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土壌の物理性 - 土壌物理学会

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34. Yt ul y 1 E 33 Chiu C Y Wang C J Huang C C 2008 Availability and im mobilization of 137Cs in subtropical high mountain forest and grassland soils J Environ Radioact 99 882 889 2011 pp 48 49 IR 2011 120 H pp 28 34 2011 http www meti go jp press 2011 04 20110422004 20110422004 2 pdf Accessed 29 Jan 2013 Kruyts N and Delvaux B 2002 Soil organic horizons as a ma jor source for radiocesium biorecycling in forest ecosystems J Environ Radioact 58 175 190 WS 2012a
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47. 5 1 2 1 1 1 2 1 3 1 1 1 1 1 2 1 1 3 26 lt gt 2009 113 3 12 Fujimaki H Ando Y Cui Y and Inoue M 2008 Parameter estimation of root water uptake model under salinity stress Vadose Zone Journal 7 31 38 Millington R J and Ouirk J P 1959 Permeabil ity of porous media Nature 183 387 388 doi 10 1038 183387a0 Bitteli M Flury M and Campbell G S 2003 A thermo dielectric analyzer to measure the freez ing and moisture characteristic of porous me dia Water Resour Res 39 2 W1041 doi 10 1029 2001WR000930 lt gt Tinker PB and Nye P H 2000 Solute movement in the rhizosphere p 308 Oxford University Press New York
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52. DAWN T DED J Jpn Soc Soil Phys No 125 p 3 15 2013 am X Original Paper Estimating the unsaturated hydraulic conductivity of Andisols using the evaporation method RUDIYANTOL Nobuo TORIDE Masaru SAKAL and Ma
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63. AR 2002 KIC IST AWYR Uc TR eu WE TR 2 ALA Both 7 ER BE AK A 220 35 41 1998 6 20 178 10 Braunack M V 1995 Effect of aggregate size and soil water content on emergence of soybean Glycine max L Merr and maize Zea mays L Soil and Tillage Research 33 149 161 Collis George N and Hector J B 1966 Germination of seeds as influenced by matric potential and by area of contact be tween seed and soil water Australian Journal of Soil Research 4 145 164 Khan A R and Datta B 1983 Effect of aggregate size on water uptake by peanut seeds Soil and Tillage Research 3 171 184 Hadas A and Russo D 1974a Water uptake by seeds as af fected by water stress capillary conductivity and seed soil water contact I Experimental study Agronomy Journal 66 643 647 Hadas A and Russo D 1974b Water uptake by seeds as af fected by water stress capillary conductivity and seed soil water contact II Analysis of experimental data Agronomy Journal 66
64. EC 4 HED ti Rhoades Rhoades 1992 Dalton etal 1984 TDR EC TDR TDR Cit EC TDR 0 EC EC EC B TDR HEDD EC 9 EC Ward et al 1994 Heimovaara et al 1995 Mallants et al 1996 Risler et al 1996 Rhoades Bhabani et al 1999 De Neve et al 2000 Mufioz Carpena et al 2005 Rhoades et al 1976
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87. 15ml 35 1 1 001 0910 10 7 3 16 Tel 011 763 1088 Fax 011 763 1667 Mail endo rika mb infosnow ne jp J Jpn Soc Soil Phys No 125 p 17 27 2013 Original Paper 42 LE Analysis of suitable condition for soybean planting in rotational clayey paddy fields under risk of excessive dry or wet condition Shuichiro YOSHIDA Hisashi HOSOKAWA and Kazuhide ADACHI Abstract Stabilization of soybean cultivation in rotational paddy fields is important issue for efficient utilization of Japanese arable
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92. Le H 4 ETE Al HEH 1 g Tee 69 4 250 524 E FEB LOS 2 H We RED J Jpn Soc Soil Phys No 125 p 29 33 2013 2 SBE eo Original Paper Development of a device for measuring the vertical distribution of radioactivity in soil using photodiode Shinya SUZUKI Hiroshi IWASE Kosuke NOBORIO Masaru MIZOGUCHI Daiki KOBAYASHI and Tetsu ITO Abstract Measurements of radiocaesium
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98. A 1985 I 1Graduate School of Agricultural and life sciences The University of Tokyo 1 1 1 Yayoi Bunkyo ku Tokyo 113 8657 Japan Correspond ing author 2National Agricultural Research Center NARO 3 1 1 Kannondai Tsukuba Ibaraki 305 8666 JAPAN 3Kubota Corporation 1 1 1 Hama Amagasaki Hyogo 661 8567 JAPAN 2012 6 26 2013 11 8 2000 We Elk AR 1998
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110. Sampling Raw Corrected Comparison between radiocaesium concentration at each depth level in undisturbed soil of paddy field in Htate village Fukushima and raw and corrected couting rates Samples were measured in wet weight 16000 y 2247 4x 3720 6 r 0 98885 gt 14000 4 Corrected Radiocaesium concentration Bq 0 2 4 6 8 10 Counting rate cpm Fig 5 Relationship between radiocaesium concentration by soil sam pling and corrected counting rate 0 2 24cm WA TRE 4 8 cm
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137. 70 23 28 Mallants D Vanclooster M Toride N Vanderborght J van Genuchten M Th and Feyen J 1996 Comparison of three methods to calibrate TDR for monitoring solute movement in unsaturated soil Soil Sci Soc Am J 60 747 754 Miyamoto T Kameyama K and Shinogi Y 2010 Electri cal conductivity and nitrate concentrations in an Andisol field using time domain reflectometry Proceedings of 19th World Congress of Soil Science 54 57 Mufioz Carpena R Regalado C M Ritter A Alvarez Benedi J and Socorro A R 2005 TDR estimation of electrical con ductivity and saline solute concentration in a volcanic soil Geoderma 124 399 413 Nadler A and Frenkel H 1980 Determination of soil solution electrical conductivity from bulk soil electrical conductivity measurements by four electrode method Soil Sci Soc Am J 44 1216 1221 2003 TDR 93 57 65 Porter L K Kemper W D Jackson R D and Stewart B A 1960 Chloride diffusion in soils as influenced by moisture content Soil Sci Soc Am Proc 24 460 463 Richards L A 1966 A soil salinity sensor of improved design Soil Sci Soc Am Proc 30 333 337 Rhoades J D 1992 Instrumental field methods of salinity ap praisal In Topp G C
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139. Oss 9 39 Table1 _ Determined surface conductivities transmission coefficient parameters and threshold water contents of soils studied Rhoades et al 1976 Table 3 Soil type EC A b a R dS mr 1 Pachappafsl 0 18 1 382 0 093 0 07 0 96 Indio vfsl 0 25 1 287 0 116 0 09 0 98 Waukena 1 0 4 1 403 0 064 0 05 0 97 Domino cl 0 45 2134 0245 0 12 0 92 0 6 INDIO V F S L Code ECy x 2 5 2 os 10 5 o 8 7 2 Oo 56 2 E 04 5 2 03 3 o o 5 O2 8 E 2 Ol 2 e o o 0 1 0 2 0 3 0 4 0 5 0 6 Volumetric Water Content cmYy cm Fig 6 Indio vfsl 6 7 Fig 3 4 12 15 st Relation of the transmission coefficient T and volumetric water content 0 determined for Indio vfsl from the data of Fig 3 and 4 and Eg 15 Rhoades et al 1976 Fig 6 ECws ECwe
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161. 125 25 12 20 3 45 7 31 ISSN 0387 6012 Journal of the Japanese Society of Soil Physics 125 20134 12 Japanese Society of Soil Physics 125 2013 12 1 Estimating the unsaturated hydraulic conductivity of Andisols using the evaporation method RUDIANTO N TORIDE M SAKAI and M Th van GENUCHTEN 3 UU 17 29 E J D Rhoades P A Raats and R J Prather
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165. 23 a 2006 b 2007 FT 1 0 0 9 0 8 07 4 0 6 J 0 5 04 0 3 4A 02 04 4 0 0 o 1 2kPa3cm 12kPa7cm Germinatiorrate Germinatiorrate 7cm 6kPa7cm o a n x 0kPa7cm 3kPa3cm 3kPa7cm CompressionBlock Tillage Depth Day Compdepth Compression Block Tilage Depth Day Depthday Factors and treatments Factors and treatments Fig 6 a 2006 b 2007 1 2 1 5 3 Tukey 5 4 x Effects of factors on germination rate of seeds 1 Days in the figure show the days after the pl
166. 1997 pp 129 138 PARRA 2005 pp 60 79 Jury W A 1996 Stochastic solute transport mod eling trends and their potential compatibility with GIS In Corwin D L and Loague K ed Appli cation of GIS to the modeling of non point source pollutants in the vadose zone pp 57 67 SSSA Spe cial Publication No 48 Madison lt Web gt FAO AGL 2000 Global extent and location of sodic soils Available at http www fao org ag AGL agll prosoil sodic html 2006 http vegetea naro affrc go jp joho manual shousan index html H 1H 6 Bil CBC Yw SD Fig 1 Table
