAD ci c B us ci eu AZ Va Az Az Va Az Az j do ud j Qi Civ dis Ci Az 1 TH 0 c t pQ K S c 8 15 where D Dait Dais is the overall dispersion coefficient cm d the superscript j denotes the time level subscript i the node number and subscripts i 1 2 and i 1 2 refer to linearly interpolated values at the upper and lower compartment boundary respectively Compared to an implicit iterative scheme above explicit scheme has the advantage that incorporation of non linear adsorption mobile immobile concepts and other non linear processes is relatively easy In order to ensure stability of
285. nt for over saturation of saturated paste 0 0 10 0 R If SWC2ECF 2 specify for each soil layer KS COREGEB A 7 b 2y Factor f to account for over saturation of saturated paste 0 0 10 0 R ek HE E E KK KK KOC OOOO ICI III III ISIC OOOO III III III III ICI IIR IIR a ak FI kk I kk kk I I I ke kk kk kk ke kk kk I ko kk kk I II I ko kk kk IR I I OR IO A RR IO AR Part 11 Interception COFAB 0 25 Interception coefficient Von Hoyningen Hune and Braden 0 1 cm R ek HEE E OOOO III III III ICI III ISIC ISI IIIS IIIS III III OOOO kkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkk Part 12 Root density distribution and root growth List relative root density 0 1 R as function of rel rooting depth 0 1 R RDCTB is not used in Swap Grass RD RDC maximum 11 records RDCTB List specific root length 0 5000 R as function of rel root weight 0 5000 R RW in kg ha dm RL in cm d RW RL maximum 11 records RLWTB 300 00 20 0 2500 00 40 0 End of table RDI 20 0 Initial rooting depth 0 1000 cm R RRI 0 01 Maximum daily increase in rooting depth 0 100 cm d R RDC 40 0 Maximum rooting depth crop cultivar 0 1000 cm R Maximum root weight kg ha dry matter default was 2500 0 wrtmax 4000 0 Maximum root weight 0 100000 0 kg ha DM R OK Ck kk kk I kk kk ok kk OOOO II I II IO IIR IO IR IO RAR RA A
286. nterflow flux is optionally calculated as Pow Pdrain n max y min 1 syl T Tor 4 3 ddrain n x Or as B erflow Q rain n Ainterflow owl B D aga t 4 4 Where Q rainn is the interflow flux cm d Yin and y are the minimum and the reference resistance related to the interflow process 1 is a factor that expresses the unit conversion and is equal to 1 d cm in this case Ainterfiow 18 a conductance parameter cm d and Binterflow is an exponent in the empirical relation The subscript n points to the rule that in the SWAP model interflow is always assigned to the highest order of distinguished drainage systems 4 3 Drain discharge Although the entity for which the SWAP model operates is at field scale the model is used both for field studies and for regional studies The different spatial scales of operation are expressed among other things by the type of drainage relation and its associated parameters chosen For the purpose of a drainage system at field scale one may use one of the classical drainage equations but for simulation of water discharge in the spatial entity of a sub catchment the use of a multiple drainage system formulation is more convenient Table 4 1 provides a brief overview of the drainage options available in the SWAP model Additionally options are available to take account for the influence of surface water management strategies on soil water flow and drain discharge The
287. nternal note Winand Staring Centre Wageningen Wesseling J G J G Kroes and K Metselaar 1998 Global sensitivity analysis of the Soil Water Atmosphere Plant SWAP model Report 160 Alterra Wageningen 67 p Wolfe N L U Mingelgrin G C Miller 1990 Abiotic transformations in water sediments and soil In H H Cheng Ed Pesticides in the soil environment processes impacts and modeling SSSA Book Series no 2 Madison Wisconsin USA Wosten J H M G J Veerman and J Stolte 1994 Water retention and hydraulic conductivity functions of top and subsoils in The Netherlands The Staring series Technical Document 18 Winand Staring Centre Wageningen The Netherlands 66 p in Dutch 222 Alterra Report 1649 update02 Wosten J H M A Lilly A Nemes and C Le Bas 1998 Using existing soil data to derive hydraulic properties for simulation models in environmental studies and in land use planning Report 156 Winand Staring Centre The Netherlands Wosten J H M G J Veerman W J M de Groot and J Stolte 2001 Water retention and hydraulic conductivity functions of top and subsoils in The Netherlands The Staring series Alterra report 153 Wageningen The Netherlands 86 p in Dutch Yates S R M Th van Genuchten A W Warrick and F J Leij 1992 Analysis of measured predicted and estimated hydraulic conductivity using the RETC computer program Soil Sci Soc Am J 56 347 354 Youngs E G and R I P
288. odel can take account for the different types of interconnections between soil moisture groundwater and surface water by offering options for describing surface runoff as a non linear function of water storage on the field interflow as a non linear function of the groundwater elevation when it has reached the near surface zone and the discharge to a series of drainage systems Options to simulate dynamically the levels in surface water systems provide the possibility to describe the feedback and the close interconnection between groundwater and surface water in stream valleys and polders Alterra Report 1649 update02 69 4 1 Surface runoff Surface runoff is one of the terms in the water balance of the ponding reservoir The ponding reservoir stores a certain amount of excess water on top of the soil surface Fig 4 1 Runon abre TOO e 2 Net precipitation Net irrigation Flooding En Evaporation gor Snow melt v Ponding layer Soilsurface Pojthreshola Surface runoff 9 Soil compartment 1 A q2 Interflow Soil compartment 2 A qs _ gt Soil compartment 3 Figure 4 1 Schematic representation of the near surface flux to a surface water system and the water balance of the ponding layer The water balance of the ponding reservoir is governed by Ah At d prec diri d met az Q runon x Oinun E q de pond d runoff Lya 4 1 where Ah is the storage change of the po
289. of variable Unit Range R DT Mnemonic Time domain Year when hydrological simulation started 1 co gt bruny Year when hydrological simulation ended E bruny co gt l eruny Time Julian daynumber when hydrological simulation 0 0 366 z R brund 1 started Minimum will be 0 0 when simulation started at 1st of January 00 00 hour Time Julian daynumber when hydrological simulation E 0 0 366 R erund ended Maximum Step size of time interval for dynamic hydrological data d 1 0 30 0 R period Geometry of model system Number of model compartments F 1 numnod l numnod Number of horizons 1 numlay numlay Number of drainage systems 0 1 2 3 4 5 l nrlevs value must be 0 1 2 3 4 or 5 The following 4 variables botcom thetawp are given for the horizons 1 numlay Compartment number of the deepest compartment 1 numnod botcom numlay bottom of each horizon layer Volume fraction moisture at Saturation m m 0 0 1 0 R thetas numlay Volume fraction moisture at Field Capacity m m 0 0 1 0 R thetafc numlay Volume fraction moisture at Wilting point m m 0 0 1 0 A R thetawp numlay The following variable dz is given for the compartments 1 numnod Thickness of compartments m 0 001 100 R dz numnod Alterra Report 1649 update02 259 Description of variable Unit Initial conditions The following variable theta is given for the compar
290. oisture content and ots is a fitting parameter 126 Alterra Report 1649 update02 Average constant absorption rate q ay per unit of depth cm cm d for time interval t is obtained from ab t ab t d 6 31 diu ab t Y f K Infiltration rate by Darcy flow per unit of depth q p cm cm d reads hs T h fa 8K h h mp a dp Sp Ava Es gt 6 32 pol d where K cm d is the hydraulic conductivity as a function of pressure head in the unsaturated matrix Am cm and term Amp Ami xy is the lateral pressure head gradient between macropore and centre of the matrix polygon Parameter fin is a shape factor to account for the uncertainties in the theoretical description of lateral infiltration by Darcy flow originating from uncertainties in the exact shape of the soil matrix polygons Depending on whether the polygons are more plate or cylinder shaped the figure in Eq 6 32 should be somewhere between 8 and 16 Thus theoretically the value of f np lies between 1 and 2 Pressure head Amp as a function of depth is obtained from the macropore water level elevation mp and depth z as hap Pmp Z 6 33 Finally the lateral infiltration fluxdensity into the unsaturated matrix per unit of depth q i cm cm d is obtained by taking the largest flow rate di max 4 disp 6 34 Distribution of d over MB and IC domains is according to their proportions Pm and P
291. olled boundary condition and head controlled boundary condition the model has additional capabilities to combine these basic types of conditions Additional options comprise the handling of e Predefined groundwater levels e Cauchy relation for the bottom boundary e Free drainage e Free outflow Alterra Report 1649 update02 39 Flux controlled bottom boundary fa pito For i n the Kj it Vo Az AZi41 term in Eq 2 29 is replaced by q which yields AA pit F 2 oi 0 He AT lp Az sit Si si 1 2 36 At YA AZ FAZ 4 i Beside the flux boundary condition the SWAP model has options to handle groundwater level dependent bottom fluxes The flux can be formulated as an exponential function of groundwater level or as the difference between groundwater level and hydraulic head in deep groundwater outside the flow domain divided by a flow resistance Such a flux is calculated explicitly at the start of the current time step and is treated as a flux condition in the numerical scheme Head controlled bottom boundary For i n Az is set to zero and hj n which leads to the following expression j 1 j 1 j 1 pean oj oi KI ha hs 1 d ig hoop 1 n Ati n n nY VA AZ 1 Az nc YAz Az Sit tS i 2 37 m n Predefined groundwater levels First the lowest partially unsaturated compartment is searched for and is called n The set of n non linear equations
292. olution of Richards equation DTMIN 1 0d 6 inimum timestep 1 d 7 0 01 d R DTMAX 0 2 Maximum timestep 0 01 0 5 d R GWLCONV 100 0 Maximum dif groundwater level between iterations 1 d 5 1000 cm R CritDevPondDt 1 0d 4 Maximum water balance error of ponding layer 1 0d 6 0 1 cm R MaxIt 30 Maximum number of iteration cycles 5 100 I MaxBackTr 3 Max number of back track cycles within an iteration cycle 1 10 I Optional input of 2 criteria CritDevhlCp and CritDevh2Cp when these parameters are absent then defaults values of resp 0 02 and 0 01 are applied CritDevhlCp 1 0d 2 Maximum relative difference in pressure heads per compartment 1 0d 10 0 1 R CritDevh2Cp 1 0d 1 Maximum difference in pressure heads per compartment 1 0d 10 1 0 cm R Switch for mean of hydraulic conductivity 1 4 I 1 unweighted arithmic mean 2 weighted arithmic mean 3 unweighted geometric mean 4 weighted geometric mean SWkmean 2 Switch for explicit implicit solution Richards equation with hydr conductivity 1 2 I SWkImpl 0 0 explicit solution 1 implicit solution kk ck kk Sk ke ck ck ck ck Sk kk KKK KKK KKK kc ck ck KKK KK KKK KK KEK KKK KKK KK KKK KKK KEK KKKKKKKKKEKKKKKKKKKKKKKKKKEKK 2 8 2 Bottom boundary conditions SWAP offers a number of options to prescribe the lower boundary condition each having their typical scale of application Tabl
293. omain j ends 1 ji Zad j Zan Zas 2 6 40 Ta If option Rzay gt O is chosen an extra Ah sub domain j nsa 1 is created with proportion R F 1 Bd for 0 z gt Za 6 41 4 F 1 ic 0 dus for z lt Z 6 41 b Because the MB domain is always present though sometimes with very low proportion the total number of domains nam Asa 1 In case of Rzay gt 0 Nam Msa 2 All domains are numbered from j 1 to nam with the MB domain being the first domain j 1 and the deepest IC domain the second j 2 In the model the vertical coordinate z is partitioned into discrete model compartments i with thickness Az cm between zy and zi at the bottom and top of the compartment respectively For each compartment a discrete macropore volume per domain is required Volumetric proportion P for each combination of domain j and compartment i is obtained by integration of Pms and P a as a function of z over the compartment thickness and dividing by Az Zti Zti Redz Epad pos and P fo 2 lt j lt n 6 42 t 1 Per domain the macropore volume is vertically interconnected over the soil compartments Domains j gt 1 to j na inclusive that end in the same model compartment are functionally equal and therefore are lumped for all compartments i 1 to ndb compartment number that contains bottom of domain j Na j P P gt Pa and P P forall 1 lt 1 lt n na 643 l 1 Ha js For each
294. only calculated for compartments n bottom to m 5 frozen The following is then valid When drainage does not occur and the available air volume is very low 0 01 cm cm the bottom flux is reduced to zero When drainage does occur and the available air volume is very low 0 01 cm cm the drainage fluxes of all drainage systems that have a drainage level above the lowest frozen soil compartment are reduced to Zero Figure 10 2 Partly frozen soil profile Alterra Report 1649 update02 10 3 User instructions Both the options for snow and frost can only be used in combination with the option for simulation of soil temperature For the snow option the two threshold temperatures Train and Tsnow the initial storage of snow at the beginning of the simulations Ssnow and the degree day factor a are required as model input Box 10 1 The frost option requires input for the two threshold temperatures 75 and T Box 10 1 Box 10 1 Input for snow and frost modules in file SWP KK KK KK KKK KKK KKK ck ck KK KK KKK KKK KK KK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK KK ck ck ckck ck ck ck k ck k ck ck ck ck KKK AK Part 11 Snow and frost SWSNOW 1 Switch calculate snow accumulation and melt Y 1 N 0 If SWSNOW 1 then specify initial snow water equivalent and snowmelt factor SNOWINCO 22 0 Initial snow storage in w e water equivalent 0 0 1000 0 cm R TePrRain 2 0 T
295. ons of all the physical parameters Hopmans and Stricker 1989 SWAP confines to the physical processes in order to be flexible in parameter input and allow the simulation of all kind of design and management scenarios The spatial variability can be taken into account by inverse modelling or Monte Carlo simulation Inverse modelling has been applied by Groen 1997 He measured for a period of time the solute concentrations in the soil profile and drainage water and determined field effective transport parameters by inverse modelling In case of Monte Carlo simulations the model is run a large number of times while the input parameters and boundary conditions are varied according to the variation at comparable fields Boesten and Van der Linden 1991 Alterra Report 1649 update02 173 SWAP focuses on the transport of salts pesticides and other solutes that can be described with relatively simple physical relations convection diffusion dispersion root uptake Freundlich adsorption and first order decomposition Transport related processes that are not considered in SWAP are volatilization and gas transport transport of non mixing or immiscible fluids e g oil and water chemical equilibria of various solutes e g between Na Ca and Mg chemical and biological chain reactions e g mineralization nitrification In case of advanced pesticide transport including volatilization and kinetic adsorption SWAP can be used in