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178. EC Fig 3 ECs Plot of bulk soil electrical conductivity ECa vs liguid phase electrical conductivity ECw for various fixed volumetric water contents as interpolated from Fig 3 Indio vfsl showing the extrapolated value of surface conductivity ECs Rhoades et al 1976 Fig 4 AG INDIO V F S L EC EC 8 c84b EC ECA ECs o 05 A 15 2 25 3 35 4 45 5 55 Volumetric Water Content 9 cm cm Fig 5 Indio vfsl 9 EC EC ECw Fig 6 g 2 3 5 6 Plot of bulk soil electrical conductivity surface conductivity liquid phase electrical conductivity ECa ECs ECw versus volumetric water content 0 for data of Fig 3 and 4 compared to the curve calculated from Eq 5 and 6 with the values of a and b determined from Fig 6 Rhoades et al 1976 Fig 6 EC 9 BC EC EC Fig 5 Fig 3 EC Fig 5
179. al 1976 Fig 1 Hanks EC EC Gupta and Hanks 1972 L Rhoades et al 1976 BC Rhoades et al EC 1976 1972 Hl EC 9 EC EC ECi s Rhoades Gupta and 1 2 9 ECi s EC 3 T a0 b 4 a 5 1 G EC
180. 7Cs 40 Kruyts and Delvaux 2002 Chiu et al 2008 B37Cs Tamura 1964 BoT AKEDE 1Graduate school of Agriculture and Life Science The University of Tokyo 1 1 1 Yayoi Bunkyo Tokyo 113 8657 Japan Corresponding author 2High Energy Accelerator Research Organization 1 1 Oho Tsukuba Ibaraki 305 0801 Japan 3School of Agriculture Meiji University 1 1 1 Higashimita Tama Kanagawa 214 8571 Japan 4X ability Co Ltd 3 16 6 801 Hongo Bunkyo Tokyo 113 0033 Japan 2013 5 4 2013 11 8 HMGWU cZER I 3 rai ti
181. Table 2 4 Rhoades GO ECw EC BGs EC TIET _ ELT 9 BC BC Fig 3 CHS 13 1 Gupta and Hanks 1972 0 EC EC Fig 3 4 9 ECw EC Fig 4 BC 0 G EC Rhoades BC Table 3 38 125 2013 INDIO V F S L 8 gt o EC 0 25 w o Cn N v o Bulk Soil Electrical Conductivity EC mmho cm N o o o 2 4 6 8 10 2 14 16 8 20 Electrical Conductivity of Liquid Phase ECw mmho cm Fig 4 9 EC
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185. http www pref niigata lg jp HTML_Simple 171 972 gitai5 0 pdf 1987 2 AS pp 259 264 1976 1 20 7 13 Ojeniyi S O and Dexter A R 1984 Effect of soil structure on soil water status Soil and Tillage Research 4 371 379 Rathore T R Ghildyal B P and Sachan R S 1983 Effect of surface crusting on emergence of soybean Glycine max L Merr seedlings 1 Influence of aggregate size in the seedbed Soil and Tillage Research 3 111 121 oR 5 2004 39 3 141 156 E 27 Stucky D J 1976 Effects of planting depth temperature and 79 1 7 cultivars on emergence and yield of double cropped soybeans Agronomy Journal 68 2
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195. 969 0 040 SE 66 0 016 CV 0 068 0 389 2 0 101 4 36 968 0 044 0 532 SE 0 002 0 06 50 0 006 0 003 CV 0 020 0 013 0 052 0 145 0 005 3 0 111 3 57 555 0 011 0 545 0 00125 1 25 SE 0 002 0 07 34 0 004 0 003 0 00009 0 01 CV 0 018 0 020 0 061 0 381 0 005 0 072 0 005 4 0 131 2 42 507 0 330 0 513 0 00072 1 74 SE 0 002 0 04 176 0 608 0 002 0 00004 0 07 CV 0 015 0 016 0 347 1 844 0 005 0 056 0 043 5 850 0 620 SE 223 0 378 CV 0 262 0 610 6 617 0 407 SE 39 0 059 CV 0 063 0 145 7 391 0 018 SE 22 0 014 CV 0 056 0 765 Note Entries indicated by were not included in the optimization but fixed at the initial values 8 125 2013 Og Og 100 100 200 5 g X 200 a Kumamoto 300 8 o o 400 _ cS 2 300 Ll A Observed o a Fitted Case 1 g 500 2 Fitted Case 2 v a 8 aW Fitted Case 3 600 400 700 500 i 1 f 1 1 1 1 800 i 1 A 1 A 1 A 1 0 1 2 3 4 5 0 1 2 3 4 5 Time t days Time t days Fig 3 Observed and fitted pressure heads as a function of time for the Kumamoto a and Mie b Andisols Case 1 long dash line case 2 short dash line and case 3 solid line variations in 9 Since Andisols have a large porosity es pecially the Kumamoto soil in our stu
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198. J Jpn Soc Soil Phys No 125 p 35 41 2013 Lectures J D Rhoades PA Raats and R J Prather VA 2 3 Reviewing classical studies in soil physics Effects of liguid phase electrical conductivity water content and surface conductivity on bulk soil electrical conductivity by J D Rhoades P A Raats and R J Prather Soil Sci Soc Am J 40 651 655 1976 Yosuke YANAI Teruhito MIYAMOTO and Nobuo TORIDE 1 9 EC Tme Domain Reflectometry TDR TDR 0 EC TDR 9 EC Decagon STE Delta T WET
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201. a y Miscellaneous A H a Ba IRZ ERAS 25 10 A 26 55 Lik 12 38 120 50 1 3 3 4
202. 63 1561 1570 Bolt G H and Bruggenwert M G M 1989 F a HEITER pp 191 212 Dalton EN Herkelrath W N Rawlins D S and Rhoades J D 1984 Time domain reflectometry Simultaneous measure a ment of water content and electrical conductivity with a single probe Science 224 989 990 Dehghanisanij H Yamamoto T and Inoue M 2004 Practical aspects of TDR for simultaneous measurements of water and solute in a dune sand field 98 21 30 De Neve S Van De Steene J Hartmann R and Hofman G 2000 Using time domain reflectometry for monitoring min eralization of nitrogen from soil organic matter Eur J Soil Sci 51 295 304 Gupta S C and Hanks R J 1972 Influence of Water Con tent on Electrical Conductivity of the Soil Soil Sci Soc Am Proc 36 855 857 Heimovaara T J Focke A G Bouten W and Verstraten J M 1995 Assessing temporal variations in soil water composi tion with time domain reflectometry Soil Sci Soc Am J 59 689 698 1992 TDR 65 55 61 B 1994 4
203. Herrmann L Ingwersen J and Stahr K 2006 Applicability of uni and bimodal retention functions for water flow method in a tropical acrisol Vadose Zone J 5 48 58 doi 10 2136 vzj2005 0047 Estimating the unsaturated hydraulic conductivity of Andisols using the evaporation method 15 van Genuchten M Th 1980 A closed form eguation for pre WOosten J H M and van Genuchten M Th 1988 Using tex dicting the hydraulic conductivity of unsaturated soils Soil ture and other soil properties to predict the unsaturated soil Sci Soc Am J 44 892 898 doi 10 2136 sssaj1980 hydraulic properties Soil Sci Soc Am J 52 1762 1770 03615995004400050002x Zurmiihl T and Durner W 1998 Determination of parame van Genuchten M Th Leij F J and Yates S R 1991 The ters for bimodal hydraulic functions by inverse method Soil RETC Code for Ouantifying the Hydraulic Functions of Sci Soc Am J 62 874 880 doi 10 2136 sssaj1998 Unsaturated Soils Version 1 0 EPA Report 600 2 91 065 03615995006200040004x R S Kerr Environmental Research Laboratory U S Environ mental Protection Agency Ada OK 85 p http www pc progress com en Default aspx retc 2 bimodal van Genuchten VG
204. R 6 ET OKA WINK EVE ORO MEL Fig 5 GE F mx OF 5 1994 2007 E Fig 5 2 ge 2007 2007 x g
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208. EE nau x hu 3 it xr yl di Mt AFR 37 S Fig 2 4 Soil filled four electrode cells positioned in pressure plate appa ratus for adjustment of water content Rhoades et al 1976 Fig 2 40 INDIO V F S L EC EC Bulk Soil Electricol Conductivity Electrical Conductivity of Liquid Phase o OS J 5 2 25 3 35 4 4 amp 5 5 55 Volumetric Water Content 8 cm cm Fig 3 Indio vfsl 9 ECa ECw Plot of bulk soil electrical conductivity liguid phase electrical conductivity ECa ECw vs volumetric water content 0 for In dio vfsl Rhoades et al 1976 Fig 3 1 1 1 Ra Rp R sa Ra R 10 EC A EC Rp G 11 9 a1 2 EC ECw97 EC 12 Rhoades 2
209. Reynolds W D and Green R E ed Advances in measurement of soil physical properties Bring ing theory into practice pp 231 248 SSSA Special Publica tion No 30 Madison Rhoades J D 1999 Soil salinity assessment Methods and in terpretation of electrical conductivity measurements p 150 Food and Agriculture Organization of the United Nations Rome Rhoades J D and Ingvalson R D 1971 Determining salinity in field soils with soil resistance measurements Soil Sci Soc Am Proc 35 54 60 Rhoades J D Raats P A and Prather R J 1976 Effects of liquid phase electrical conductivity water content and sur face conductivity on bulk soil electrical conductivity Soil Sci Soc Am J 40 651 655 Rhoades J D Kaddah M T Halvorson A D and Prather R J 1977 Establishing soil electrical conductivity salinity cali brations using four electrode cells containing undisturbed soil cores Soil Sci 123 137 141 Rhoades J D Manteghi N A Shouse P J and Alves W J 1989 Soil electrical conductivity and soil salinity New for mulations and calibrations Soil Sci Soc Am J 53 433 439 Risler P D Wraith J M and Gaber H M 1996 Solute trans port under transient flow conditions estimated using time do main reflectometry Soil Sci Soc Am J 60 1297 1305 Shinberg I Rhoades J D and Prather R J 1980 Eff
210. When the value of 6 is fixed from these water mass balance consid erations K should be estimated in the evaporation method Since the initial estimates of the water retention param eters were determined from the independently measured water retention data parameter estimation succeeded to converge guickly regardless of the number of optimized parameters When water retention data from near satura tion to very low pressure heads are available and used in the objective function it is possible to predict K h by op timizing only two conductivity parameters Ky Since the flat region of the bimodal water retention curve is dif ficult to measure precisely we recommend optimizing all of the bimodal VG parameters except 6 and 0 to yield the best overall fit In order to demonstrate the role of water retention data at low pressure heads in the objective function we com pared hydraulic functions optimized with and without wa ter retention data at low pressure heads Although almost similar matches to observed pressure heads were obtained with or without the low pressure data in the dry range the second subregion parameter 0 n2 converged to different values if the low pressure data were omitted from the ob jective function Predictions based on the hydraulic func tions optimized with the low pressure data agreed well with observed pressure heads near the surface after a longer pe riod of evaporation than used for the tensiometer
211. o morr rr a ESEN a K h of Kumamoto 3 o A b K h of Mie w 1 Q O 5c N Y E 10 NN E 109 N o EN A o x SOA x gt gt ce 103 NN 10 ADN 9 N AS 8 YNS pS S 9 8 Case 1 2 10 104 Case 5 Case 6 g Ss FF Case7 109 sse UL 103C il il 109 10 10 108 104 108 109 101 10 10 104 108 Pressure head h cm Pressure head h cm Fig 7 Impacts of the pressure head range in the objective function on the estimated unsaturated hydraulic conductivity for the Kumamoto a and Mie b Andisols case 1 used all data case 5 only h gt 200 cm case 6 only h gt 100 cm and case 7 only h gt 50 cm results again indicate that including water retention data at pressure heads below the tensiometer range about 500 cm will improve the estimates of the soil hydraulic pa rameters Since water retention at low pressure heads now can be measured relatively easily and accurately using dew point potentiameters e g WP4 we strongly recommended to include in the optimization also water retention data in the measurement range of the dew point potentiameter 10 lt h lt 3 x 10 cm to extend the applicable range of the model predictions On the other hand estimates of the hydraulic conductivity at the very low pressure heads e g h lt 10 may require further investi
212. 13 2 22 42 1 05 2006 0 10 cm H ns Fine 60 1 2 6 214 6 1 41 7 13 Coarse 51 8 12 6 241 3 6 0 5 cm i ns Fine 69 6 9 3 32 1 6 1 Coarse 40 2 10 2 216 24 5 cm x 2007 Fine 60 2 12 7 30 0 46 Coarse 42 8 4 4 222 2 6 35 7 1 0 Whole Layer A ns Fine 62 4 7 4 306 49 37 0 14 1 4 2 5 ns AE 13 mm 50 mm 2006 L 2006 2 3 3 cm 2 5 75cm 7 5 12 5cm DS 2007 1 7 cm
213. 1981 Collis George al 1974a 1974b 2008 etal 1966 Hadas et HHR ME bao F BOAR AD FETII 2006 Fig 5 Fig 7 Fig 6 3 4
214. 2 K X du a 1 1 re F aa NG 21 2 2 E xl amp Wi Tanaka 1994 Nakamura and Suzuki 1981 3 1 et al 1978 Tayler et al 1945 NN ABC T vat A S AIT
215. a and Mie b Andisol soils samples Sown are the observed evaporation rate data open circles and the fitted polynomial equation solid line on the parameter optimization process using the evapora tion method can be neglected Sakai and Toride 2007b The objective function to be minimized during the parameter estimation process consisted of pressure heads measured at several depths as well as the independently measured water retention data shown in Fig 1 Hopmans et al 2002 im nek et al 2008 w hans 1 Ma oF i l 9 ng Y6 y Gobs hi Oit h i l where np and ng are the number of observed pressure heads in the column and independently measured water reten tion data respectively vh 1 nn op and vg 1 ng og are weights for each data type in which o is the variance of the observed data while the subscripts obs and fit indi cate observed and model fitted values respectively at time ti im nek et al 1998 recommended including the final water content of the evaporation experiment in the objec tive function in order to anchor the retention curve along the axis Instead of including the final water content in the objective function we fixed the value of 0 by applying a mass balance to the column The value of 0 was esti mated from the final water content of the column and the cumulative amount of evaporation during the evaporation experiment as determined from the
216. caesium with mineral soils Nuclear Safety 5 262 268 RREA Be K MAIK 2012 31 75 129 A 4 fey FAB REA AF ELA ymi RA
217. gt 0 99 and P gt 0 95 respectively RT 5 x 2 Different letters denote statistically significant P gt 0 95 differences between the series of sampling dates from the summer to the following spring according to Tukey s multiple comparison 3 The filled and open symbols represents statistically significant and non significant factors respectively Crosses denote data sets inadeguate for statistical analysis due to the nature of them 2007 2 6 35 28 2 4 4 1 1 EREJE ER eH EX E ep John son and Buchele 1961 Johnson and Henry 1964 Hum meletal
218. loss of weight of the sample after the experiment Estimates of the remaining water retention parameters 0 01 11 W2 2 n2 in Eqs 1 to 3 were determined first from the observed water re tention data in Fig 1 using version 6 02 of the RETC code http Www pc progress com en Default aspx retc of van Genuchten et al 1991 In order to reduce the number of optimized parameters the value of 0 was assumed to be zero for our two Andisols since we found that optimiza tion of 9 did not improve the fit of the data in Fig 1 We similarly found that the restrictions m 1 1 n in the bimodal VG model did not affect the goodness of fit Fig 1 shows excellent visual matches of the bimodal VG soil water retention functions to the data Following Spohrer et al 2006 and Sakai and Toride 2007b the fitted retention parameter values were used next as initial estimates in the overall optimization of the evaporation experiment In our study we optimized the hy draulic conductivity parameters K and since these two parameters are generally difficult to measure directly The initial value for K was fixed at the value obtained with the falling head method while was initially assumed to be 0 5 as suggested by Mualem 1976 The values of 0 and K in an evaporation experiment may be slightly different from observed static water retention measurements and the falling head method because of entrapped air during sat uration or the
219. measure ments The results indicate that including water retention data at low pressure heads can extend the applicable range of the model predications at least down to approximately 10 cm The benefit of using independently measured water re tention data was further studied by including different pres sure head measurement ranges in the objective function Neglecting the lower pressure data did not affect the K A estimation process very much leading to almost similar K h functions This confirms that collecting water reten tion data over a wide range of pressure heads will give very useful prior information to the parameter estimation pro CCSS References Bittelli M and Flury M 2009 Errors in water retention curves determined with pressure plates and their effect on soil hy draulic functions Soil Sci Soc Am J 73 1453 1460 doi 10 2136 sssaj2008 0082 Chamindu Deepagoda T K K Moldrup P Jensen M P Jones S B de Jonge L W Schjgnning P Scow K Hopmans J W Rolston D E Kawamoto K and Komatsu T 2012 Diffusion aspects of designing porous growth media for earth and space Soil Sci Soc Am J 76 1564 1578 doi 10 2136 sssaj2011 0438 Cresswell H P Green T W and McKenzie N J 2008 The ad equacy of pressure plate apparatus for determining soil water retention Soil Sci Soc Am J 72 41 49 doi 10 2136 ss saj2006 0182 Coppola A 2000 Unimodal and bimodal