296. opment stage Higher temperatures accelerate the turnover rates in plant tissue and hence the costs of maintenance An increase in temperature of 10 C typically increases maintenance respiration by a factor of about 2 Kase and Catsky 1984 Penning de Vries and Van Laar 1982 However to be more flexible the user may specify the increase factor of the respiration rate per 10 C temperature increase Qio Tyg 725 avg Ro Fines Rmret Qro i 7 20 where Rn is the actual maintenance respiration rate kg ha d It may be assumed that the vegetation will not be self consuming in terms of carbohydrates Therefore the maintenance respiration rate cannot exceed the gross assimilation rate The net assimilation rate Ane kg ha d is the amount of carbohydrates available for conversion into structural material A A R with A 20 7 21 gross m 7 3 7 Dry matter partitioning and growth respiration The primary assimilates in excess of the maintenance costs are available for conversion into structural plant material In this conversion process CO and H5O are released The magnitude of growth respiration 1s determined by the composition of 158 Alterra Report 1649 update02 Development stages E emergence flower initiation flowering fruit set fruit ripening pollination fruit filling 6 vegetative stage i reproductive stage D H 2 j Q a S E E 2B Figure 7 5 Typical
297. opy According to Goudriaan 1977 the reflection coefficient Pray of a green leaf canopy with a random spherical leaf angle distribution equals p l 1 6 2 7 10 IeWi o 141 6 sin Byn l with Ojear the scattering coefficient of single leaves for visible radiation which is taken to be 0 2 The first right hand side term of Eq 7 10 denotes the reflection of a canopy of horizontal leaves and the second term is the approximate correction factor for a spherical leaf angle distribution The fraction 1 Praa of the incoming visible radiation is available for absorption by the canopy Light intensity adjusted for crop reflection decreases approximately exponentially with leaf area index when going deeper into the canopy Alterra Report 1649 update02 153 PAR 1 p PAR e 7 11 where L is the cumulative leaf area index XLAI m leaf m ground counted from the top of the canopy downwards PAR is the net light intensity J m d at depth L and is the radiation extinction coefficient The profiles of the net diffuse flux and the net flux caused by direct irradiance can be characterized analogously Goudriaan 1982 Diffuse and direct fluxes each attenuate at a different rate and both extinction coefficients are input in SWAP For a random spherical leaf angle distribution the extinction coefficient of the direct flux component Kair might be approximated by Goudriaan 1977 1982 Kair 223 7
298. orage cm cm dsup external supply to the control unit em cm d ais discharge from control unit cm em d ddrain regional drainage flow cm cm d daaxn bypass flow through cracks of a clay soil to drains or cm cm d ditches Qrnott surface runoff runon cm cm d The regional surface water storage Vou cm cm is the sum of the surface water storage in each order of the surface water system Voir A 6 2 eg i l in which Aye is the total area of the sub region cm l the total length of channels drains of order i in the sub region cm and Aa is the wetted area of a channel vertical cross section cm The wetted area Aa is calculated from the surface water level sur the channel bed level the bottom width and the side slope Substitution of Eq 4 22 in Eq 5 2 yields the expression Asi Var gt bye sur 2 L Channels of order i only contribute to the storage if sur gt Zbeai The storage in tile drains is neglected SWAP calculates the net discharge qais qsup for a given timestep and for specified surface water levels o7 and 97 sur Alterra Report 1649 update02 97 Vo d ui us 5 dais sup At iy darain F d erackfi m d runoff 5 4 If the sum of the terms on the right hand side is positive discharge has taken place and the supply is equal to zero If the sum is negative supply has taken place and the discharge is equal to zero The drainage flux is calculated by n
299. owmelt water routed directly into the macropores at the soil surface at a given precipitation irrigation snowmelt intensity P cm d is calculated as oap 6 25 where Amp cm cm is the horizontal macropore area fraction at the soil surface which equals Vinp o cm cm the total macropore volume fraction at soil surface For macropore domain dm subscript dm mb or ic this direct infiltration reads Do A P with A P V dm 0 mp 0 6 26 pr dm where Pamo is the volumetric proportion of domain dm at the soil surface In case of a snowpack on top of the soil surface it is assumed that the macropores are sealed off from the atmosphere and consequently Jp 0 except when snowmelt occurs Infiltration rate term Zu occurs when the head boundary condition holds for the top boundary of the soil matrix see Section 2 7 3 1 In that case the water balance of the ponding layer is calculated which includes u Ponding occurs when the total of precipitation irrigation snow melt runon and inundation intensity exceeds soil matrix infiltration capacity Runoff into the macropores is described in the same form as used for regular runoff to surface water or adjacent fields Section 4 1 to allow for similar incorporation into the numerical solution of the top boundary Eq 2 34 and 2 36 p 6 27 where ho cm is the pressure head at the soil surface that equals the ponding height and yr d is the resistance for macro
300. p approach requires canopy and air resistan ces which are not yet available for many crops Therefore at present SWAP follows a two step approach The first step is calculation of potential evapotranspiration using the minimum value of the canopy resistance and the actual air resistance as shown in Section 3 3 In the second step actual evapotranspiration is calculated taking into account reduction of root water uptake due to water and or salinity stress this section and reduction of soil evaporation due to drying of the top soil next section see Fig 3 3 The maximum possible root water extraction rate integrated over the rooting depth is equal to T cm d which is governed by atmospheric conditions and plant characteristics Taking into account the root length density distribution Bouten 1992 the potential root water extraction rate at a certain depth Sp z d is calculated by Loa 2 T 2 67 EE 7 Dy S 2 where Droot is the root layer thickness cm Stresses due to dry or wet conditions and or high salinity concentrations may reduce S z The water stress in SWAP is described by the function proposed by Feddes et al 1978 which is depicted in Fig 3 4 In the range h3 lt h lt hz root water uptake is optimal Below hs root water uptake linearly declines due to drought until zero at ha wilting point Above hz root water uptake linearly declines due to insufficient aeration until zero at h The critical
301. p J l p YAz Az J p OK E Az Ki iA OK j 1 z j 1 j l oh p AZ Az Kj p oh p A relation for the conductivity derivative to the pressure head QA h 1s given by OK _ OK 08 Oh OS Oh Where Alterra Report 1649 update02 239 1N 1 m 1 1 SS Js ies ear a The coefficients of the Jacobian are given by OF KIE K OK T n A npo 1 Oh YA Az Az Ohne V Az Az LER e Cu HARE QI AR i Oh P YA Az Az Y2 Az Aaa OK 9er pi ES pi OK Tee pi IK hi K stk Oh VA Az Az ohne Ya Az Az a OF K ee OK ee p uk ed a K zd 1 Oh VA Az AZ 1 Oh NVA Az Azia 240 Alterra Report 1649 update02 Appendix 6 Numerical solution heat flow equation The discretized form of the heat flow equation as described in Chapter 9 is Gr r I a Ati A6 1 ju ju j l j l y ire T i T PUDE T T T Az i Ve i Ve i Az Az where for notational convencience the subscript heat of thermal conductivity A and soil heat capacity C is omitted Equation A6 1 can be rewritten as At AZ AZ At Az AZ J j Verp j l jtte At itv diy T T c Mie i u j Aa Tit ANO y CT A6 2 i i Az Az i e itl i i i L Application of Eq A6 2 to each node results in a tri diagonal matrix p Yi Ti a p Y2 e h a B Y3 T fh A6 3 1 Qa pa Ya To dei a p ee Ti where n is the number of no
302. partitioning of assimilated dry matter among leaves stem roots and storage organs as function of development stage the end product formed Penning de Vries et al 1974 Thus the weight efficiency of conversion of primary photosynthates into structural plant material varies with the composition of that material Fats and lignin are produced at high costs structural carbohydrates and organic acids are relatively cheap Proteins and nucleic acids form an intermediate group At higher temperatures the conversion processes are accelerated but the pathways are identical Spitters et al 1989 Hence the assimilate requirements do not vary with temperature In the vegetative stage the increase in total dry weight of the crop is partitioned over the plant organs roots leaves stems and storage organs Storage organs however may not only be formed from current photosyntheses but also from carbohydrates and proteins that have been stored temporarily in vegetative parts and that are redistributed during the reproductive stage In the model the latter process is not incorporated The total growth of the crop is partitioned among the plant organs according to partitioning factors that are introduced as forcing functions their values only change with the development stage of the crop Alterra Report 1649 update02 159 In WOFOST average crop specific conversion factors Cei kg kg should be specified for leaf storage organ stem and root bio
303. pdate02 where A is the relative crack area cm cm For the drainage boundary condition during drainage drain gt 0 the solute flux Jarain g cm that leaves the one dimensional soil profile is accumulated for each compartment below groundwater level J cain Qin i Ci 8 19 where gm is the compartment with the groundwater level and qq is the lateral drainage flux cm d of compartment i During infiltration qan lt 0 Jarain follows from J arain m 2 rain Cor 8 20 T Dowl where c is the average solute concentration in the groundwater g cm For the bottom boundary condition SWAP uses the flux through the bottom of the soil profile quo cm dy In case of upward flow qbo gt 0 the solute flux Jpor g cm positive is upwards equals Jo Qoo Cg 8 21 If quo is directed downwards quo lt 0 the solute flux Jpo g cm equals Jy e Qoo Cn 8 22 8 4 Crack solute transport In order to calculate solute transport in combination with macropore flow SWAP may generate soil water fluxes which are input to the pesticide model PEARL or the nutrient model ANIMO 8 5 Residence time in the saturated zone In the case of heterogeneous groundwater flow or multi level drainage the residence time approach described in Chapter 4 is used This section describes an alternative concept assuming a homogeneous aquifer and field drainage at one level Ernst 1973 and Van Ommen 1985 showed that the
304. ping or field investigation Z could be taken at or some decimetres above the mean annual lowest groundwater table Processes leading to the presence of static macropores like ripening of clay and peat soils and biological activities like soil penetration by plant roots worms insects and small mammals will very likely be limited to this depth Zi might be found at the depth of a clear shift in macropore density by investigation of a vertical soil profile in a pit or by taking relatively large soil samples e g 20 cm diameter and 10 20 cm height Information about macropore volume to obtain a value for static macropore volume fraction at soil surface Vso VIMpStSs in Box 6 1 and the distribution of macropore volume with depth can be obtained by comparing pore volume of large samples with fitted values for 0 4 of the original unmodified Mualem Van Genuchten functions The latter expresses the pore volume of the soil matrix while the first may comprise macropore volume as well Parameters which are relevant for the distribution of macropore volume with depth PpIcSs NumSbDm PowM DiPoMi DiPoMa and optional RZah SPoint SwPowM ZDiPoMa may be derived from inverse modelling of field experiments on tracer transport with dye conservative solutes or isotope tracers To illustrate the concept of the effective polygon diameter in case of combinations of cracks and hole shaped macropores in the field we consider the following equation 1 L
305. piration and potential transpiration T T gt as reduction coefficient Reduction due to low minimum temperatures water stress and salinity stress and taking into account that for each kg CO 30 44 kg biomass CHO is formed results in the following daily gross assimilation rate A gross Kg ha d 30 T 4 gross 44 Jimin T 4 dos Alterra Report 1649 update02 157 7 3 6 Maintenance respiration Some of the carbohydrates formed are respired to provide energy for maintaining the existing bio structures This maintenance respiration consumes roughly 15 30 of the carbohydrates produced by a crop in a growing season Penning de Vries et al 1979 This underlines the importance of accurate quantification of this process in the model WOFOST estimates the maintenance costs using the approach proposed by Penning de Vries and Van Laar 1982 assuming that the reference maintenance requirements Rmrer kg ha d are proportional to the dry weights of the plant organs to be maintained Ru Ga E TF Oan ct Cua m stem stem m stor stor m root root 7 19 mref where cm denotes the maintenance coefficient of organ i kg kg d and W the organ dry weight kg ha The maintenance coefficients should be specified by the user The maintenance respiration rate still has to be corrected for senescence and temperature The reduction factor for senescence fi is crop specific and is defined as a function of devel
306. plication depth may be applied as an observed gross irrigation dose Interception of irrigation water may occur dependent on the type of application surface irrigation or sprinkling I 1 E 11 1 where 12 is the net amount of irrigation water cm d I is the gross given amount of fixed irrigation water cm d E is the amount of intercepted irrigation water cm d The interception irrigation water E is assumed to evaporate within the same day as the day of irrigation 11 2 Scheduled irrigation regime A specific combination of timing and depth criteria is valid from a user defined date in the growing season until the end of crop growth Both timing and depth criteria may be defined as a function of crop development stage Scheduled irrigation only occurs when a crop is present 11 2 1 Timing criteria For the timing of the irrigation schedule one out of five different criteria must be selected e Allowable daily stress e Allowable depletion of readily available water in the root zone e Allowable depletion of totally available water in the root zone e Allowable depletion amount of water in the root zone e Critical pressure head or moisture content at sensor depth Alterra Report 1649 update02 201 At the start of each day the selected criterion is evaluated based on state variables at the start of the day The outcome of this evaluation may generate an irrigation event on that same day In addition the user may
307. plied for soil profiles with deep groundwater levels The bottom flux is only provoked by gravity flow and the head pressure gradient equals Zero 1 Oh d Qbor t gt don K 2 46 n4 Substitution into Eq 2 30 yields 1 1 F 5 oi oj KJ hi a 1 K S n Ati n n ny VA AZ 1 Az n Y 2 47 tazsie si gi 42 Alterra Report 1649 update02 2 8 User instructions 2 8 1 General Box 2 1 shows the general input with regard to soil water flow The initial soil moisture condition Part 1 is defined by the soil water pressure head Initial values can by specified as function of soil depth with linear interpolation between depths or can be calculated assuming hydrostatic equilibrium with a groundwater level A third option is to use the output of an earlier SWAP simulation This option is very useful when no data are available of the initial soil moisture condition Part 4 describes the vertical discretization of the soil profile In addition to the natural soil layers with different hydraulic functions the thicknesses of the calculation compartments should be defined For correct simulation of infiltration and evaporation fluxes near the soil surface the compartment thickness near the soil surface should be X 1 cm Deeper in the soil profile where the soil water flow is less dynamic the compartment thicknesses may increase to 10 cm Subsequently in part 5 the hydraulic parameters of each distinct soil