220. van Genuchten 1980 The bimodal form of this function has been used in several recent studies e g Coppola 2000 Peters and Durner 2008 Schelle et al 2010 including for the water retention properties of Andisols Miyamoto et al 2003 Hamamoto et al 2009 Chamindu Deepagoda et al 2012 Most of these studies were concerned with the wa ter retention properties of soils By comparison very few studies have applied the bimodal VG model to the unsat urated hydraulic conductivity function of aggregated soils When used also for the hydraulic conductivity most ap plications were concerned with improved descriptions of the unsaturated conductivity function near saturation in at tempts to account for the effects of macropores or rock fractures Peters and Klavetter 1988 Zurmiihl and Durner 1998 Iden and Durner 2007 Durner and Iden 2011 The bimodal VG model has considerable flexibility in describing the hydraulic properties of aggregated media Unfortunately optimization of the large number of param eters in the model against transient flow data such as from multistep outflow or evaporation methods is a major chal lenge Since several of the hydraulic parameters are often correlated Zurmiihl and Durner 1998 it is inherently dif ficult to find the global minimum of the objective function in the optimization process Zurmiihl and Durner 1998 showed that convergence of the parameter optimization process depends very m
221. 04 Rathore et al 1983 wc 18 2
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224. 2006 c 2007 d 2007 Change in air temperature precipitation and soil water potential during the experiment a Air temperature in 2006 b Precipitation and soil water potential in 2006 c Air temperature in 2007 d Precipitation and soil water potential in 2007 The arrows below the horizontal axes represent the planting dates MS 11 2 21 Ur a 2006 180 a ys S140 160 c 2007 Ur cm T Ur 03cm 12 po 7cm T g Un 7cm L 100 120 5 so 100 5 5 so 2 60 2 o 5 60 40 o 5 5 40 20 S 20 LI EN SS lr See
225. 291 294 2008 ag i ee a 3 37 6290 BIT SA 4 AP 2000
226. 4a In fact as shown in Fig 4b the estimated hydraulic con Estimating the unsaturated hydraulic conductivity of Andisols using the evaporation method 9 0 8 St rr a 6 h of Kumamoto 0 7 0 6 0 5 0 4 ve O Observed Case 1 0 2 Water content 9 cm3 cm 3 0 1 0 10 102 10 104 108 Pressure head h cm T TTT rrr TY Y T TTTT 0 8 0 7 c 6 h of Mie 0 6 0 5 0 4 0 3 0 2 Water content cm3 cm 3 0 1 ot ail 10 10 10 10 10 105 Pressure head h cm Lil ol 0 10 rr b K h of Kumamoto 8 40 x 2 Z 10 o am o o o S 10 N 8 gt IT 10 ii il s srul 10 10 10 10 10 108 Pressure head h cm 10s Tm TT Y TTTTTT Ty d K h of Mie 109 X gt gt 510 o Cc o o 2 510 gt x 102 1 10 101 10 10 10 105 Pressure head cm Fig 4 Estimated water retention a c and unsaturated hydraulic conductivity b d curves for the Kumamoto top and Mie bottom Andisols case 1 long dash lines case 2 short dash lines and case 3 solid lines ductivities were almost identical for all three Kumamoto optimizations In addition all of the optimized parameters had small standard errors as reflected by the narrow con fidence intervals sho
227. 632 Fayer M H and Simmons C S 1995 Modified soil water re tention functions for all matric suctions Water Resour Res 31 1233 1238 doi 10 1029 95WR00173 14 125 2013 Gerke H H and van Genuchten M Th 1993 A dual porosity model for simulating the preferential movement of water and solutes in structured porous media Water Resour Res 29 305 319 doi 10 1029 92WR02339 Hamamoto S Perera M S A Resurreccion A C Kawamoto K Hasegawa S Komatsu T and Moldrup P 2009 The solute diffusion coefficient in variably compacted unsatu rated volcanic ash soils Vadose Zone J 8 942 952 doi 10 2136 vzj2008 0184 Hopmans J W and Dane J H 1986 Temperature dependence of soil water retention curves Soil Sci Soc Am J 50 562 567 doi 10 2136 sssaj1986 03615995005000030004x Hopmans J W im nek J Romano N and Durner W 2002 Simultaneous determination of water transmission and reten tion properties Inverse methods In Dane J H and Topp G C ed Methods of Soil Analysis Part 4 pp 963 1008 SSSA Book Ser 5 SSSA Madison WI Iden S C and Durner W 2007 Free form estimation of the unsaturated soil hydraulic properties by inverse modeling us ing global optimization Water Resour Res 43 W07451 doi 10 1029 2006WR005845 Kaveh F and van Genuchten M Th 1992 A further look at a new unsaturated hydraulic conduct
228. 647 653 IRA BA 6 92 1994 172 29 38 Heatherly L G and Russell W J 1979 Effect of soil water po tential of two soils on soybean emergence Agronomy Journal 71 980 982 Helms T C Deckard E L Goos R J and Enz J W 1996a Soil moisture temperature and drying influence on soybean 38 1985 emergence Agronomy Journal 88 662 667 2005 60 6 254 257 Hummel J W Gray L E and Nave W R 1981 Soybean emer gence from field seedbed environments Transactions of the ASAE 24 872 879 Johnson W H and Buchele W F 1961 Influence of soil granule size and compaction on rate of soil drying and emergence of corn Transactions of the ASAE 4 2 170 174 Johnson W H and Henry J E 1964 Influence of simulated row compaction on seedling emergence and soil drying tates Transactions of the ASAE 7 3 252 255 2013 25 EEK K 5
229. A E as a AS amp 5 0 5 8 0 5 A A 5 A D 2 0 4 9 04 o 5 0 3 03 O 0 2 a o 02 o 01 gol mmlglm zlo ejg Jefe IAS Aa 0 0 Es Sr B38 Eggs Jz e 2 l Isls laia lalaa S o ON o Sg el8ieis Elo Sc I ae o ele ele oO O N Lo o r ow olgj g SI5 S15 o LO e S 2 TA Compression Block Tilage Depth Day Depthday Compression Block Tillage Depth Day Tilageday factors and treatments Fig 7 14 28 factors and treatments a 2006 b 2007 1 1 5 2 Tukey 5 Effects of factors on emergence and establishment rate 1 and denote statistical significance level of P gt 0 99 and P gt 0 95 respectively 2 Different letters denote statistically significant P gt 0 95 differences between the series of sampling dates from the summer to the following spring according to Tukey s multiple comparison
230. DER 5 A4 600 words 1 Manuscript title Full name of authors First name 1 Family name 1 Address of institutions of authors Corresponding author Full name of authors 300 words Abstract 5 Key words HAS ECHL EKA 350 5 MM ERD OR H
231. EE RH NWYF RI YR RUDIYANTO N TORIDE M SAKAI and M Th van GENUCHTEN 3 Analysis of suitable condition for soybean planting in rotational clayey paddy fields under risk of excessive dry or wet condition YN EE TE Rat S YOSHIDA H HOSOKAWA and K ADACHI 17 Development of a device for measuring the vertical distribution of radioactivity in soil using photodiode sapissi S SUZUKI H IWASE K NOBORIO M MIZOGUCHI D KOBAYASHI and T ITO 29 Lectures Reviewing classical studies in soil physics Effects of liquid phase electrical conductivity water content and surface conductivity on bulk soil electrical conductivity by J D Rhoades P A Raats and R J Prather en a EE AE EET TETEE Y YANAI T MIYAMOTO and N TORIDE 35 Miscellaneous Poster abstracts at the 2013 JSSP annual meeting eii Fyn etet CR DU CN EE EE 43 Collaboration structure aimed at ressurection of Iitate village 2 H YOKOKAWA and M MIZOGUCHI 53 Excursion tour in Fukushima held after the 55th symposium NS CO A ES Y OSADA 55 Battles of Soil Scientists in Fukushima Japan PTA E E EE TA WY EEE M MIZOGUCHI K NOBORIO and C JOHNSTON 59 Readers column eo eA E Y YF a a AE OT C KATO 6l Wn su A GM VO I SE SE SE ES da Sete Si Y IWATA 63 Announcements a LI Y ae ena BYR yd dn DY DF CN YD OR EEE 65 Editors PoStscript a cdd iw ee Gi CAD YF FU cod Y tata dens aime eae ated 67 Published by Japanese Society of Soil Physics Graduate
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233. OBS E 90 330 MOB 2 EC E pH 5 mm AO Si Eh DO O EC pH
234. School of Agricultural and Life Sciences The University of Tokyo 1 1 1 Yayoi Bunkyo ku Tokyo 113 8657 Japan http js soilphysics com
235. anting 2 and denote statistical significance level of P gt 0 99 and P gt 0 95 respectively 3 Different letters denote statistically significant P gt 0 95 differences between the series of sampling dates from the summer to the following spring according to Tukey s multiple comparison 4 The filled and open symbols represents statistically significant and non significant factors respectively Crosses denote data sets inadeguate for statistical analysis due to the nature of them 3 12 kPa EZ 4 2 2006 2007 Fig 5 Fig 7
236. as determined using the evapora tion method In addition to the pressure heads we also used water retention data in the objective function The satu rated hydraulic conductivity Ks and the pore connectivity factor 4 in the VG hydraulic conductivity function along with several water retention parameters were optimized Different sets of optimizations were conducted by restrict ing the pressure head range of the water retention and ten siometer measurements in the objective function We were especially interested in the role of water retention data at very at low negative pressure heads in the objective func tion We furthermore used the measured pressure head profiles of the samples at the end of the evaporation ex periment to confirm the shape of the estimated hydraulic functions beyond the tensiometer measurement range 2 Material and methods 2 1 Evaporation experiment For the evaporation experiments we used two different Japanese Andisols collected from the surface horizons of two sites One set of soil samples was obtained from the NARO Kyushu Okinawa Agricultural Research Center in Kumamoto and one from the NARO Institute of Vegetable and Tea Science in Mie Japan Collected soil samples were sieved using a 2 mm mesh The disturbed Andis ols were packed uniformly in 16 cm long 3 8 cm diame ter acrylic columns to bulk densities py of 0 48 and 0 75 g cm for the Kumamoto and Mie soils respectively The saturated hydra
237. cause h gt 50 cm covered the entire region of the first slope of the water retention curve Fig 1 We conclude that inde pendently measured water retention data covering a wide range of pressure heads provide very useful information to the parameter estimation process leading to a much more robust optimization of the remaining parameters Kg in this case Note that the standard errors and coefficients of variation have a tendency to increase as the pressure range becomes narrower Table 1 This means that one should still use all available tensiometer data in the objective func tion 4 Conclusions Parameters of the bimodal VG model for two aggre gated Andisols were inversely determined using the evap Estimating the unsaturated hydraulic conductivity of Andisols using the evaporation method 13 oration method Independently measured water retention data from near saturation to very low pressure heads down to 10 cm were included in the objective function in addi tion to soil pressure head data at two depths measured dur ing the evaporation experiments The saturated hydraulic parameter K and the pore connectivity factor along with several sets of water retention parameters were opti mized Since direct 8 measurements are often quite vari able for high porosity Andisols the saturated water con tent was determined from the final water content and the measured cumulative amount of evaporation
238. column weights using an elec trical balance connected to a data logger The evapora tion experiment for the Mie Andisol continued until the pressure head became less than 600 cm at 1 cm depth The evaporation period for the Kumomoto Andisol was al lowed to continue longer until the pressure head at 10 cm depth became less than 500 cm The valves connected to the tensiometers above 10 cm depth were closed at h val ues of about 500 cm to prevent water leakage from the tensiometer cups Durner and Or 2005 Schindler et al 2010 Volumetric water content profiles at the end of ex periments were determined gravimetrically by sectioning the soil columns Pressure head profiles near the surface at the end of experiments for the Kumamoto Andisol were measured using the WP4 potentiameter 2 2 Bimodal van Genuchten model The bimodal water retention Durner 1992 1994 and unsaturated hydraulic conductivity Priesack and Durner 2006 functions based on the van Genuchten Mualem model van Genuchten 1980 Mualem 1976 were used to describe the hydraulic properties of the two Andisols Q h O S WiSi 1 0 6 1 where S is given by S 1 a A 2 Me WiSi 1 Yma 1 SW 3 i K h K x 2 wid I The subscript 7 in these equations represents the number of subregions i 1 2 in our application S is effective satu ration of the i th subregion is t
239. community in Japan to address this enormous chal Johnston lenge The dedication and the novel and practical ap proaches being used are remarkable I found the most Battles of Soil Scientists in Fukushima Japan I was very impressed by work that is being done among the soil FF 1nterestimng and inspiring part was the way the different _ groups of scientists and volunteers have come together Working with local residents Although this is such a large TS complex and difficult problem the session in Tampa was a testament to the significant intellectual resources in Japan that are addressing this prob
240. concentration profiles in a soil are very time consuming and labor intensive work We developed a device for in situ mea surements of the vertical distribution of radioactivity in a soil using a photo diode sensor Four photodiode sensors were separated by lead shielded plates to increase direc tivity at each depth Because the directivity was relatively broad we defined a leakage coefficient to compensate the broad directivity by introducing a matrix expression With a field test of the device in an undisturbed rice field in Iitate Village Fukushima we confirmed that the vertical distri bution of soil radioactivity was properly measured with the device developed Key Words radiocaesium vertical radioactivity distribu tion photodiode matrix of leakage coefficient decontam ination 1 3 5 cm 2011 2 2012a EK
241. des and Ingvalson 1971 5 Rhoades et al 1976 4 D a b 0 EC ECw a b Fig 6 4 Koa b EC ECa ECw Rhoades et al 1976 2 5 56 dS m7 EC fi EC BC 4 dS m EC EC BC Shainberg et al 1980 Nadler and Frenkel 1980 EC
242. descriptions of hy draulic properties for aggregated soils Soil Sci Soc Am J 64 1252 1262 doi 10 2136 sssaj2000 6441252x Dane J H and Hopmans J W 2002 Water retention storage In Dane J H and Topp G C ed Methods of soil analysis Part 4 pp 675 680 SSSA Book Ser 5 SSSA Madison WI Dorel M Roger Estrade J Manichon H and Delvaux B 2000 Porosity and soil water properties of Caribbean vol canic ash soils Soil Use Manage 16 133 140 doi 10 1111 J 1475 2743 2000 tb00188 x Durner W 1992 Predicting the unsaturated hydraulic con ductivity using multi porosity water retention curves In van Genuchten M Th Leij F J and Lund L J ed Indirect methods for estimating the hydraulic properties of unsaturated soils Proc Intl Workshop Riverside pp 185 202 CA 11 13 Oct 1989 U S Salinity Lab Riverside CA Durner W 1994 Hydraulic conductivity estimation for soils with heterogeneous pore structure Water Resour Res 30 211 223 doi 10 1029 93WR02676 Durner W and Or D 2005 Soil water potential measurement In Anderson M G and McDonnell J J ed Encyclopedia of Hydrological Sciences pp 1089 1102 John Wiley amp Sons Ltd doi 10 1002 0470848944 hsa077a Durner W and Iden S C 2011 Extended multistep outflow method for the accurate determination of soil hydraulic prop erties near water saturation Water Resour Res 47 W08526 doi 10 1029 2011WR010
243. ding 1day 2days 3days Seeding 1day 2days 160 180 dc b 2006 3 d 2007 5 T SS 140 SS 160 amp 120 3cm 140 3cm a m7cm Fn m7cm 100 5 80 5 100 gt 5 Ed 5 80 Cc Cc 60 O 40 8 L 9 5 20 20 WR Seeding 1day 2days 3days Seeding 1day 2days Fig 4 a 2006 b 2006 3 c 2007 d 2007 5 16 Change in water content of seeds after planting a Planted soon after the tillage in 2006 b Planted three days after the tillage in 2006 c Planted soon after the tillage in 2007 d Planted five days after the tillage in 2007 Data variation caused by the factors except planting day is represented by error bars The figure compares the effect due to planting dates alone 3 4 Bme 7 CAS FA GEIS CRY E Gan aad Fig J KOY
244. draulic conductivity in unsaturated porous media ac counting for film and capillary flow Water Resour Res 44 W11417 doi 10 1029 2008WR007136 Peters A and Durner W 2010 Reply to comment by N Shokri and D Or on A simple model for describing hy draulic conductivity in unsaturated porous media accounting for film and capillary flow Water Resour Res 46 W06802 doi 10 1029 2010WR009181 Peters R R and Klavetter E A 1988 A continuum model for water movement in an unsaturated fractured rock mass Water Resour Res 24 416 430 doi 10 1029 WR024i003p00416 Priesack E and Durner W 2006 Closed form expression for the multi modal unsaturated conductivity function Vadose Zone J 5 121 124 doi 10 2136 vzj2005 0066 Saito H im nek J and Mohanty B 2006 Numerical anal yses of coupled water vapor and heat transport in the vadose zone Vadose Zone J 5 784 800 doi 10 2136 vzj2006 0007 Sakaguchi A Nishimura T and Kato M 2005 The effect of entrapped air on the quasi saturated soil hydraulic conductiv ity and comparison with the unsaturated hydraulic conductiv ity Vadose Zone J 4 139 144 doi 10 2136 vzj2005 0139 Sakai M and Toride N 2007a Optimum conditions for pre dicting unsaturated hydraulic properties using the evaporation method J Jpn Soc Soil Phys 106 33 46 Sakai M and Toride N 2007b Soil water hydraulic functions for a sandy soil and an aggregat