308. poration irrigation salinization simulation model soil water solute transport surface water management transpiration vadose zone ISSN 1566 7197 This report is available in digital format at www alterra wur nl A printed version of the report like all other Alterra publications is available from Cereales Publishers in Wageningen tel 31 0 317 466666 For information about conditions prices and the quickest way of ordering see www boomblad nl rapportenservice O 2009 Alterra P O Box 47 6700 AA Wageningen The Netherlands Phone 31 317 474700 fax 31 317 419000 e mail info alterra wur nl No part of this publication may be reproduced or published in any form or by any means or stored in a database or retrieval system without the written permission of Alterra Alterra assumes no liability for any losses resulting from the use of the research results or recommendations in this report Alterra Report1649 02 Swap32 Theory description and user manual doc August 2009 Contents Preface Summary 1 Model overview 1 1 1 2 1 3 1 4 1 5 1 6 1 7 Model domain and processes SWAP installation Model input Model run Model output Example run Hupsel catchment Reading guide Soil water flow 2 1 232 2 3 2 4 2 5 2 6 2 7 2 8 Basic equations Soil physical relations Modification for near saturation conditions Hysteresis Frozen soil conditions Lower boundary Numerical implem
309. pore inflow at the soil surface The macropore inflow resistance is estimated from the maximum ponding height Ao max assuming no runoff either into macropores or regular and the vertical hydraulic conductivity of the macropores at soil surface Kyermp cm d The latter is derived as a function of effective macropore width at soil surface from a theoretical slit model presented by Bouma and Anderson 1973 3 Ww h Omax with K 14 4 108 6 28 Iru ver mp E unos d pol 0 Alterra Report 1649 update02 125 It can be seen that even the lower limit of macropore width 100 um yields large conductivities in the order of 100 1000 cm d and consequently very low inflow resistances of 0 001 0 01 d This implies that ponding water is routed preferentially into macropores To account for the micro relief at the soil surface mostly a threshold value for ponding height is used that must be exceeded before regular runoff starts It is assumed that this does not apply to runoff into macropores because it is very likely that micro depressions at the soil surface are connected to macropores As a consequence runoff into macropores is favoured over regular runoff and thus Yru is not a very sensitive variable Distribution of over MB and IC domains is according to their proportions at the soil surface Pao and Pico Lateral infiltration into the unsaturated matrix qu Lateral infiltration of macropore water into the unsatura
310. proportional to the pore water velocity v q 0 Bolt 1979 Da L dis v 8 5 with Lais the dispersion length cm Unless water is flowing very slowly through repacked soil the dispersion flux is usually much larger than the diffusion flux Alterra Report 1649 update02 175 The total solute flux J g cm d is therefore described by JS oon HS gy Sais qc 6 D AS 8 6 Z 8 2 2 Continuity and transport equation By considering conservation of mass in an elementary volume we may derive the continuity equation for solute transport gc S 8 7 Ot pr c with X being the total solute concentration in the soil system g cm and S the solute sink term g cm d accounting for decomposition and uptake by roots The solutes may be dissolved in the soil water or may be adsorbed to organic matter or to clay minerals X 0c p 0 8 8 with py being the dry soil bulk density g cm and O the amount adsorbed g g The adsorption isotherm describes the amount of solutes adsorbed in equilibrium with the dissolved concentration At this stage we will assume instantaneous equilibrium between c and Q and use the non linear Freundlich equation which is a flexible function for many organic and inorganic solutes Freundlich adsorption can be written as ref Q Kc 8 9 with Ke the Freundlich coefficient cm g Ns is the Freundlich exponent and Cref is a reference value of the solute concentratio
311. ption following Von Hoyningen Hiine 1983 and Braden 1985 They proposed the following general formula for canopy interception Fig 3 2 ET 2 52 gross a LAI where P is intercepted precipitation cm d LAI is leaf area index Peross is gross precipitation cm d a is an empirical coefficient cm d and b represents the soil cover fraction For increasing amounts of precipitation the amount of intercepted precipitation asymptotically reaches the saturation amount aLAT In principle a must be determined experimentally and should be specified in the input file In case of ordinary agricultural crops we may assume a 0 025 cm d The coefficient b denotes the soil cover fraction and when LAT is given b is estimated by SWAP as K LA b l e m 2 53 where b denotes the soil cover fraction and kz is the extinction coefficient for solar radiation 10 ADU 0 Maximum a LAI 4 0 4 Gash with p 0 32 p 0 02 S 0 8 mm e 3 0 Prean 1 38 mm hi En E Enen 0 19 mmh E P 1 359 mm xd 2 0 Von Hoyningen H ne and Braden witt o a 0 25 mm a b 1 00 o 5 0 0 0 5 10 15 20 Precipitation Pross mm Figure 3 2 Interception for agricultural crops Von Hoyningen H ne 1983 Braden 1985 and forests Gash 1979 1985 54 Alterra Report 1649 update02 In case irrigation water is applied with sprinklers SWAP will simulate separately interception of
312. q 6 19 Parameter values concern parameters of Eq 6 19 Void ratio e cm cm 103 8 7 E 9 61 E 2 nS J 9 4 2 41 a J 8 4 S E e 2 2 g 2 QU a 0 60 gt a b 3 90 2 P 0 79 ot r r T r r 0 2 4 6 8 10 Moisture ratio J cm cm Void ratio cm cm Description organic matter and clay content mass of the peat soils Figures in sample E 9 codes refer tot sample depths in cm E Sample Soil Org Clay e code description matter A 15 peaty clay 33 40 E A 25 clayey peat 62 21 A 45 sphagnum 93 1 peat D 80 wood peat 81 N 80 sphagnum 91 2 5 peat 5 V 10 peaty sandy 18 17 5 clay o J 2 33 1 J 1 80 w 14 di 2 21 Ja 1 62 Z 10 clayey peat 48 36 E e 0 52 Bed 1D Z 60 wood peat 82 gt 05 a 0 70 0 57 a 1 00 b 3 73 b 1 90 Z 80 wood peat 83 4 P 0 13 P 0 07 0 05 1 15 2 25 0 05 1 15 2 Moisture ratio cm cm Moisture ratio cm cm Alterra Report 1649 update02 253 254 Alterra Report 1649 update02 Appendix 12 List of input array lengths The array lengths of input data are defined as parameters in the Fortran file param fi The array lengths can be enlarged by adjusting the values in param fi en recompilation of the Fortran code In the internet version of WAP we did define the array lengths as listed in the Table below Code MAYRS MAXDAT MACROP MACP MADR MAHO MABBC MASCALE MRAIN MAIRG MAOUT MAOWL MAWLP MAWLS MAM
313. r dependent resistances and simulated drainage levels In most applications the control unit involves the primary watercourse the largest canals with the deepest channels beds An option is available to specify that the primary watercourse e g a large river functions separately from the other watercourses within the sub regional surface water system In that case the primary water courses have their own surface water level which should be specified in the input In the real situation there may be some interaction between the primary water course and the control unit for instance a pumping station for removal of drainage water and or an inlet for letting in external surface water supply Figure 4 4 The hydraulics of such structures are not included in the model Conveyance processes within the surface water devices are not described Contrary to the model option described in Par 4 3 5 the influence of the surface water level on drainage resistances can be accounted for by distinguishing two parts of the resistance 1 a part independent of the surface water level and 2 a part that is adjusted by the level For the drainage case Alterra Report 1649 update02 83 0 drain i Y drain i Y drain i Yentr i 4 4 drain i And for the sub infiltration case Toa 0 drain Tin li Yintili Yexiti 4 5 drain i Where E and y are the level independent parts of the drainage and infiltration resistance and resp
314. r of soil matrix polygones per compartment m 0 001 10 0 R DiPoCp numnod 1 NUMNOD Initial conditions The following variable theta and tempi are given for the compartments 1 numnod Volume fraction moisture initially present in compartments 1 m m 0 0 1 0 R Theta numnod NUMNOD Initial groundwaterlevel m surf 0 0 E R Gwl negative below soil surface when positive use Pond Storage by initial ponding m 0 0 s R Pond Storage by snow m 0 0 d R Ssnow Soil temperature of compartments 1 NUMNOD C 50 0 50 0 R Tsoil numnod Initial conditions for macropores domain 1 Main Bypass Flow domain Water level m surf 0 0 E R WaLevDm1 Areic volume m m 0 0 2 R VIMpDm1 Areic volume of water stored m m 0 0 R WaSrDm1 Initial conditions for macropores domain 2 Internal Catchment domain Areic volume m m 0 0 R VIMpDm2 Areic volume of water stored m m LO gt R WaSrDm2 262 Alterra Report 1649 update02 Description of variable Dynamic part Time Julian daynumber in hydrological model 1 0 means 1st of January 24 00 hour Stepsize of time interval for dynamic hydrological data Rainfall water flux Snowfall water flux Irrigation flux Evaporation flux by interception of precipitation water Evaporation flux by interception of irrigation water Sublimation of snow Evaporation flux Actual evaporation flux by bare soil Evapo
315. r storage capacity The first row contain zeros indicating that irrespective the conditions the minimum target level should never drop below that level Table 5 1 Example of a water management scheme with Psurtar as the target level the groundwater level criterium Pargmasy the pressure head criterium ya and the soil water storage criterium V uns min Cur tar cm Dave max cm fmax cm V uns min cm 180 0 0 0 160 80 100 1 5 140 90 150 2 0 120 100 200 2 5 100 120 250 3 0 80 130 300 4 0 100 Alterra Report 1649 update02 To avoid the target level reacting too fast on the prevailing groundwater level a maximum drop rate parameter has been introduced specifying the maximum permitted change of the target level per time unit cm d The limitation of the target level change can become effective in periods with surface water supply combined with a rising groundwater level In periods with heavy rainfall and high discharge the maximum capacity of a soil moisture controlled weir can be reached and the crest level will drop to its minimum level Then the surface water level is not controlled by any of the criteria mentioned before any longer but will be a function of the discharge characteristics of the surface water infrastructure Therefore the management scheme of a soil moisture controlled weir should always be combined with a table defining a stage discharge relationship This tabulated relationship should be defined
316. r time step is calculated as T T b age Sose acis where fage Physiologic ageing factor for leaf age increase T Daily average temperature C Tease Lower threshold temperature for physiologic ageing C The lower threshold temperature for physiologic ageing T age acronym tbase is crop specific and should be provided by the user The integral of the physiologic ageing factor over time yields the physiologic age Po P f At age t age t l age 274 Alterra Report 1649 update02 where Paget Physiologic age at time step t d fage Physiologic ageing factor for leaf age increase At time step d Leaves may attain the age defined by the crop specific life span acronym span however they can not exceed it In Grass the leaf class age is checked the first class younger than the defined life span becomes the oldest class Note that death of old leaves takes place after ageing being the result of the daily shifting from one leaf class to the next In this way the life time of leaves is the maximum number of days that a leaf class contributes to the LAI and to photosynthesis The leaf death rate due to water stress is calculated as T AW W a cade T where AW Leaf death rate due to water stress kg ha d fmax v Maximum relative leaf death rate due to water stress kg kg d Wy Leafdry matter weight kg ha Ta Actual transpiration cm d Tp Potential transpiration cm
317. rage in profile Groundwater level Water balance error Log file SWAP log Echo of input swp file Errors and warnings Cumulative solute balance sba Flux at soil surface Amount decomposed Amount taken up by plant roots Amount in soil profile Amount in cracks Flux at soil profile bottom Drainage flux Bypass flux from cracks Amount in defined saturated aquifer Flux from defined saturated aquifer Soil temperatures ate Soil temperature of all nodes Soil profiles vap Profiles of water content pressure head solute concentration temperature water flux and solute flux Irrigation irg 4 Calculated irrigation applications Detailed crop growth crp Development stage Leaf area index Crop height Rooting dept Cumulative relative transpiration during DVS 0 2 and 1 2 Cumulative potential and actual weight of dry matter Cumulative potential and actual weight of storage Optional files are denoted with Simple crop growth crp Development stage Leaf area index Crop height Rooting depth Cumulative relative transpiration Cumulative relative crop yield Transpiration stress str Potential and actual transpiration Transpiration reduction due to wet dry saline and frost conditions Extended drainage components drf Drainage fluxes of each level Total drainage flux Net runoff Rapid drainage Surface water management 1 swb 4 Groundwater level Weir target level
318. ration flux by ponding Potential evaporation flux by soil Potential transpiration flux Flux of surface Runon originates from other source field Flux of surface Runoff negative value means inundation Groundwater level at end of time interval negative below soil surface when positive use Pond Storage by ponding at soil surface at end of time interval Storage by snow at end of time interval Error in Water Balance Unit m surf m m m Range R 0 0 1 0 30 0 0 0 i 0 0 0 0 i 0 0 0 0 A 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 DT YD D DD D D Xm I I J D D R R Mnemonic Daycum period Igrai Igsnow Igrid lerai leirr ISubl levap lepnd Ipeva Iptra Irunon Iruno Gwl Pond SSnow Wbalance The variables h ingdra are given for the compartments 1 numnod with one exception for inq which is given for the compartments 1 numnod 1 Suction pressure head of soil moisture negative unsaturated Volume fraction of moisture at end of time interval Actual transpiration flux Flux incoming from above compartments 1 numnod 1 positive downward cm m m md md i 0 0 1 0 0 0 a aed R DDD h numnod theta numnod inqrot numnod ing numnod 1 The presence of valu
319. re geometry Hijmans R J I M Guiking Lens and C A van Diepen 1994 User s guide for the WOFOST 6 0 crop growth simulation model Technical Document 12 Winand Staring Centre Wageningen The Netherlands 144 p Hillel D 1980 Fundamentals of soil physics Academic Press San Diego CA 412 p Hooghoudt S B 1940 Algemene beschouwing van het probleem van de detailontwatering en de infiltratie door middel van parallel lopende drains greppels sloten en kanalen Versl Landbouwk Onderz 46 B 193 p Hoogmoed W B and Bouma J 1980 A simulation model for predicting infiltration into a cracked clay soil Soil Sci Soc Am J 44 458 461 Homaee M 1999 Root water uptake under non uniform transient salinity and water stress PhD thesis Wageningen University 173 p Hopmans J W and J N M Stricker 1989 Stochastic analysis of soil water regime in a watershed J Hydrol 105 57 84 Hopmans J W K C Roy and W W Wallender 1991 Irrigation water management and soil water hysteresis a computer modeling study with stochastic soil hydraulic properties Transactions of the ASAE 34 449 459 Hopmans J W J C van Dam S O Eching and J N M Stricker 1994 Parameter estimation of soil hydraulic functions using inverse modeling of transient outflow experiments Trends in Hydrology 1 217 242 Hornung U and W Messing 1983 Truncation errors in the numerical solution of horizontal diffusion in saturated unsaturated