245. dy direct measure ment of saturation can be guite vulnerable also to small measurement errors Since we fixed 6 based on water mass balances of the sample K is probably best treated as fitting parameter in the evaporation method Initial val ues of all of the parameters used in the optimizations for the two Andisols are listed in Table 1 We optimized the K and values for three cases involv ing different combinations with the water retention param eters 1 only two hydraulic conductivity parameters i e Ks while keeping the water retention parameters fixed according to the independently measured water retention functions 2 adding the water retention parameters of the first subregion i e Ks 01 n1 w2 in the optimization and 3 further including the retention parameters of the second subregion i e Ks l 01 11 W2 02 n2 The val ues of 6 and 6 0 remained fixed in all optimizations 3 Results and discussion 3 1 Parameter estimation In earlier work im nek et al 1998 showed that a single set of tensiometer readings near the sample surface was sufficient to yield accurate estimates of the soil hy draulic parameters using the evaporation method Our ex periments confirmed this in that similar results were ob tained irrespective of including pressure head data from points deeper in the columns Sakai and Toride 2007a found that using pressure heads at two different depths in the objec
246. ect of ex changeable sodium percentage cation exchange capacity and soil solution concentration on soil electrical conductivity Soil Sci Soc Am J 44 469 473 BIG 2012 ERZ E 2011 64 71 Ward A L Kachanoski R G and Elrick D E 1994 Labora tory measurements of solute transport using time domain re flectometry Soil Sci Soc Am J 58 1031 1039 AY 4B 41 x TDR 6 EC EC ECy 9 4 EC EC 9 EC Rhoades et al 1976 Rhoades
247. ed soil J Jpn Soc Soil Phys 107 63 77 Schaap M G and Leij F J 2000 of unsaturated hydraulic conductivity with the Mualem van Genuchten model Soil Sci Soc Am J 64 843 851 doi 10 2136 sssaj2000 643843x Schelle H Iden S C Peters A and Durner W 2010 Analysis of the agreement of soil hydraulic properties obtained from Improved prediction multistep outflow and evaporation methods Vadose Zone J 9 1080 1091 doi 10 2136 vzj2010 0050 Schindler U Durner W von Unold G Mueller L and Wieland R 2010 The evaporation method Extending the measurement range of soil hydraulic properties using the air entry pressure of the ceramic cup J Plant Nutr Soil Sci 173 563 572 doi 10 1002 jpln200900210 Shoji S Nanzyo M and Dahlgren R A 1993 Volcanic ash soils Genesis properties and utilization pp 1 288 Elsevier Amsterdam Netherlands im nek J Wendroth O and van Genuchten M Th 1998 Pa rameter estimation analysis of the evaporation method for de termining soil hydraulic properties Soil Sci Soc Am J 62 894 905 doi 10 2136 sssaj1998 03615995006200040007x im nek T ejna M Saito H Sakai M and van Genuchten M Th 2008 The Hydrus 1D software package for simu lating the movement of water heat and multiple solutes in variably saturated media Version 4 0 HYDRUS Softw Ser 3 Dep of Environ Sci Univ of California Riverside Spohrer K
248. gations because of the possible effects of film flow Peters and Durner 2008 diffusion of water vapor Saito et al 2006 Peters and Durner 2010 and the effect of shrinkage Dorel et al 2000 3 3 Pressure head measurement range We next demonstrate the effect of using different ranges of the pressure head data measured in the columns during the evaporation experiments in the inverse analysis while fixing in the objective function the bimodal water retention parameters 0 Os 01 n1 W2 02 n2 as determined from the independently measured retention data These scenar ios are the same as case in that only the conductivity parameters K are optimized except that we used dif ferent ranges of the measured pressure heads in the op timizations only data for which h gt 200 cm case 5 h gt 100 cm case 6 and h gt 50 cm case 7 The es timated parameter values for these three cases 5 to 7 are given in Table 1 Fig 7 shows the estimated K h plots for the Kumamoto and Mie Andisols obtained with the different pressure head measurement ranges The conductivity function for case 1 is the same as shown in Fig 4 Except for the much lower K h curve for case 7 of the Kumamoto Andisol the plots neglecting the lower pressure data did not affect the K h results very much they produced almost identi cal K h curves as for case 1 For the Mie Andisol even case 7 did give a good estimate of K likely be
249. h 50 cm in Fig 3b should not change the water content very much This ex 10 123 2013 0 8 PETIA Terere rer rr rr 103 TI Tr T a 0 h of Kumamoto b K h of Kumamoto o a T o co 20 4 O Observed ob Case 3 0 3 Case 4 o 6 0 2 o 2 0 1 observed pressure head range 0 po itil po isl pa iil soaron os sasu 100 101 102 10s 104 105 Pressure head h cm 0 8 c h of Mie o 2 2 w P o o N T T T T Water content 6 cm cm 3 x T observed pressure _ head range 10 40 10 10 104 105 Pressure head h cm o Q o Hydraulic conductivity K cm days 1 9 10 po iil oo sl sosul 10 10 10 10 10 10 Pressure head h cm d K h of Mie Hydraulic conductivity K cm dayS 1 o a a o 10 10 10 10 105 Pressure head h cm Fig 5 Estimated water retention a c and unsaturated hydraulic conductivity b d curves for the Kumamoto top and Mie bottom Andisols Results were obtained with solid lines and without dashed lines including water retention data at the low pressure heads in the objective function plains why the small change in the water retention curve obtained by additionally optimizing the first subregion re tention parameters 0 n1 w2 still produced a significant improvement in the press
250. he soil water pressure head L is the volumetric water content LL 3 and 6 are the saturated and residual water contents LL respectively n O L and m 1 1 n are shape parameters subject to gt O and n gt 1 wi and w3 are the weighing factors subject to 0 lt w lt 1 and w1 W2 1 K is the hydraulic conductivity LT Ks is the saturated hydraulic conductivity LT and is a pore connectivity coefficient The S variable subject to Ci gt 05 is as sociated with the first subregion of 6 at the higher water contents while 2 corresponds to the second subregion at the lower water contents The hydraulic functions given by Egs 1 to 3 are further referred to here as the bimodal VG model Note that the hydraulic functions contain a to tal of nine parameters Seven of these parameters Os Or O 11 W2 Op n2 relate primarily to the water retention curve and two additional parameters Ks to the unsatu rated hydraulic conductivity function 2 3 Parameter optimization Parameters of the bimodal VG model for our two Andisols were optimized using version 4 08 of the HYDRUS ID progress com en Default aspx hydrus 1d of im nek et software package http Www pc al 2008 The calculations assumed applicability of the Richards eguation to one dimensional vertical water flow under isothermal condition as follows 99 9 dh Ta 4 whe
251. ivity eguation Iranian J Agric Sciences 23 24 32 Ma ek M Smolar J and PetkovSek A 2013 Extension of measurement range of dew point potentiameter and evap oration method Proc 18th Intl Conf Soil Mechanics and Geotechnical Engineering pp 1137 1142 Paris Mallants D Jacgues D Tseng P H van Genuchten M Th and Feyen J 1997 Comparison of three hydraulic prop erty measurement methods J Hydrol 199 295 318 doi 10 1016 S0022 1694 96 03331 8 Miyamoto T Annaka T and Chikusi J 2003 Soil aggregate structure effects on dielectric permittivity of an Andisol mea sured by time domain reflectometry Vadose Zone J 2 90 97 doi 10 2136 vzj2003 9000 Mohanty B P Bowman R S Hendrickx J M H and van Genuchten M Th 1997 New piecewise continuous hy draulic functions for modeling preferential flow in an intermit tent flood irrigated field Water Resour Res 33 2049 2063 doi 10 1029 97WR01701 Mualem Y 1976 A new model for predicting the hydraulic conductivity of unsaturated porous media Water Resour Res 12 513 522 doi 10 1029 WR012i003p00513 Nanzyo M 2002 Unigue properties of volcanic ash soils Glob Environ Res 6 99 112 Othmer H Diekkriiger B and Kutilek M 1991 Bimodal porosity and unsaturated hydraulic conductivity Soil Sci 152 139 150 doi 10 1097 00010694 199109000 00001 Peters A and Durner W 2008 A simple model for describ ing hy