320. re ky is the extinction coefficient for solar radiation Ritchie 1972 and Feddes 1978 used Kg 0 39 for common crops More recent approaches estimate Kg as the product of the extinction coefficient for diffuse visible light Kar which varies with crop type from 0 4 to 1 1 and the extinction coefficient for direct visible light Kair K KK gr Kar dir 2 64 Not always reliable figures of LAI as function of crop development are available For such cases the soil cover fraction might be a good alternative to account for the reduction of solar radiation due to crop cover 10 sc frac E E 1 p E 1 W 2 65 60 Alterra Report 1649 update02 Next the most important evapotranspiration term should be calculated the potential transpiration rate T of the dry crop which partly covers the soil During transpiration of dry crops the total energy for evapotranspiration will be distributed over and Tp SWAP assumes that the total evapotranspiration rate in periods with dry canopy corresponds to ET p as this rate is best defined Therefore Tj taking into account rainfall interception and partly soil cover follows from T ET 1 0 W frac P 2 66 3 5 Actual plant transpiration Potential and even actual evapotranspiration estimates are possible with the Penman Monteith equation through the introduction of canopy and air resistances to water vapour diffusion This direct or one ste
321. res ended at bottom A horizon OPTIONAL default 0 0 0 1 R SPoint 1 Symmetry Point for freq distr curve OPTIONAL default 1 0 0 1 R SwPowM 0 Switch for double convex concave freq distr curve OPTIONAL Y 1 N 0 default 0 Ou c4 I DiPoMi 10 0 Minimal diameter soil polygons shallow 0 1 1000 cm R DiPoMa 50 0 Maximal diameter soil polygons deep 0 1 1000 cm R ZDiPoMa 180 0 Depth below which diameter polygons is max OPTIONAL default 0 1000 0 cm R Start of Tabel with shrinkage characteristics ISOILLAY3 indicator number of soil layer as defined in part 4 1 MAHO 1 SWSoilShr Switch for kind of soil for shrinkage curve 0 rigid 1 clay 2 peat 0 2 I SWShrInp Switch for determining shrinkage curve 1 2 I 1 parameters of curve are given 2 typical points of curve given a 3 only peat intersection points of 3 straight line model given ThetCrMP Threshold moisture content below which horizontal shrinkage 0 1 cm3 cm3 R GeomFac Geometry factor 3 0 isotropic shrinkage 0 100 R ShrParA to ShrParE parameters for describing shrinkage curves E depending on combination of SWSoilShr and SwShrInp 1000 1000 R F SWSoilShr 0 0 variables required all dummies SWSoilShr 1 SwShrInp 1 3 variables required ShrParA to ShrParC rest dummies m SWSoilShr 1 SwShrInp 2 2 variables required ShrParA to ShrParB rest dummies
322. resistance s m and Fair is the aerodynamic resistance s m To facilitate analysis of the combination equation an aerodynamic and radiation term are defined ET ET ET rad aero where ET is potential transpiration rate of crop canopy cm d ET is the radiation term cm d and ET ero is the aerodynamic term cm di The radiation term equals _ A R G m XA Ya where the modified psychrometric constant kPa C is r o crop Yair E V r E lj The aerodynamic term equals PiP airC air m z aero A w A t Viir Wair Alterra Report 1649 update02 225 Many meteorological stations provide mean daily values of air temperature Tair CC global solar radiation R J m d wind speed uy m s and air humidity e kPa These basic meteorological data are used to apply the Penman Monteith equation 226 Alterra Report 1649 update02 Radiation term The net radiation R J m d is the difference between incoming and outgoing radiation of both short and long wavelengths It is the balance between the energy adsorbed reflected and emitted by the earth s surface R 1 a R Ry where a is the reflection coefficient or albedo and Ry is the net longwave radiation J m d The albedo is highly variable for different surfaces and for the angle of incidence or slope of the ground surface It may be as large as 0 95 for freshly fallen snow and as small as 0 05 for a wet bare
323. responds to a certain type of drainage system From Figure 4 6 one can infer that the drainage base of the larger channels is roughly at z 120 cm as no discharges were measured below that level The schematized arain avg relationship has transition points at mean groundwater levels of 80 and 55 cm below soil surface These transition points Alterra Report 1649 update02 81 correspond to the representative bed levels of the second and third order channels These levels could be imposed to the SWAP model as drainage levels 0 007 a measured schematized relationship qai 6 m 0 204 m 2 S 0 404 u channels of a a orders 1 2 and 3 8 z a A EEA z COUP N bed 3 55 2 0 60 oo I E channels of E orders 1 and 2 0 804 DONA IO cia 3 3 a hannels of channels o 2 1 095 order 1 9 a 1 204 bed 1 120 l l 1 0 1 0 2 0 3 0 4 0 5 0 6 Discharge q4 ai cm d Figure 4 6 Discharge qarain as function of mean phreatic surface Pave in the Beltrum area Massop and de Wit 1994 4 3 5 Multi level drainage with fixed resistances and imposed drainage levels Prior to any calculation of the drainage sub irrigation rate we determine whether the flow situation involves drainage sub irrigation or neither No drainage or sub irrigation will occur if both the groundwater level and surface water level are below the drainage base Drainage will only occur if the
324. rfaces either a wet ETwo or dry ET 0 canopy and a wet soil Eo In field conditions we deal with partly covered soils and with vegetation which is either dry or wet due to rainfall or irrigation interception We will use the uniform fluxes to derive the potential transpiration rate T and potential soil evaporation rate E for these field conditions When the crop is wet due to interception we assume that the energy available for evapotranspiration is entirely used to evaporate the intercepted water independent of the soil cover fraction This is at least valid for higher soil cover fractions At small soil cover fractions this assumption might overestimate the actual evaporation rate of intercepted water However as at small soil fractions the interception amounts are minor this seems not important Therefore the fraction of the day that the crop is wet Wirac follows from the ratio of the daily amount of intercepted precipitation P Section 3 2 and ET yo P Weae with W lt 1 0 ET 2 62 Next the potential soil evaporation rate can be derived from Epo taking into account reductions due to shade by crops and periods without evaporation when the crop is wet The most common method assumes that the net radiation inside the canopy decreases according to an exponential function Goudriaan 1977 Belmans 1983 In that case the potential soil evaporation rate E is equal to E E 1 W Ky LAI frac d 2 63 whe
325. rgence to anthesis 0 10000 C R TSUMAM 1000 0 Temperature sum from anthesis to maturity 0 10000 C R TBASE 0 0 Start value of temperature sum 10 30 C R kk KK KK KK KKK KK KKK KK KK KKK KKK KK ck ck kck ck ck kck ck ck ckck ck ck ckck ck KKK KKK KKK KKK KKK KKK KKK KKK KK KKK KKK ck k ck k ck kck k ck k RARA RARA KKK KKK KKK KKK KKK KKK KK KKK ck ck ck ck ck KKK KKK KKK KK KKK ckck ck KKK KK KKK KKK KKK KKK KKK KK KKK KKK KKK ck k ck ck ck k ck k ck k ck k KKK KKK Part 2 Light extinction KDIF 0 60 Extinction coefficient for diffuse visible light 0 2 R KDIR 0 75 Extinction coefficient for direct visible light 0 2 R ck KK RK RK RK ck ck RK KK KK AAA KARA KK RARA KKK KK KKK KKK KKK KKK KK KKK kck ck KKK KK KKK KKK ck ckck KKK KK KKK ck kck k ck k ck k KKK KK KKK KK KK KK RK RK RK RK KK KK KK KK KK KK KK KKK KK KKK KKK KKK KKK KKK KKK KKK KKK KKK KK KK KKK KKK KK KKK ck k ck k ck kck k ck k ck k ck k ck KK KKK Part 3 Leaf area index or soil cover fraction SWGC 1 choice between LAI 1 or soil cover fraction 2 If SWGC 1 list leaf area index 0 12 ha ha R as function of dev stage 0 2 R 164 Alterra Report 1649 update02 If SWGC 2 list soil cover fraction 0 1 m2 m2 R as function of dev stage 0 2 R DVS LAI or SCF maximum 36 records GCTB 0 00 0 05 0 30 0 14 0 50 0 61 0 70 4 10 1 00 5 00 1 40 5 80 2 00 5 20 End of table RR KK RK RK
326. rice 1981 Scaling of infiltration behaviour in dissimilar porous materials Water Resour Res 17 1065 1070 Yule D F and J T Ritchie 1980a Soil shrinkage relationships of Texas Vertisols I Small cores Soil Sci Soc Am J 44 1285 1291 Yule D F and J T Ritchie 1980b Soil shrinkage relationships of Texas Vertisols II Large cores Soil Sci Soc Am J 44 1291 1295 Zaidel J and D Russo 1992 Estimation of finite difference interblock conductivities for simulation of infiltration into initially dry soils Water Resour Res 28 2285 2295 Alterra Report 1649 update02 223 224 Alterra Report 1649 update02 Appendix 1 Application Penman Monteith method After Allen et al 1998 The original form of the Penman Monteith equation can be written as Monteith 1965 1981 As R G J PiPairC air sat 7 ea ET w w lj r i r A Y air r air where ET is the potential transpiration rate of the canopy mm d A is the slope of the vapour pressure curve kPa Sd Ay is the latent heat of vaporization J kg Ra is the net radiation flux at the canopy surface J m d G is the soil heat flux J m d p accounts for unit conversion 86400 s d pair is the air density kg m Cair is the heat capacity of moist air J kg C esa is the saturation vapour pressure kPa e is the actual vapour pressure kPa Yair is the psychrometric constant kPa ec Ferop 18 the crop
327. rly stage has an exponential form Alterra Report 1649 update02 271 Grass assumes that the exponential leaf growth rate continues until a closed canopy is formed i e a leaf area index of about 6 The exponential growth rate is calculated as Lao LALRL T exp t max where Lay Exponential leaf area growth rate at time step t ha ha da LAI Leaf area index at time step t ha ha RLmax Maximum relative leaf area index increase ecd T Daily effective temperature C In theory the maximum relative leaf area index increase is a function of the effective temperature For a relative wide temperature range the maximum relative leaf area index increase responds more or less linearly to temperature In Grass however a fixed value is assumed acronym rgrlai The effective temperature is defined as T max 0 T E T se where Ts Average temperature C Tbase Temperature below which physiological processes stop C During crop development the leaf area expansion is increasingly restricted by assimilate supply Branching and tillering generate an increasing number of sites per plant where leaf initiation can take place Grass assumes that during the exponential leaf area growth no leaf senescence takes place i e the dry matter growth equals the net dry matter growth rate The source limited leaf area growth rate is described by AW S ia where Es Leaf area index growth rate at time step
328. ropores In SWAP it is assumed that shrinkage enlarges the present permanent macropore volume and consequently the shrinkage volume is added up to the static volume Eq 6 3 Soil matrix shrinkage occurs in vertical and horizontal direction Vertical shrinkage leads to soil surface subsidence horizontal shrinkage to dynamic macropore volume The dynamic volume is calculated from overall and vertical shrinkage as Va Tx Va Ya 6 10 where Vs Vay and VA all in cm cm are the volume fraction of overall matrix shrinkage the dynamic macropore volume fraction and the subsidence volume fraction respectively In the present version of SWAP the vertical shrinkage does not affect the vertical coordinate system of SWAP This approach avoids numerical problems that may result from solving Richards equation for a dynamical vertical coordinate We assume that at the field scale the effects of ignoring changes of the soil matrix in vertical direction are small as compared to effects of uncertainties in other processes and input parameters However the approach of ignoring vertical changes in soil matrix does affect the calculation of the dynamic macropore volume This volume is corrected for the vertical shrinkage according to T Va Vo Ya 1 V 6 11 In this way the ratio between Vay on one hand and the matrix volume fraction and the static macropore volume fraction Vs on the other hand is consistent If static macropore volu
329. roundwater p g macropores in MB and IC domains and the various macropore water balance terms Mark that the saturated lateral exchange flux qu can occur in two directions See text for explanation of terms 5 lateral exfiltration out of the saturated soil matrix by interflow out of a zone with perched groundwater qi cm d 6 rapid drainage to drainage systems gra cm d Water balance The water balance of the MB domain for a given time interval dt t t reads t t f Sinb Sas cee Lon Qi mb a Alu mb gt Als mb dia jit 6 24 a to where Ziftop z 0 Zuns bot Kim Gum 25 duas Rada dus As mb AZ 6 24 b Zif bot Zuns bot Zprof bot All balance terms are positive except qi which is positive in case of infiltration into the matrix and negative in case of exfiltration out of the matrix The storage term is always less than or equal to the actual macropore volume All flux densities q are defined per unit of depth cm cm d Depths Zigtop Zif bot Zuns bot AN Zprof bot Cm refer to top and bottom of interflow zone and bottom of unsaturated zone and soil profile respectively 124 Alterra Report 1649 update02 The water balance calculation of the IC domain is equal to that of the MB domain with the exception of the rapid drainage term Per definition rapid drainage occurs exclusively in the MB domain Inflow at soil surface Lp and I The rate fp of precipitation irrigation and sn
330. s In part 3 either leaf area or soil cover during crop development should be specified in order to distribute evapotranspiration fluxes over evaporation and transpiration as discussed in Chapter 3 In part 4 a choice should be made between input of crop factors or crop heights Crop factors should be used when ET values are used as input or when the Penman Monteith method is used to calculate ET ef Crop heights should be specified if the potential evapotranspiration fluxes are derived directly for the actual crop see Table 3 2 In that case also the reflection coefficient and stomatal resistance of the crop should be defined Rooting depth during crop development part 5 in combination with a dimensionless root length density distribution part 10 will be used by SWAP to determine the distribution of rootwater extraction rates Alterra Report 1649 update02 163 In part 6 yield response factors as function of development stage should be specified In case of a linear relation between Y Y and T T during the whole growing period or when no information is available of the yield response factors as function of development stage D for the particular crop specify Kyx 1 for 0 lt D lt 2 and specify one growing stage k Please note that increasing the number of growing stages reduces the relative yield as calculated by Eq 7 1 Part 7 describes the reduction function of root water uptake for either too wet or too dry conditions
331. s Crop development Snow and frost Light extinction Numerical solution of Richards equation Leaf area index or soil cover fraction e Lateral drainage section Crop factor or crop height optional name of file with drainage input data rooting depth optional name of file with runon input data yield response e Bottom boundary section soil water extraction by plant roots optional name of file with bottom boundary salt stress conditions interception selection out of 8 options Root density distribution and root growth e Heat flow section e Calculated Irrigation section calculation method General Solute transport section Irrigation time criteria Specify whether simulation includes solute Irrigation depth criteria transport or not Top boundary and initial condition File with drainage data dra Diffusion dispersion and solute uptake by roots e Basic drainage section Adsorption Table of drainage flux groundwater level Decomposition Drainage formula of Hooghoudt or Ernst Transfer between mobile and immobile water Drainage and infiltration resistances volumes if present e Extended drainage section Solute residence in the saturated zone Drainage characteristics Surface water level of primary and or secondary system Simulation of surface water level Weir characteristics Alterra Report 1649 update02 19 Box 1 3 Example of input according to TTUTIL in main file SWP General data
332. s Xmn for component m particles suspended in the continuous phase n phase depend on the ratio of the specific thermal conductivities of component m and n and on the shape of m particles in the direction of the temperature gradient When we assume the particles to be spheroids whose axes are randomly oriented in the soil Ten Berge 1986 the weighting factors can be calculated by 2 1 Um 7 3 38 kn k 1 5 3 1 k k 1 1 2g 9 12 Alterra Report 1649 update02 187 The shape factors and weights calculated using Eq 9 12 are given in Table 9 2 For dry soil 0 lt 04 air is considered as the continuous phase and the conductivity is given by 1 25 X and air Faia na LER aay Nany A organic air dus ebat X er aie A water Nan aen 9 13 xu f water air air air air A heat X and air sand X scc day Anoa A gie x which is similar to Eq 9 11 with an empirical correction factor In the case that neither water nor air can be considered as the continuous phase 04 lt 0 lt Owet Anear is found by interpolation between values at the wet and dry limits Meat Ova z A heat 04 Ova 70 Area 0 Apear 84 0 UM 9 14 wet dry The values of Qay and Oye are taken as 0 02 and 0 05 respectively We refer to De Vries 1975 and Ten Berge 1986 for more detail on the calculation of Anea and further references Table 9 2 Shape and weight factors for different component
333. s in water and air phases as used for thermal conductivity calculations Ashby et al 1996 Component Sand Clay Organic Water Air Shape factor Esand Eclay Sorganic E water Zair 0 14 0 00 0 50 0 14 0 05 Weight factor for water Xsand water Xclay water Xorganic water Xwater water Xair water as continuous phase 0 2474 0 7244 1 2476 1 0000 3 0592 Weight factor for air Xsand air Xelay air Xorganic air Xwater air Xair air as continuous phase 0 0145 0 6628 0 4500 0 1826 1 0000 At the soil surface either the daily average air temperature Tavg or measured soil surface temperatures can be used as boundary condition In case of a snow layer and the use of Tag SWAP will adjust Tay as described in Chapter 10 At the bottom of the soil profile either soil temperatures can be specified or que 0 0 can be selected The latter option is valid for large soil columns Application of Eq 9 4 to each node and including the boundary conditions at the top and bottom of the soil profile results in a tri diagonal system of equations as shown in 0 SWAP efficiently solves the equations with LU decomposition for tridiagonal systems Press et al 1989 188 Alterra Report 1649 update02 9 3 Analytical solution sinus wave If the values of Anea and Cheat are considered to be constant with depth and time the soil thermal diffusivity Dy cm d can be defined as eal D i i e 9 15 heat and Eq 9 3 simplifies to OF WT
334. saturation Other factors that may reduce the daily assimilation rate are typical crop characteristics unfavourable temperatures and water stress Typical crop characteristics depend on the phenological crop stage Therefore the WOFOST user should specify a maximum CO assimilation rate Amax kg CO ha d as function of development stage A reduction factor fiday which is a function of the average daytime temperature Taay C accounts for sub optimum temperatures Taay is calculated by Tiny 0 75 Teo 0 25 7 16 min where Tmax and Tmin CC are the daily maximum and minimum temperature respectively The shape of the reduction function is entered as a table in WOFOST The crop characteristics and temperature effect reduce Apeross to Apgross Kg CO ha d A sd max Ass J s 2 Aue 7 17 In addition low nighttime temperatures affect assimilation At night assimilates produced during daytime are transformed into structural biomass This process is hampered by low temperature If these low temperatures prevail for several days the assimilates accumulate in the plant and the assimilation rate diminishes and ultimately halts In the model this temperature effect is accounted for by a reduction factor fimin Which is a function of the minimum temperature during the previous seven days Other important factors that may reduce assimilation are water and salinity stress WOFOST uses the ratio of actual trans
335. shold 1 0 Threshold value 0 0 20 0 mm R Select optional minimum time interval 0 t tcsfix Switch minimum timing criterion 0 or 1 I If tcsfix 1 specify irgdayfix 7 minimum length of interval between irrigations 1 365 d I 206 Alterra Report 1649 update02 Box 11 4 Scheduled irrigation depth criteria in the CRP file IRRIGATION SCHEDULING part 3 KK KK KK KK KK KK KKK KKK KK KK KK KKK KK KKK KKK KKK KKK KKK KKK KKK KKK KKK KKK ckck ck ck KKK ck ckck ck ck ck k ck ck ckck ck ck KKK Part 3 Irrigation depth criteria Choose one of the following 2 options for irrigation depth DCS 1 Switch depth criterion sep TJ 4 1 Back to Field Capacity i 2 Fixed Irrigation Depth Back to Field Capacity DCS 1 If DCS 1 specify amount of under or over irrigation dI 100 100 mm R as function of development stage DVS dcl 0 2 R maximum 7 records DVS dcl al 0 0 10 0 2 0 10 0 End of table Fixed Irrigation Depth DCS 2 If DCS 2 specify fixed irrigation depth FID 0 400 mm R as function of development stage DVS_dc2 0 2 R maximum 7 records DVS_dc2 FID 0 0 60 0 2 0 60 0 End of table Select optional limitations of irrigation depth dcslim 0 Switch limited irrigation depth 0 No 1 Yes 05 17 T If dcslim 1 specify irgdepmin 0 0 minimum irrigation depth 0 0d0 100 0d0 mm I irgdepmax 0 0 maximum
336. simulation ended bruny l eruny Time Julian daynumber when hydrological simulation 0 0 366 0 R brund 1 started Minimum will be 0 0 when simulation started at 1st of January 00 00 hour Time Julian daynumber when hydrological simulation 0 0 366 0 R erund ended Maximum Alterra Report 1649 update02 261 Geometry of model system Number of model compartments 1 numnod l numnod Number of horizons 1 numlay l numlay Number of drainage systems O 5 l nrlevs value must be 0 1 2 3 4 or 5 The following 4 variables botcom thetawp are given for the horizons 1 numlay Compartment number of the deepest compartment bottom 1 numnod l botcom numlay of each horizon layer Volume fraction moisture at Saturation m m 0 0 1 0 R thetas numlay Volume fraction moisture at Field Capacity m m 0 0 1 0 R thetafc numlay Volume fraction moisture at Wilting point m m 0 0 1 0 R thetawp numlay The following variable dz is given for the compartments 1 numnod Thickness of compartments m 0 001 100 0 R dz numnod Geometry of macropore system Areic volume of static macropores in domain 1 Main Bypass m m 0 0 y R VIMpStDm 1 numnod Flow domain per compartment 1 NUMNOD Areic volume of static macropores in domain 2 Internal m m 0 0 Y R VIMpStDm2 numnod Catchment domain per compartment 1 NUMNOD Diamete
337. soil matrix water storage in macropores and rapid drainage to drainage systems The macropores are divided in a main bypass domain network of continuous horizontal interconnected macropores and an internal catchment domain discontinuous macropores ending at different depths The internal catchment domain causes infiltration of macropore water at different relatively shallow depth In addition the macropores are divided in static and dynamic volumes The dynamic volumes depend on shrinkage characteristics Chapter 6 The simple crop module prescribes crop development independent of external stress factors Its main function is to provide a proper upper boundary condition for soil water movement In addition SWAP includes the generic crop growth module WOFOST In this module the absorbed radiation is a function of solar radiation and crop leaf area Next the produced carbohydrates CH2O are calculated taking into account photosynthetic leaf characteristics and possible water and or salinity stress The carbohydrates provide energy for living biomass maintenance respiration and are converted into structural material during which weight is lost as growth respiration The material produced is partitioned among roots leaves stems and storage organs using partioning factors that depend on the crop development stage The fraction partioned to the leaves determines leaf area development and hence the dynamics of light interception During crop
338. solution in closed form and a series solution to replace the tables for the thickness of the equivalent layer in Hooghoudt s drain spacing formula Agricultural Water Management 19 p 1 16 220 Alterra Report 1649 update02 Van der Zee S E A T M and W H van Riemsdijk 1987 Transport of reactive solute in spatially variable soil systems Water Resour Res 23 2059 2069 Van Dobben W H 1962 Influence of temperature and light conditions on dry matter distribution development rate and yield in arable crops Netherlands Journal of Agricultural Science 10 377 389 Van Genuchten M Th and P J Wieringa 1974 Simulation of one dimensional solute transfer in porous media New Mexico State University Agric Exp Stn Bull 628 New Mexico Van Genuchten M Th and R W Cleary 1979 Movement of solutes in soil computer simulated and laboratory results In G H Bolt Ed Soil Chemistry B Physico Chemical Models Elsevier Amsterdam pp 349 386 Van Genuchten M Th 1980 A closed form equation for predicting the hydraulic conductivity of unsaturated soils Soil Sci Soc Am J 44 892 898 Van Genuchten M Th 1982 A comparison of numerical solutions of the one dimensional unsaturated saturated flow and transport equations Adv Water Resour 5 47 55 Van Genuchten M Th 1987 A numerical model for water and solute movement in and below the root zone Res Report US Salinity Laboratory Riverside CA Van Genuchten
339. t travel time approach The discharge layers are considered as horizontal layers Each layer occupies a certain part of the groundwater volume The ratio between the occupied flow volumes Vi is derived from the proportionality between flow volumes and volumetric discharge rates Mi Oan i 4 9 Via Oan i i The volumetric flux Qaraini to drainage system i is calculated as Qarain i Laraini L rain i 4 10 86 Alterra Report 1649 update02 Flow to first order drains Flow to second order drains Figure 4 7 Schematization of regional groundwater flow to drains of three different orders First order drains act also as field ditches and trenches and next higher drains act partly as third order drains In the SWAP model the lumped discharge flux per drainage system is computed from the relation between groundwater elevation and drainage resistance Figure 4 7 shows the schematization of the regional groundwater flow including the occupied flow volumes for the nested drain systems The volume Vi consists of summed rectangles LiD of superposed drains where D is the thickness cm of discharge layer i The flow volume V assigned to drains of order 1 2 and 3 is related to drain distances L and thickness D of discharge layers as follows V LD LD LD 4 11 V L D LD 4 12 V LD 4 13 Rewriting Eq 4 30 to 4 32 and substituting Eq 4 28 and Eq 4 29 yields
340. t i MS iznla poli Numerical solution For the numerical solution of Richards equation Section 2 7 2 the partial derivative of the exchange between macropores and matrix to the pressure head must be added to the total partial derivative to the pressure head For each compartment the macropore contribution to this derivative is the sum of the derivatives of all nag macropore domains j 136 Alterra Report 1649 update02 as Nami esi m i m j i l 1 p I Lp oh j l oh 6 62 where refers to the time level and p to the iteration round For the Darcy flow and seepage face fluxes qup gis and qi the derivative to the pressure head is calculated as lp l 1 p l 1 p lp OS ni HB Op or sj ad OS ji E diji 6 63 Ip o l l 1 p Ip o l l 1 p Oh hii m hus Oh hj gt hui For the absorption flux q ap the derivative to the pressure head is obtained by eg Q ihe mj Dab j i f 6 64 O anit M 9 6 thry i Oji 6 dh i where is the differential water capacity Section 2 2 i 6 3 User instructions 6 3 1 General input parameters The most important aspect of macropore flow is that precipitation water is routed into macropores at the soil surface A relatively small part of precipitation enters the macropore volume directly Inflow of precipitation excess via overland flow in case of precipitation intensity exceeding matrix infiltration rate is the dominant source of macropore inflo
341. tant time intervals CKCkckckckckckckckckckckckck ck ck ckck ck ck ckck ck ck ckck ck ck ck ck ck ck ckck ck ck ck ck ck ck ckckckckckckckckckckckckckckckckckck ck A ck ckckckck ck k ck ck a a Filename Raindetail 003 Contents Detailed meteorological data of Wageningen weather station KKKKKKKKKKKKKKKKKKKKKKKKK ck ck kc ck ck ck KKK KARA RARA AA KKKKKKKKKKKKKKKKKKKKKKKKKKKKKK Comment area Each day 10 weather records as specified in general input file KKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKK ck ck ck cock ck ck KKK ck RARA AAA KARA AAA ck ck ck kc k ko kckck ck ko kk Date Record Rad Temp Hum Wind Rain i nr kJ m2 uC kPa m s mm KKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKK KKK KK KKK KKK cock ck ck ck ko ckckckock ck kk kc kk ck ck ck ck kc k ck kckck ko kokok may 2003 may 2003 may 2003 may 2003 may 2003 may 2003 may 2003 may 2003 may 2003 may 2003 02 may 2003 02 may 2003 02 may 2003 02 may 2003 02 may 2003 o HB o o o o o ul o o oooooooo o ooooooo0oooooooo SN 000 O IP 0 48 O1 O 0 i0 O U1OUOoo0U0UoUuUUoo Np oOoOooonrn nnmvosyunmnD ooc ANaUWAIYRFPOUMUOKRNOA A OoOoooocoooooonenmnpo OoOoooooooooo IHWwi O40 bNHP O Y0 190 0 40 MN OO 0 OC 0 00 0 0100000 Box 3 4 Detailed rainfall data OK ROK OK ROK ROK RK RK ck ck ck ckckckck ck ck ckck ck ck ckck ck ck ckck ck ck ckckckck ckckckckckck ck ck ckck ck ck ckck ck ck ck ck ck ck ck Filename Raindetail 003 Contents Detailed rainfall data of
342. te02 189 Table 9 3 Thermal diffusivity Dheat cm2 d for various dry and wet soils Jury et al 1991 Sand Loam Clay Peat Dry Wet Dry Wet Dry Wet Dry Wet 147 380 156 518 156 320 112 104 A B 25 00 4 25 00 5 20 00 20 00 4 15 00 9 15 00 10 00 4 E 10 00 4 3 5 00 4 8 5 00 4 0 00 T T T T T 1 0 00 T T T T 0 00 0 50 1 00 1 50 2 00 2 50 3 00 0 00 0 50 1 00 1 50 2 00 2 50 Time days Time days Figure 9 1 Calculated soil temperatures at depths z 2 0 z 2 5 en z 2 10 cm for a dry A and a wet B sand soil The following input date were used Timean 12 C Tampi 10 C T 1d tmax 0 5 d en Dy 147 droog en 380 nat cmi d 9 4 User instructions Box 9 1 lists the input data for heat transport When the analytical method is used the parameters describing the soil surface temperature wave and the demping depth should be specified The demping depth might be derived from Eq 9 19 and the thermal diffusivity values in Table 9 3 When the numerical method is used information should be given of the soil texture initial soil temperatures and type of bottom boundary condition 190 Alterra Report 1649 update02 Box 9 1 Information on heat transport in main file SWP KKK KK KK KK KKK KA KK KK KK KK KK KK KK KK KKK KK KK kckckckckckckck k ckck ck k ck k ck k ck k ck k ck k ck k ck k ck k ck k KKK kckokck Part 1 Specify whether simulation includes heat flow SWHEA 1 Switch for simu