252. jae E o Compression Block Tilage Depth Day Tilageday Factors and treatments Fig 8 1 1 5 2 Tukey T 5 Effects of factors on damage of seeds by seed corn flies 1 and denote statistical significance level of P gt 0 99 and P gt 0 95 respectively 2 Different letters denote statistically significant P gt 0 95 dif ferences between the series of sampling dates from the summer to the following spring according to Tukey s multiple comparison 3 Ald JRA 1994 2002
253. kuba 305 8609 Japan 3Graduate School of Bioresources Mie University 1577 Kurima Machiya Tsu 514 8507 Japan 2013 10 22 2013 11 25 TDR 9 EC Rhoades Rhoades Jim Rhoades U S Salinity laboratory soil salinity 4 EC EC Wl CHDI 1 cm ERICHA L T EC Richards 1966
254. land The present study aimed to clarify the suitable condition of soybean planting for stable es tablishment in clayey paddy fields by taking account the particularity of physical properties of clayey paddy soils The effects of four experimental factors intensity of com pression days after tillage seeding depth and tilth on the germination and growth of soybean were investigated by field experiments following the randomized block design The seeding depth and the timing of seeding after tillage were revealed to be the most influential factor while com pression had supplementary role Mean dimension of ag gregates did not affect the germination and growth under the poor tilth condition The results suggest that seed ing should be conducted soon after tillage but the optimal depth depends on the expected weather in the following days However if drainage efficiency of the field can be improved seeding deeply supposed to be less risky unless enough rain is surely expected Key Words clayey paddy soybean soil aggregates ger mination establishment 1
255. lem I hope that there can be SSSA continued exchanges between the United States and Japan that would provide an opportunity for our students and Sci entists to see the different remediation strategies being used and to interact with the various groups involved As a point of moving forward I think this session was logical starting point looking at where the contamination exists in the soils of Fukushima and the transport of radioactive Cs in the soil profile I think that continued linkages with the soil chemistry and soil mineralogy communities would be beneficial For example another session in Tampa was fo cused on K fixation in soils and the information that was presented in that session has direct relevance to the Cs Fig 1 Web https scisoc confex com crops 2013am webprogram Session11722 html participate in this Session problem in Fukushima Thank you for the opportunity to J Jpn Soc Soil Phys No 125 p 61 62 2013 BR EFA RIES Reader s Column
256. length of soil column used Hopmans and Dane 1986 Dane and Hopmans 2002 Sakaguchi et al 2005 The value of K can easily change with very small Estimating the unsaturated hydraulic conductivity of Andisols using the evaporation method Table 1 Values of the optimized hydraulic parameters of the bimodal VG model and their standard errors SE and coefficients of variation CV obtained with the evaporation method for cases 1 through 7 of the Kumamoto and Mie Andisols Cas Or Os 1 nl K l w2 oo no cm cm cm md O cm O Kumamoto initial 0 0 78 0 057 1 88 200 0 5 0 544 0 00011 1 44 1 703 0 751 SE 11 0 107 CV 0 016 0 142 2 0 045 1 92 312 0 054 0 544 SE 0 001 0 03 26 0 022 0 003 CV 0 022 0 015 0 083 0 418 0 005 3 0 044 1 96 343 0 436 0 549 0 00013 1 39 SE 0 001 0 03 32 0 214 0 003 0 00001 0 02 CV 0 023 0 017 0 093 0 492 0 006 0 076 0 011 4 0 055 1 87 312 0 614 0 541 0 00025 1 55 SE 0 001 0 04 38 0 231 0 008 0 00006 0 31 CV 0 018 0 020 0 122 0 377 0 014 0 232 0 203 5 971 2 301 SE 18 0 227 CV 0 019 0 099 6 208 0 007 SE 42 0 016 CV 0 202 2 167 28 0 001 SE 6 0 012 CV 0 214 15 250 Mie initial 0 0 629 0 129 2 41 1000 0 5 0 509 0 00062 1 28 1
257. lication Japan Academic Association for Copyright Clearance JAACC 41 6 Akasaka 9 chome Minato ku Tokyo 107 0052 Japan TEL 81 3 3475 5618 FAX 81 3 3475 5619 E mail kammori msh biglobe ne jp 1255 20134412 20 T 113 8657 1 1 i 03 584 1 5344 FAX 03 5841 8169 spsyomu ml affrc go jp http js soilphysics com ent 235 1153264 01350 2 40943 http js soilphysics com ent E mail kibyos1 ml affrc go jp El T 116 0011 7 12 16 ISSN 0387 6012 Journal of the Japanese Society of Soil Physics No 125 December 2013 Contents Foreword daeoni ge DnE RE DF Yd o T NAKATSUJ 1 Original Papers Estimating the unsaturated hydraulic conductivity of Andisols using the evaporation method ER
258. of the second subregion parameter 02 n2 The discrep ancies shown in Fig 5 for case 4 are a reason why op timized hydraulic functions are generally assumed to be reliable only within the range of the tensiometer measure ments im nek et al 1998 Hopmans et al 2002 Table 1 shows that most of the standard errors of the estimated parameters for case 3 were smaller than those for case 4 which indicates that including water retention data at the lower pressure heads in the objective function will reduce parameter uncertainty and lead to more reliable parameter values Although observed pressure head data over a 5 day pe riod were used for parameter optimization of the Ku mamoto Andisol Fig 3a the evaporation experiments continued for 6 08 days until the pressure heads at 10 cm depth reached approximately 500 cm To confirm the ac curacy of the hydraulic properties of cases 3 and 4 for the Kumamoto Andisol pressure heads were simulated for a longer time period using case 3 and 4 properties Fig 6 shows observed WP4 data near the surface with one ten siometer datum at the 10 cm depth and predicted final pressure head profiles after 6 08 days The simulation us ing case 3 parameters agreed well with the observed pres sure profile near the surface whereas the prediction using case 4 parameters overestimated the pressure heads These 12 125 2013 103 morr rr rr 10
259. pical Acrisol from transient field data using initial values of the fitted water retention parameters When the hydraulic properties are estimated inversely using the evaporation method the optimized hydraulic functions are generally assumed to be representative only within the range of the tensiometer data No guarantee exists that the hydraulic functions can be extrapolated be yond the invoked pressure measurement range im nek et al 1998 and Hopmans et al 2002 suggested the ap plicable range of the model predictions could be extended by including independently measured hydraulic data in the objective function Sakai and Toride 2007b estimated the unsaturated conductivity of the model of Fayer and Simmons 1995 for a dune sand as well as the bimodal VG model for an Andisol using the evaporation method in combination with water retention data from close to saturation to very dry conditions down to pressure heads of approximately 105 cm They showed that the ob served pressure heads agreed well with the model pre dictions when an appropriate hydraulic function was used to describe the water retention data over a wide range of pressure heads The validity of the estimated unsaturated hydraulic conductivity beyond the pressure measurement range however was not discussed in detail in their study The objective of this study was to determine parame ters of the bimodal VG model for Andisols over a wide range of pressure heads