343. ted soil matrix takes place strictly over the depth where stored macropore water is in contact with the unsaturated matrix Two lateral infiltration mechanisms are relevant absorption of macropore water when capillary forces dominate and Darcy flow due to a pressure head gradient from macropore wall to centre of the effective matrix polygon Absorption is the dominant mechanism at low soil moisture contents It will be negligible under wet conditions even when there is a large pressure head gradient In the latter case Darcy flow will be dominant Darcy flow is very small under dry conditions because of very low hydraulic conductivities Therefore for each situation the flow rates of both infiltration mechanisms are calculated and the unsaturated infiltration flux is set equal to the largest of these two rates Lateral absorption is described with Philip s sorptivity Philip 1957 T A ass Pure 29 ab Ads P t t Vas 6 dax Va where T is the lateral absorption per unit of depth cm cm over time interval ty t d and Sp is Philip s sorptivity cm d 5 The meaning of A siis is explained in Appendix 2 Eq A2 12 Sp is a function of initial volumetric moisture content 0 cm cm at f to the time of first contact of macropore water with the matrix It is empirically described as adapted from Greco et al 1996 Sp xd Bp max 5 ace Sp max 2 3 6 30 where Sp max is the maximum sorptivity when 0 0 residual m
344. ters Specify for each soil type the soil texture g g mineral parts and the organic matter content g g dry soil ISOILLAY5 PSAND PSILT PCLAY ORGMAT maximum MAHO records 1 0 80 0 15 0 05 0 100 2 0 80 0 15 0 05 0 100 End of table If SWINCO 1 or 2 list initial temperature TSOIL 20 40 C R as function of soil depth ZH 1 0d5 0 cm R ZH TSOIL maximum MACP records 10 0 T5530 40 0 12 0 70 0 10 0 95 0 9 0 End of table Define top boundary condition SwTopbHea 1 1 use air temperature of meteo input file as top boundary 2 use measured top soil temperature as top boundary If SwTopbHea 2 specify name of input file with soil surface temperatures TSOILFILE Haarweg File name without extension TSS A16 Define bottom boundary condition SwBotbHea 1 1 no heat flux 2 prescribe bottom temperature If SwBotbHea 2 specify a tabel with dates and temperatures at bottom boundary DATET TBOT maximum MABBC records 01 jan 1980 15 0 30 jun 1980 20 0 23 dec 1980 10 0 End of table Alterra Report 1649 update02 191 192 Alterra Report 1649 update02 10 Snow and frost The SWAP model contains separate switches for simulating snow and frost conditions When these two switches are turned off in the simulations precipitation and soil water remain unfrozen at temperatures below zero C Snow is described in Section 10 1 and frost in Section 10 2 10 1 Snow
345. th depth are given in Box 4 7 and 4 8 An implicit approach for travel times distribution Section 4 4 1 requires specification of an anisotropy factor COFANI for each soil layer This factor represents the division of horizontal over vertical saturated hydraulic conductivity and will generally increase with depth The exact location of the so called discharge layers may be influenced by an adjustment of the upper boundary of the discharge layer Box 4 8 and Section 4 4 2 This adjustment requires expert judgement and it is generally not recommended to apply adjust it without thorough knowledge of the underlying processes Box 4 7 Implicit approach of travel times in drainage file DRA Ckckckckckckckckckck ck ck ckck ck KK ck ck ckck ck ck ckck ck ck ck ck ckck ck ck ck ck ck ck ckck ck ck ckck ck ck ckckckckckck ck ck ckckckck ck ckckckckckckck ck ck ck ck k ck ck ck ck ck ck ckckckckok Part 0 General SWDIVD 1 Calculate vertical distribution of drainage flux in groundwater Y 1 N 0 If SWDIVD 1 specify anisotropy factor COFANI horizontal vertical saturated hydraulic conductivity for each soil layer maximum MAHO 0 1000 R COFANI 1 0 1 0 Box 4 8 Discharge layers in drainage file DRA FO III E HE HE AE E HE OOOO IIIS III III OOOO OOOO OA Switch to adjust upper boundary of model discharge laye SWDISLAY 1 switch to adjust discharge layer 0 1 2 I SWDISLAY 1 specify for the drainage systems 1 NRLEVS
346. th infiltration runoff events during intensive rain showers or when the soil occasionally gets flooded in areas with shallow groundwater tables At moderate weather and soil wetness conditions the soil top boundary condition will be flux controlled In either very wet or very dry conditions the prevailing water pressure head at the soil surface starts to govern the boundary condition hitbe gt pi In case of a Flux controlled top boundary the term K 57 2 7 1 is V Az 4 Azj replaced by the flux through the soil surface qi cmd which yields the following expression i pi _ pit Azi git 0 n dtop a Kj l h Y Az Az F At where qop is calculated from external driving factors as net precipitation prec Ki AuS i e Az Sf A S 2 31 a l m irrigation qiri melt of a snow pack qe runon originating from adjacent fields Grunon and inundation from adjacent water courses Ginun Diop prec irri d meit 4 runon Ainun 2 32 piro piro In case of a Head controlled top boundary the term K 57 2 7 1 is Ya Az _ Azj hit E nj F replaced by Kl TAOS 1 where hf is the pressure head at the soil surface AA at the new time level The internodal conductivity K is always treated implicitly Within each iteration round and also within each backtracking sub cycle it is tested j l whether the combination of qrp and hj would lead
347. th rate kg ha d gwrt pot net growth rate roots kg ha d 278 Alterra Report 1649 update02 gwst pot net stem growth rate kg ha d idregr pot starting day re growth after mowing d il counter leaf age classes Ilvold pot counter leaf age classes kdif extinction coefficient for diffuse visible light kdir extinction coefficient for direct visible light lai pot total green area index leaves stems ha ha laicr critical leaf area index ha hat laiem leaf area index at emergence ha ha laiexp pot leaf area index during exponential growing phase ha ha laisum total leaf area of all leaf classes ha ha Iv pot array that contains the leaf weight classes kg lvage pot array that contains the leaf age classes d perdl maximum rel leaf death rate due to water stress d pgass pot gross daily CH2O assimilation rate kg ha d ptra potential transpiration rate cm d q10 relative increase of the respiration rate per 10 C temperature increase rdc maximum rooting depth determined by the crop cm rd pot rooting dept cm rdi Initial rooting depth cm rds maximum rooting depth determined by the soil cm relni reduction factor of the gross daily assimilation rate as relnitab table containing the gross daily assimilation factors as a function of the nitrog
348. th the specific leaf areas yielding the leaf area index growth rate of the living leaves per age class Multiplication with At and summation over the classes gives the total leaf area index The green area index of the stems and the storage organs is added to this amount The total dry matter weight of living leaves can be found in a similar way The green area index of the stems may also absorb radiation and should therefore be added to the total leaf area index The green area index of these organs can be calculated by GAI S W where GAI Green area index of stems ha ha Ss Specific stem green area ha kg W Stem dry matter kg ha However in Grass the specific stem green area acronym SSA is set to zero Leaf senescense Senescence refers to the loss of capacity to carry out essential physiological processes and to the loss of living biomass The fundamental processes involve physiological ageing and protein breakdown These processes are difficult to quantify leaves are assumed to die when they have completed their life cycle The dying rate may be accelerated by drought stress and mutual shading Physiologic ageing Leaves die when the leaf age exceeds the life span for leaves i e physiologic ageing Life span is defined as the maximum time in days a leaf can live at a constant temper ature of 35 C The concept of lifespan is compatible with a definition in terms of temperature sum The physiologic ageing factor pe
349. that many of it should fit together without any gaps to tile the plane From the regular polygons only equilateral triangles squares and regular hexagons have this quality Empirical experience points out that squares and hexagons in particular are the most likely candidates for these polygons Which of the two should be chosen is irrelevant They are both regular polygons with an even number of sides All of these even sided regular polygons from square to circle have two relevant special qualities the quotient of their perimeter divided by their area is independent of the number of sides and their area is a function of the squared diameter Effective vertical macropore wall area All even sided regular polygons with n sides are built up of n equal isosceles triangles with base of length x cm and height Y dpoi cm Fig A2 1 The perimeter of the polygon equals n times x and the area equals n times the area of the triangle The latter equals 4 dpa x cm so that erimeter nx 4 E e es A2 1 1 d n d x 4 Figure A2 1 Hexagon 6 sided regular polygon consists of 6 a isosceles triangles with area Vadpor ex dpoix Area of y N polygon 61 4 dpoix and perimeter 6 x Vertical wall N i area per unit of volume Aya 6 x 6 5 dax 4 depor X The vertical area of the wall of the polygon of Figure A2 1 per unit of depth is equal area el to the perymeter of the polygon In order to express this ar
350. the explicit scheme the time step At should meet the criterium Van Genuchten and Wierenga 1974 Az 8 At lt 2D 8 16 This stability criterium applies to non sorbing substances and is therefore also safe for sorbing substances 8 3 Boundary conditions As initial condition the user needs to specify the solute concentrations c g cm in the soil water and the average solute concentration Car g cm in the groundwater For the top boundary condition the solute concentrations in irrigation and rain water Cir aNd Corec Z cm need to be specified During evaporation no solutes leave the soil profile at the surface During infiltration the solute concentration of water that enters the soil profile at the top Cpona g cm is affected by the ponding layer and its concentration at the former time step the solute amounts coming in by rain and irrigation and the solute amounts transported laterally to cracks Pi Cpe TES oer j net prec net irr pond ae E do du Jari c 8 17 pond where Pe is the net precipitation rate cm d Inet is the net irrigation rate cm d Nyona is the height of water ponding on the soil surface qup is the water flux at the soil surface cm d positive upward and gq is the water flux flowing to cracks cm d see Section 8 4 The solute flux Jiop g cm entering the soil at the surface equals Joi diop pona 1 0 s A 8 18 178 Alterra Report 1649 u
351. the assessment of surface heat flux and evaporation using large scale parameters Mon Weath Rev 100 81 92 Raats P A C 1973 Unstable wetting fronts in uniform and nonuniform soils Soil Sci Soc Am J 37 681 685 Raes D H Lemmens P van Aelst M van der Bulcke and M Smith 1988 IRSIS Irrigation Scheduling Information System reference manual Laboratory of Land Management K U Leuven Belgium Reinink K I Jorritsma and A Darwinkel 1986 Adaption of the AFRC wheat phenology model for Dutch conditions Neth J Agric Science 34 1 13 Rijniersce K 1983 A simulation model for physical ripening in the IJsselmeerpolders Rijksdienst voor IJsselmeerpolders Lelystad The Netherlands 216 pp Rijtema P E P Groenendijk and J G Kroes 1997 ANIMO a dynamic simulation model for transport and transformation of nutrients and organic materials in soils Report 30 DLO Winand Staring Centre Wageningen in press Ritchie J T 1972 A model for predicting evaporation from a row crop with incomplete cover Water Resour Res 8 1204 1213 Ritsema C J L W Dekker J M H Hendrickx and W Hamminga 1993 Preferential flow mechanism in a water repellent sandy soil Water Resour Res 29 2183 2193 Ritsema C J and L W Dekker 1994 How water moves in a water repellent sandy soil 2 Dynamics of fingered flow Water Resour Res 30 2519 2531 Ritsema C J 1998 Flow and transport in water repellent sandy soi
352. the concept discussed here is valid for a region having any number of drainage levels only three drainage systems are considered for reasons of convenience One dimensional leaching models generally represent a vertical soil column Within the unsaturated zone solutes are transported by vertical water flows whereas in the saturated zone the drainage discharge can have a three dimensional flow pattern Van Ommen 1986 has shown that for a simple single level drainage system the travel time distribution is independent from the size and the shape of the recharge area Under these assumptions the average concentration in drainage water can mathematically be described by the linear behaviour of a single reservoir But the non homogeneous distribution of exfiltration points the variety of hydraulic properties and the influence of stratified soil chemical characteristics necessitates to distinguish between the different soil layers The distribution of drainage fluxes with depth is used to describe the travel time distribution of drainage water in an implicit manner Drainage fluxes are treated as lateral sink terms of the water balance in the SWAP model The vertical flux q in the saturated zone of the SWAP model relates to the distribution of lateral drainage rate sink terms according to dds L Gets 4 7 dy D where D is the depth of the zone for which qai has a certain value Assume that a fluid particle is at the depth of yo at time fo The tim
353. the extra head loss near the drains caused by converging flow lines Hooghoudt 1940 The numerical solution of Van der Molen and Wesseling 1991 is employed to obtain an estimate for Deg A characteristic dimensionless length scale x is used x 2g duum T Simp 4 11 Lacan where Zimp is the level of the impervious layer The equivalent depth D is approximated for three ranges of x as If x 10 Daeg Parain Zimp 4 12 D Larain eq 8 drain Zimp La ai 4 13 6 In t 4 13 If 10 lt x lt 0 5 T T Fdrain drain 7 Zimp _ Lain ed oo 2kx 8 Larai 4e 2 in drain J 4 14 If x gt 0 5 x E m P ka Case 3 Heterogeneous soil profile drain at interface between both soil layers The drainage resistance follows from Iu Yarain drain Yentr 4 1 5 8K mor Deg 4K yop Pewi O drain 76 Alterra Report 1649 update02 with Khtop and Kibot the horizontal saturated hydraulic conductivity cm d of upper and lower soil layer respectively The equivalent depth D is calculated using Eq 4 11 to Eq 4 13 Case 4 Heterogeneous soil profile drain in bottom layer The drainage resistance is calculated according to Ernst 1956 with later extensions for the entrance resistance as Yarain Y ver Y hor Y rad Yentr 4 16 where Yver Yhor Yrad ANd Yen are the vertical horizontal radial and entrance resistance d respectively The vertical resistance is calculated by Pe Z
354. the files are fixed An exception is the meteorological file which has an extension equal to the last 3 digits of the year e g 2008 gives 008 The names of the input files are free to choose and are specified in the main input file As listed in Box 1 1 the main input file contains general information with regard to the simulation meteorology crop rotation scheme irrigation soil water flow heat flow and solute transport For meteorological data commonly a file with daily data is used In Chapter 3 more detailed input of evapotranspiration and rainfall fluxes will be discussed The detailed crop growth input file is required to simulate crop development and biomass assimilation As an alternative the development of crop parameters as leaf area index or rooting depth can be prescribed in the simple crop growth input file The drainage input file contains two sections The basic drainage section provides input for drainage towards ditches and or drains The extended drainage section provides input for drainage including simulation of surface water levels Alterra Report 1649 update02 17 SWAP uses the TTUTIL library Kraalingen amp Rappoldt 2000 for reading input files Box 1 3 gives an example of a part of the swp input file General rules for the format of input files are e free format with the structure VariableName value or in a table with variable names in the first line see Box 1 3 e order of variables is fre
355. the incoming fluxes snow and rain and the outgoing fluxes melt and sublimation Figure 10 1 and reads S n Ss P P I meit d melt r E Az 10 2 snow snow in which Ssnow is storage of snow at day ft or the previous day 7 1 in cm water equivalent cm w e P and P are the two precipitation terms cm w e d qme and melt are two snow melt terms cm w e d E is sublimation of snow cm w e d and At is the time step of one day Precipitation Rain Interception ve Rain or Snow Sublimation Snowmelt Snow layer Soil layers Transport of water and heat Figure 10 1 Water fluxes to and from the snow layer Two forms of snowmelt are included in the model 1 air temperature rise above a threshold value the degree day model Kustas amp Rango 1994 Amer A T T forT gt T 10 3 4 Ine 0 for T T 10 3 b 194 Alterra Report 1649 update02 where a is the degree day factor cm C d Tay is the daily average air temperature C and T is the base temperature C which is set to 0 C according to Kustas amp Rango 1994 The value of a can be specified by the user and ranges under most circumstances between 0 35 and 0 60 cm C d 2 heat release from rainfall P on the snowpack additional melt will occur due to heat released by splashing raindrops This snowmelt rate quac is calculated with Fern ndez 1998 Singh et al 1997 PC
356. the leaf area index The green area index of the stems and storage organs are calculated from the dry matter weights of the organs 162 Alterra Report 1649 update02 GAI S W 7 32 gai i with S a the specific green area ha kg of either stems or storage organ Seai are crop specific and should be provided by the user 7 3 10 Root growth Root extension is computed in a straightforward way The user needs to specify the initial rooting depth the maximum rooting depth as determined by the crop and by the soil and the maximum daily increase in rooting depth drootmax cm Daily increase in rooting depth is equal to the maximum daily increase unless maximum rooting depth is reached or no assimilates are available for root growth Di D d if D SD and w 20 7 33 root root root max root root max net roo where Dooi is the rooting depth cm at day j 7 4 User instructions 7 4 1 Simple crop module An example of the input file is given in Box 7 1 Most data are specified as function of crop development stage which ranges from 0 to 2 In part 1 the development stage can be defined either linear in time specify only duration of crop growth or based on the temperature sums in the vegetative and reproductive stage In part 2 light extinction coefficients are used to quantify the decrease of solar radiation within a canopy Chapter 3 Default values of Kair 0 8 and Kait 0 72 will suffice in most case
357. this output file the fluxes are presented between the subdomains plant snow pond layer soil and their environment as depicted in Figure 1 3 Apart from the in and outgoing fluxes of each subdomain also the water storage and balance is depicted For instance the ponding layer received 61 49 cm rain and 7 57 cm soil water from the first soil compartment Of this amount 14 42 cm evaporated towards the atmosphere and 54 69 cm infiltrated into the first soil compartment As both the initial and final storage of the ponding layer are zero the storage change is also zero Box 1 6 Example of Result blc file for Hupsel case Project Hupsel File content detailed overview of water balance components cm File name Result ble Model version Swap 3 2 revision 10 Date 02 May 2008 Generated at 05 May 2008 15 57 05 Period 01 Jan 1980 until 31 Dec 1980 Depth soil profile 200 00 cm 4 INPUT OUTPUT PLANT SNOW POND SOIL PLANT SNOW POND SOIL 4p Initially Present 0 00 0 00 72 07 Finally present 0 00 0 00 72 19 Gross Rainfall 66 01 Nett Rainfall 0 00 61 49 Nett Rainfall 61 49 Gross Irrigation 0 05 Nett Irrigation 0 05 Nett Irrigation 0 05 Interception 4 52 Snowfall 0 00 Snowmelt 0 00 Snowmelt 0 00 Sublimation 0 0
358. tments 1 numnod Volume fraction moisture inltially present in compartments m m 1 NUMNOD Inltial groundWAterlevel m surface Storage by inltial ponding m surface m surface Dynamic part Time Julian daynumber in hydrological model Precipitation incl irrigation water flux md Evaporation flux by interception ma Actual evaporation flux by bare soil md Evaporation flux by ponding ma Potential evaporation flux by soil md Potential transpiration flux ma Flux of surface RUnoff md GroundwAter level at end of time interval m surface Storage by ponding at soil surface at end of time interval m surface Range R DT Mnemonic 0 0 1 0 R theta numnod 0 0 00 gt R gwl 0 0 00 gt R pond 0 0 00 gt 2 R tcum 0 0 00 gt R iprec 0 0 co gt R iintc 0 0 00 gt R ievap 0 0 R 0 0 0 0 00 gt R ipeva 0 0 00 gt R iptra 0 0 00 gt R iruno 0 0 00 gt R gwl 0 0 co gt R pond The variables h ingdra are given for the compartments 1 numnod with one exception for inq which is given for the compartments 1 numnod 1 Suction pressure head of soil moisture negative when cm unsaturated Volume fraction of moisture at end of time interval m m Actual transpiration flux md Flux incoming from above compartments 1 numnod 1 md downward positive 00 00 R h numnod 0 0 1 0 R theta numnod 0 0 00 gt R inqrot numnod 0 0 00
359. to hj raf E s gt 0 In Y such a case it is decided that the head boundary condition holds and the water balance of the so called ponding layer is calculated which includes the surface runoff flux and 38 Alterra Report 1649 update02 the ponding depth at time level 1 The value of f is set to the ponding depth at time level The water balance of the ponding layer reads as hj h T hj j l K L l1 4 i Qu dos Vinen 4 q I At Y YA Az prec irri melt runon inun e pond runoff ru 2 33 Where is the runoff into the macropores section 6 1 2 The surface runoff flux q 5is defined as a function of the ponding height hi ho threshold A runoff 0 2 34 j j y ho gt No threshold A runoff a ng No threshold Where a and f are coefficients of the surface runoff equation employed by the SWAP model see Section 4 1 Substitution of surface runoff expression into water balance equation for the ponding layer yields the relation which is solved in the iteration procedure Aat Kj j4 Y j l A hy E a n edad y At Ya Az hi n Kj At Az 2 35 j4 j4 EN hi Ky d prec Q nelt i d runon De pond L which is solved in the iteration procedure 2 7 3 2 Bottom boundary condition The SWAP model provides a number of options to describe the relation between saturated shallow soil layers with deep groundwater see Chapter 5 Beside handling the flux contr
360. ts will suffice for most applications However when surface runoff is expected daily rainfall amounts may underestimate the amount of surface runoff In such situations real rainfall intensities should be used Alterra Report 1649 update02 65 3 7 2 Weather data In case of daily weather records the data should be specified as listed in Box 3 2 Missing data are given the number 99 9 When SWAP should use Penman Monteith SWETR 0 Box 3 1 data on solar radiation air temperature min and max air humidity and wind speed are required When SWAP should simulate detailed crop growth Chapter 7 data on solar radiation and air temperature min and max are required For rainfall either daily amounts SWRAIN 0 Box 3 1 or daily amounts plus duration SWRAIN 0 Box 3 1 should be specified Box 3 2 Daily basic weather data KK OK ROK ROK ROK ROK ck RARA ckck ck ck ckck ck ck ckck ck ck ck ck ck KK KKK KK KK KK KK KK KK KK KK KK KK KK RK KK RK KK ck ck KK KK RK RK KK KK KK KK KK KK KK KK KK KK RK Filename Wageningen 003 Contents Daily meteorological data of Wageningen weather station kk kk ck ck ck ck ck ck kk ck ck ck ck ck ck kk ke ck cock ck kk ck ck ck ck ck ck ck kk ck ck cock ck ck ck ck ck ck ck ck ck kk ck cc ck ck ck ck ck kc ck ck ck ck KKK KKK KKK KKK ARA AAA ARA AAA ck ck ck ck kc k kc KR Comment area Use of basic weather data for Penman Monteith method Including rainfall duration Missing data 99 9 EEES
361. turated flow Adv Water Resour 8 32 36 Monteith J L 1965 Evaporation and the Environment In G E Fogg ed The state and movement of water in living organisms Cambridge University Press p 205 234 Monteith J L 1981 Evaporation and surface temperature Quarterly J Royal Soc 107 1 27 Mualem Y 1976 A new model for predicting the hydraulic conductivity of unsaturated porous media Water Resour Res 12 513 522 Murray F W 1967 On the computation of saturation vapor pressure J Appl Meteor 6 203 204 Nieber John L Tammo S Steenhuis Todd Walter amp Mark Bakker 2006 Enhancement of seepage and lateral preferential flow by biopores on hillslopes in Biologia Nielsen D R M Th van Genuchten and J W Biggar 1986 Water flow and solute transport in the unsaturated zone Water Resour Res 22 supplement 89S 108S Nimmo J R J Rubin and D P Hammermeister 1987 Unsaturated flow in a centrifugal field Measurement of hydraulic conductivity and testing of Darcy s law Water Resour Res 32 124 134 Parlange J Y 1975 On solving the flow equation in unsaturated soils by optimization horizontal infiltration Soil Sci Soc Am Proc 39 415 418 Peat W E 1970 Relationships between photosynthesis and light intensity in the tomato Annal Bot 34 319 328 Peck A J R J Luxmoore and J L Stolzy 1977 Effects of spatial variability of soil hydraulic properties in water budget modeling
362. ulic head at the lower boundary is approximated by the pressure head of the lowest nodal point plus the elevation head of node n hj z 0 gan AA E 2 4 Qbot VAZ 2 FC K J K n Substitution into Eq 2 30 yields i hitt giu pit E F D oj E e 1 e 20 At YA AZ 1 AZ V2Az cK 2 43 H5 jtK j j AZ s S35 si Seepage face The seepage face option is used to simulate the soil moisture flow in a lysimeter with an open outlet at the bottom No outflow occurs when the bottom soil layer is still unsaturated Since the flow resistance of the outlet is negligible small no positive Alterra Report 1649 update02 41 pressure head values will be build up at the bottom when the soil water percolates at the bottom Within the iteration cycle for solving the numerical expression of the Richards equation it is checked whether the flux or the head controlled boundary condition prevails When hj Az 0 the bottom flux q is set to zero but when ni Az tends to take values larger than zero the pressure at the bottom is set to Zero hj 20 The numerical implementation is as follows hij pem oj oi c 2 1 j n hj Az lt 0 gt At Y2A AZ 1 AzZ 2 44 Aus 5 5 2 p ni hit gesungen uique E oun At VA Az 4 Az hi Az 0 2 45 Kies ta yy Az sie S s n4 YAz nan d n m n Free drainage The free drainage option is ap
363. um sudanese Triticum aestivum Triticum turgidum Phaseolus vulgaris Beta vulgaris Brassica oleracea botrytis Brassica oleracea capitata Daucus carota Zea mays Cucumis sativus Lactuca sativa Allium cepa Solanum tuberosum Spinacia oleracea Lycopersicon lycopersicum ECmax dS m5 8 0 1 0 1 7 7 1 3 2 3 0 11 4 6 8 5 0 7 0 1 7 6 0 5 9 2 0 6 0 6 9 1 5 1 8 2 5 5 6 2 8 4 5 2 1 1 0 4 0 2 8 1 8 1 0 1 7 2 5 1 3 1 2 1 7 2 0 2 5 ECslope 96 per dS m 5 0 19 0 12 0 25 2 29 0 12 0 10 8 16 0 20 0 5 9 5 9 7 3 8 7 3 7 1 6 4 12 0 7 4 11 0 7 6 4 3 2 6 2 5 19 0 9 0 9 2 9 7 14 0 12 0 13 0 13 0 16 0 12 0 7 6 9 9 Rating MS MT T MS MS MS MT MT MT MT S MT MS MS S MS MS MS S MS MS MS Ref These data serve only as a guideline to relative tolerances among crops Absolute tolerances vary depending on climate soil conditions and cultural practices In gypsiferous soils plants will tolerate ECe values about 2 dS m higher than indicated Ratings according to Maas 1990 S sensitive MS moderately sensitive MT moderately tolerant and T tolerant References 1 Maas and Hoffman 1977 2 Francois et al 1986 3 West and Francois 1982 Less tolerant during seedling stage ECe at this stage should not exceed 4 dS m or 5 dS m 7 Sensitive during germination and emergence ECe should not exceed 3 dS m j Average of se
364. undwater flow in the saturated zone and its calculation when parallel open conduits are present Thesis Dutch with English summary University of Utrecht 189 pp Ernst L F 1973 The determination of residence times in case of groundwater flow Nota 755 I C W now Winand Staring Centre Wageningen in Dutch Ernst L F 1978 Drainage of undulating sandy soils with high groundwater tables I en II Journal of Hydrology 39 1 50 Ernst L F and R A Feddes 1979 Invloed van grondwateronttrekking voor beregening en drinkwater op de grondwaterstand Report 1116 ICW currently Winand Staring Centre Wageningen The Netherlands Feddes R A 1971 Water heat and crop growth Ph D thesis Wageningen Agricultural University The Netherlands Feddes R A P J Kowalik and H Zaradny 1978 Simulation of field water use and crop yield Simulation Monographs Pudoc Wageningen 189 pp Feddes R A 1987 Crop factors in relation to Makking reference crop evapotranspiration In Evaporation and weather TNO Committee on Hydrological Research Proceedings and information no 39 p 33 46 Feddes R A P Kabat P J T van Bakel J J B Bronswijk and J Halbertsma 1988 Modelling soil water dynamics in the unsaturated zone state of the art J Hydrol 100 69 111 Feddes R A G H de Rooij J C van Dam P Kabat P Droogers and J N M Stricker 1993a Estimation of regional effective soil hydraulic parameters by inverse modelling
365. urated saturated zone including possible transient and perched groundwater levels SWAP solves Eq 2 3 numerically using known relations between 6 h and K 2 2 Soil physical relations The Mualem Van Genuchten function Van Genuchten 1980 which has been used in numerous studies and forms the basis of several national and international data bases e g Carsel and Parrish 1988 Yates et al 1992 Leij et al 1996 W sten et al 2001 has been implemented in SWAP The analytical h function proposed by Van Genuchten 1980 reads 0 Ores Osat Ox la hl ie 2 4 Alterra Report 1649 update02 27 where Q4 is the saturated water content cm cm Os is the residual water content in the very dry range cm cm and a cm n and m are empirical shape factors Without loosing much flexibility m can be taken equal to d 2 5 n Using the above h relation and applying the theory on unsaturated hydraulic conductivity by Mualem 1976 the following K 0 function results 1 m K K S 1195 2 6 where K 4 is the saturated conductivity cm d A is a shape parameter depending on OK Oh and S is the relative saturation defined as ed 0 EZ 8 0 0 sat S 2 7 The numerical solution to the Richards equation requires an approximation of the differential water capacity C cm An expression is obtained by taking the derivative of 0 to h 00 a n FOn D CL a matt ay Ops a id A numer
366. ure 2 3 Influence of initial estimate on an intermediate solution of a first order approximation based root finding procedure The solution to the second part of the right hand side of Eq 2 30 is referred to as the Newton step Ah Eq 2 31 pio ni Ahi P pira hih 4 An 2 30 j l p 1 j Lp j Lp hi hj Ah We always first try the full Newton step and we check at each iteration that the proposed step reduces 3 F If not we backtrack along the Newton direction until i we have an acceptable step The aim is to find which results in a decrease of 3 aiit 2An 2 The first estimate of amounts to 1 If it is decided that a i l second estimate is needed A is set to 1 3 The third estimate amounts to 1 9 Thereafter no further reduction of A is applied but a new Newton iteration step is performed In SWAP the main convergence criterium in the unsaturated zone is based on the water closure term of the water balance F If F is less than a user defined criterion for all compartments it is decided that the iteration cycle has resulted into a sufficiently accurate solution Alterra Report 1649 update02 37 2 7 3 Numerical implementation of boundary conditions 2 7 3 1 Top boundary condition Appropriate criteria for the procedure with respect to the top boundary condition are important for accurate simulation of rapidly changing soil water fluxes near the soil surface This is for instance the case wi
367. user first has to select the option for extended drainage Box 5 1 Box 5 1 Extended drainage option in drainage file DRA LATERAL DRAINAGE SECTION KOK ROK OK ROK ROK RK ROK RK RK ck ck ck ckckckck ck ck ck ck ck ck ck ck ck ck KK ck ck ckckckckckckckckckckckckckckckckckckckckckckckckckckckckckckck ck ck ck k ck ck ckckckckck Specify whether lateral drainage should be included SWDRA 2 Switch simulation of lateral drainage 0 No simulation of drainage l Ed Simulation with basic drainage routine p2 Simulation with extended drainage routine incl surf water man If SWDRA 1 or SWDRA 2 specify name of file with drainage input data DRFIL wg02 File name with drainage input data no extension A16 KOK ROK OK ROK ck ckckckck ck ck ckckckck ck ck ckck ck ck ck ck ck ck ckck ck ck ck ck ck ck ck ck ck ck ck ck ckckckck ck ck ck ck ck ck ck ck ckckckckckck ck ck ck ck ck ckckck ck ck ck ck KK KK KKK Parameters and input variables are specified in a separate file indicated by the varia ble DRFIL The input data for the options described in this paragraph are given in 2 sections section 1 drainage characteristics described in chapter 4 section 2 surface water system In section 1 the user should specify the altitude of the control unit soil surface with respect to a certain reference level ALTCU In section 2 water management levels are given with respect to the same reference The us
368. uy where u is the measured average wind speed over 24 hours m s When crop height Aerop reaches below or above measurement height Zmmeas the wind speed is corrected with the following assumptions e auniform wind pattern at an altitude of 100 meter e wind speed measurements are carried out above grassland e a logarithmic wind profile is assumed Alterra Report 1649 update02 229 e below 2 meter wind speed is assumed to be unchanged with respect to a value at an altitude of 2 meter applying a logarithmic wind profile at low altitudes is not carried out due to the high variation below 2 meter These assumptions result in the following equation for wind speed correction d d d Tass In Zact act In 100 grass Zomact om grass Uo day In Zio Fact ln Z m meas d is Zom act Zom grass where uwind speed at crop height m s zac is the actual crop height with a minimum value of 2 m dac and dgrass are zero plane displacement of actual crop and grass m Zomact aNd Zom grass are roughness parameter for momentum actual crop and grass m 230 Alterra Report 1649 update02 Appendix 2 Derivation of some macropore geometry equations Basis of the determination of the effective vertical macropore wall area and the effective crack width is the assumption that the natural variety of soil matrix polygons can be described in terms of one effective regular soil matrix polygon Crucial condition for this polygon is
369. values of y and p might be derived from experimental data or from a hydraulic model of soil surface flow Box 4 1 Information on input of surface runoff in main file SWP Ckokckckckckckckckckckckckckckckckckckckckckckckckck ck ck ck ok KK AA KA kc kc kc kc kc kc ckckckckckckckckckckckckck ck ck ckckckckckck ck ck ck ck ckck ckckckckok Part 2 Ponding runoff and runon Ponding threshold time dependent threshold of ponding layer is optional and dependent on the presence of the input parameter swPondmx Only when swPondmx is present and has a value of 1 then a table must be supplied with dates and values for days when pondmx changes value the value for RSRO must be larger than 0 01 d swPondmx In case of time dependent threshold swpondmx 1 then specify date DATEPMX dd mmm yyyy and threshold for ponding PONDMXTB cm maximum MAIRG records The threshold value is determined by linear interpolation between date values DATEPMX PONDMXTB 22 Jan 198 549 22 Feb 198 0 17 Jul 1 98 ds 18 Jul 198 0 17 Sep 198 0 End of table In case of a constant threshold swpondmx 0 or absent then specify PONDMX PONDMX 0 2 In case of ponding minimum thickness for runoff 0 1000 cm R Runoff RSRO 0 RSROEXP 1 5 Drainage resistance for surface runoff 0 001 1 0 d R 0 Exponent in drainage equation of surface runoff 0 1 10 0 R Runon Specify whether runon data are provided in extra input file
370. vel and bottom flux listed in the table using the simulated groundwater level gi 5 Prescribed soil water pressure heads at the bottom of the model In this case values of ho are given as input to the model For days with unknown values a linear interpolation is carried out between the days with known values 6 Zero flux at the bottom of the model domain A bottom flux quo of zero may be applied when an impervious layer exists at the bottom of the profile This option is implemented with a simple switch which forces bot tO Zero 7 Free drainage In the case where free drainage is taken to be the bottom boundary condition the gradient of hydraulic head H is assumed to be equal to one at the bottom boundary which sets qbo equal to the hydraulic conductivity of the lowest compartment o thus qq K 2 51 OZ 6 Free outflow In this case drainage will only occur if the pressure head in the bottom compartment h becomes greater than zero During drainage and after a drainage event h is set equal to zero and qho is calculated by solving the Richards equation This option is commonly applied for lysimeters where outflow only occurs when the lowest part of the lysimeter becomes saturated In the field this condition is appropriate when the soil profile is drained by a coarse gravel layer Lysimeters with groundwater table controlling provisions can be better simulated imposing a zero bottom flux condition Alterra Report 164
371. veral varieties Suwannee and Coastal are about 20 more tolerant and common and Greenfield are about 20 less tolerant than the average Data from one cultivar Pobred Alterra Report 1649 update02 249 NN FPWR Ee ee NPP RPE NNR RP BPR RE Ria a Ln gt gt gt gt aa 250 Alterra Report 1649 update02 Appendix 10 Shrinkage characteristic data After Bronswijk and Vermeer 1990 1 0 22 22 42 42 78 78 120 2 0 26 26 34 34 56 56 75 75 107 3 0 29 29 40 40 63 63 80 80 100 4 0 21 21 52 52 77 77 100 5 0 22 22 38 38 60 60 90 90 110 6 0 18 18 30 30 58 58 85 7 0 35 35 60 60 80 80 95 1 Locations 1 Oosterend 2 Nieuw Beerta 3 Nieuw Statenzijl 4 Schermerhorn 5 Dronten 6 Bruchem and 7 Kats A11 ACg C2g Ap A12 Clig C12g C13g Ap AC C21 C22g C23g A11 A12 C21g C22g Apl A12 C22g C23g C24g A11 A12 Clig C12g Ap C21g C22g C23g 2 Density of the solid phase 3 Organic matter Alterra Report 1649 update02 2 52 2 60 2 66 2 68 2 64 2 61 2 62 2 68 2 69 2 65 2 67 2 69 2 66 2 69 2 59 2 61 2 62 2 63 2 66 2 66 2 63 2 59 2 57 2 52 2 60 2 64 2 59 2 67 2 67 2 70 2 69 0 0 0 0 2 5 6 9 1 4 0 8 1 7 3 3 0 3 9 0 10 6 11 3 9 8 11 6 11 7 11 1 17 6 18 8 9 9 8 1 6 6 5 8 4 6 0 0 0 0 0 0 0 0 10 2 13 6 15 9 5 10 3 6 9 4 5 2 2 4 8 3 9 2 2 1 9 3 0 3 3 2 9 2 2 8 2 2 5 9 6 2 3 7 3 1 2 6 2 2 7 6 7 0 10 5 9 9
372. w at soil surface In order to describe these inflow processes accurately realistic precipitation intensities and matrix infiltration rates should be simulated The consequences of this for the SWAP parameterisation other than the macropore parameters are discussed below Rainfall option For realistic rainfall intensities rainfall option SWRAIN 3 is preferred Section 3 7 1 Less preferable are options 1 and 2 Option 0 daily rainfall sum is not recommended This option may seriously underestimate macropore inflow at soil surface because of far too small rainfall intensities Vertical discretisation Realistic simulation of matrix infiltration at the soil surface requires thin compartments in the top of the profile in the order of 1 cm thick Van Dam and Feddes 2000 A typical vertical discretisation for a macroporous field soil could be for the first 10 20 cm compartments of 1 cm thick for the next 20 30 cm 2 5 cm Alterra Report 1649 update02 137 thick until the depth of the bottom of the IC domain maximal 5 cm thick until the depth of the bottom of the static macropores 5 to maximal 10 cm thick and below this depth compartments of 10 25 cm thick Soil hydraulic functions The hydraulic functions of the soil matrix should be used This implies that the saturated volumetric moisture content is without the static macropore volume And that the saturated hydraulic conductivity concerns a soil physical conductivity of the matrix rat
373. wer m a shape factor In order to describe the individual IC macropores the IC domain is divided into sub domains Strictly speaking this subdivision of the IC macropore volume is an aspect of the numerical implementation and therefore is discussed in Section 6 2 1 1 The IC volumetric proportion at the soil surface Pico is an essential parameter of the concept It determines the distribution over the two main domains of the precipitation water routed into the macropores at the soil surface the major source of macropore water It is assumed that the IC macropore volume consists of many individual small macropores that originates at the soil surface and functional end at different depths In 114 Alterra Report 1649 update02 ZAh Zic 100 Figure 6 2 Cumulative frequency distribution R of the depth z at which the functional IC macropores end and the fraction F of IC macropores that is functional at depth z this sense functional implies that flow is blocked at the depth of ending of the macropores Thus the functional volume of IC macropores gradually declines to zero at depth Zic The cumulative frequency distribution of the depth z at which the functional IC macropores end in the concept is described with a power law function Fig 6 2 Z R 5 fr 0 2 gt Za 6 3 2 Zan Rem e r Za for Za 2 zZ 2 Z 6 3 b where the depths z Zan and Zi cm are defined negative downwards and the power m is
374. y Figuur B16 1 AMAXTB 45 4 40 4 2 ERN 304 S 254 E 20 4 154 10 4 54 0 T T T T 1 95 200 275 366 Day Figure B16 1 The maximum leaf CO assimilation rate AMAX as a function of the day number The maximum leaf CO assimilation rate has to be corrected for sub optimal average day time temperatures The applied correction factor is a function of the average day time temperature acronym tmpftb An afgen function is used to establish its value Figuur B16 2 Reduction factor AMAX 0 8 4 0 6 4 0 4 4 Reduction 0 2 4 0 5 15 25 40 Day time average Temp Figure B16 2 Reduction factor for influence of day time average temperature on AMAX The average day time temperature is calculated as Alterra Report 1649 update02 265 T s DO us T is Tua 2 where Taa Average day time temperature C Tmax Maximum temperature C Tmin Minimum temperature C The corrected maximum leaf CO assimilation rate is subsequently introduced in the subroutine totass which returns the gross daily CO assimilation rate This rate is subsequently corrected for low minimum temperatures using a correction factor acronym tmnftb Figure B16 3 The reduction is based on the 7 day running average of Tmin Reduction factor daily gross assimilation rate 1 0 8 4 c 2 0 64 o 2 044 ra 0 2 4 0 0 4 6 Minimum Temp Figure B16 3 Reduction factor
375. y J cm C of each component respectively and the components are indicated in the subscripts Table 9 1 gives values of C for the different soil components Table 9 1 Volumetric heat capacity and thermal conductivity of the soil components Component Volumetric heat capacity Thermal conductivity J cm C den cd Sand 2 128 7603 Clay 2 385 2523 Organic 2 496 216 Water 4 180 492 Air 20 C 1 212 22 In order to calculate Chea and Aneat from 9 10 the percentage by volume of sand and clay denoted VPsana and VPa respectively must be specified by the SWAP user VPsana and VP should be provided as percentages of the total solid soil matter and may differ for each soil layer The total volume fraction of solid matter is given by O iia 1 7 0 9 6 where 0 4 is the saturated volumetric water content The volume fraction of air is equal to the saturated minus the actual water content f 794 9 9 7 frand Fetay aNd forganic are then calculated by 186 Alterra Report 1649 update02 VP sand 0 9 8 Sowa 1 0 0 solid VP fax E 100 O nia 2 9 organic zx Bota xS 3 Z clay 9 10 where it has been assumed that solid matter that is not sand or clay is organic Table 9 1 also lists the thermal conductivities which are greatest for sand and clay an order smaller for organic material and water and again an order smaller for air Hence the space average thermal conductivity of a
376. y consist of files for main input meteorological data crop growth and drainage SWAP employs the TTUTIL library to read the ASCII input files in easy format Output is generated in ASCII and binary files The internet site contains a large number of SWAP test cases Chapter 1 Soil water flow is calculated with the Richards equation The Mualem Van Genuchten relations with a modification near saturation describe the soil hydraulic functions Scaling of main drying and main wetting curves describe hysteresis in the retention function The bottom boundary is controlled by head flux or the relation between flux and head SWAP solves the Richards equation numerically with an implicit backward finite difference scheme The Newton Raphson iterative procedure ensures mass conservation and rapid convergence Chapter 2 For agricultural crops and grassland SWAP computes the interception following Von Hoyningen H ne and Braden The interception concept of Gash is available for trees and forests The Penman Monteith equation can be used to calculate the potential evapotranspiration of uniform surfaces wet and dry vegetation bare soil An alternative is providing input of reference evapotranspiration in combination with crop factors Next the potential transpiration and evaporation fluxes of partly covered soils are derived taking into account interception and soil cover Actual transpiration depends on the moisture and salinity conditions in the root
377. ydraulic conductivity root water uptake drainage fluxes and bottom flux Chapter 10 Irrigations with fixed date depth and quality can be specified as input In addition SWAP can be used to schedule irrigation Timing criteria include allowable daily stress allowable depletion amount and critical pressure head or water content Depth criteria include back to field capacity and fixed depth Chapter 11 The appendices contain information on the parameters of the soil hydraulic functions critical pressure heads for root water extraction salt tolerance data shrinkage characteristic data numerical solution of water and heat flow description of binary output files and list of main SWAP subroutines Alterra Report 1649 update02 13 14 Alterra Report 1649 update02 1 Model overview 1 1 Model domain and processes SWAP simulates transport of water solutes and heat in the vadose zone in interaction with vegetation development The model employs the Richards equation including root water extraction to simulate soil moisture movement in variably saturated soils Concepts are added to account for macroporous flow and water repellency SWAP considers for solute transport the basic processes convection dispersion adsorption and decomposition For more extensive studies which for instance include volatilization or nutrient transformations SWAP generates soil water fluxes for detailed chemical transport models as PEARL for pesticides and AN

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