260. re z is the vertical coordinate L positive upward and f istime T The initial and boundary conditions for the evaporation experiment are given by e g im nek et al 1998 h z 0 hi 2 5 ol K h z i evap L t 6 a 0 1 K H FE 1 0 7 where h z is the initial pressure head L distribution in the column gevap f is the time variable evaporation rate LT at the soil surface and L is the z coordinate of the soil surface L The initial condition z was linearly interpolated using the initial tensiometer readings while gevap f was described with a polynomial function fitted to the observed evaporation rate as shown in Fig 2 A no flow boundary condition was imposed at the bottom boundary We note that vapor flow was not included in the flow model thus assuming that the effects of vapor flow an 123 2013 a Kumamoto O Observed Fitted Evaporation rate gevuap cm d y 0 0024x8 0 0515X5 0 4336x4 1 8186 x 3 9418 x2 4 1538 x 2 6124 4 1 4 L 1 L L 1 1 1 0 1 2 3 4 5 Time t days A b Mie O 2r 1 OO i X o o a A 8 slap amp fi Wo O ON Owen a 1 CFA O o MOSM Ses eo So O o 5 BUFO o Roe g Coy wu 0 5 y 0 03x2 0 337x3 1 3273x2 2 3103x 2 5649 0 1 1 1 1 1 1 4 1 1 0 1 2 3 4 5 Time t days Fig 2 Evaporation rate from the surface of the Kumamoto
261. rtinus Th van GENUCHTEN Abstract Parameters of the bimodal van Genuchten VG hydraulic functions for two aggregated Andisols were in versely determined using the evaporation method Initial estimates of the water retention parameters were deter mined from separate retention measurements which fa cilitated rapid convergence of the parameter optimization process regardless of the number of optimized parame ters When the bimodal water retention parameters were fixed according to the independently measured retention data from near saturation to very low pressure heads down to 10 cm it was possible to estimate the unsaturated hydraulic conductivity K 4 by optimizing only two con ductivity parameters Ks Since the flat region of the bi modal retention curve at intermediate pressures is difficult to measure precisely however we still recommend opti mizing all bimodal VG parameters to yield the best overall results Including water retention data at very low pressure heads in the dry range extended the applicable range of the model predictions at least down to pressure heads of ap proximately 10 cm Key Words unsaturated hydraulic conductivity wa ter retention curve aggregated soil Andisol evaporation method 1 Introduction Andisols generally are developed from volcanic ash consisting of noncrystalline materials such as allophone imogolite Al humus complexes and ferrihydrite Shoji et al 1993 Nanz
262. ssure heads In addition to the pressure head measurements obtained during the evaporation experiments for h gt 600 cm we included in the objective function thus far also all of the in dependently measured water retention data between 105 and 5 cm Fig 1 This is to obtain reliable estimates of K h in the low pressure head range as recommended by Siminek et al 1998 and Hopmans et al 2002 To test the need for retention data in the dry range we compared hydraulic functions optimized with case 3 and without case 4 including the independent water retention data at the low pressure heads in the objective function The op timized conditions for case 4 were the same as for case 3 including the initial estimates except that case 4 consid 3 cm The esti ered only water retention data for gt 10 mated parameter values for case 4 are also listed in Table 1 For both Andisols good agreement between the observed and fitted pressure heads in the columns was obtained very similar to case 3 as shown in Fig 3 Fig 5 shows the observed and fitted water retention curves and the estimated unsaturated hydraulic conductiv ity functions for cases 3 and 4 The observed water re tention data in the dry range were severely underestimated using case 4 relative to case 3 Since no information was given for h lt 10 cm for the case 4 optimizations it is not surprising that this case converged to different values
263. tion method 11 Soil depth z cm do 10 OO Observed Case 3 AZF ese Case 4 14 16 1 1 1 1 12000 9000 6000 3000 0 Pressure head h cm Fig 6 Observed and predicted pressure head profiles after 6 08 days for the evaporation experiment of the Kumamoto Andisol Results were obtained with solid lines case 3 and without dashed lines case 4 including water retention data at the low pressure heads in the objective function Circles represent WP4 data and the square a tensiometer datum lowing Mualem 1976 As pointed out in several studies e g W6sten and van Genuchten 1988 Kaveh and van Genuchten 1992 Schaap and Leij 2000 Spohrer et al 2006 can be quite variable depending upon soil type Using the case 3 optimization was found to be 0 436 for the Kumamoto Andisol and 0 011 for the Mie Andisol More data are clearly needed to obtain a better definition of possible values for Andisols Our parameter optimizations were found to converge guickly in all cases less than 10 iterations 5 8 and 8 it erations for cases 1 to 3 respectively of the Kumamoto Andisol and 8 9 and 9 iterations for cases to 3 of the Mie Andisol This included case 3 which had the largest number of optimized parameters Our results suggests that using water retention parameters fitted to independently observed retention data as initial estimates will facilitate convergence 3 2 Water retention data at low pre
264. tive function produced smaller standard errors for Ks and than when data from only one depth were used Since K and were our primary concern we will show be low results when using pressure heads at 1 and 3 cm depths in the objective function given by Eg 8 Still obtaining additional tensiometer measurements at other depths may well be useful for backup information in case some of ten siometers failed to work properly Hopmans et al 2002 Fig 3 shows fitted and observed pressure heads as a function of time at the 1 and 3 cm depths for the Kumamoto and Mie Andisols Estimated water retention and unsat urated hydraulic conductivity functions corresponding to the three optimization cases of our study are shown in Fig 4 The optimized parameter values and their standard er rors as well as the coefficients of variations defined as the optimized values divided by the standard errors for the bi modal VG model are listed in Table 1 For the Kumamoto Andisol all three optimization sce narios i e case 1 with Ks optimized case 2 with Ks 6 ni w2 optimized and case 3 with K O1 11 W2 Oz n2 optimized gave almost identical re sults All three cases produced excellent agreement with the observed pressure heads at the 1 and 3 cm depths Fig 3a Predicted pressure heads for cases 2 and 3 were al most identical The three cases also produced close agree ment with the observed water retention data Fig
265. uch on the initial estimates of the unknown parameters In addition to the transient mea surements the objective function could also include in dependently measured soil water retention or unsaturated hydraulic conductivity data points Parameter uncertainty 4 5125 2013 0 8 CO mmm Hmm O Hanging water rrem TTTrrr YT TTTT 0 7 Pressure plate 2 O WP4 o 06 Bimodal VG L o 0 5 Kumamoto 04 o L c 8 03 o 0 2 L 0 1 TY ll ll ll dy 0 109 10 10 10 104 10 Pressure head h cm Fig 1 Water retention curves for the Kumamoto and Mie An disols fitted with the bimodal VG model solid line Retention data were obtained with a hanging water column open circles a pressure plate crosses and a WP4 dewpoint potentiameter open sguares i e the reliable range of the optimized parameter values generally will be reduced by including independently mea sured soil hydraulic property data in the objective function but this may affect the goodness of fit between modeled and experimental data im nek et al 1998 Hopmans et al 2002 More rapid minimization of the objective func tion may be achieved by using as initial estimates water retention parameters fitted to observed retention data For example Spohrer et al 2006 succeeded in estimating 25 parameters of the bimodal VG model for four soil layers of a tro
266. ulic conductivity Ks based on the falling head method was estimated to be approximately 200 cm d for the Kumamoto Andisol and 1000 cm d7 for the Mie Andisol Fig 1 shows water retention curves as mea sured using a hanging water column for the pressure head h range 200 lt h lt 5 cm using a pressure plate for 1 2 x 104 lt h lt 250 cm and a WP4 dew point poten tiameter Decagon Devices Pullman WA based on rela tive humidity measurements equilibrated with the soil wa ter pressure for the range 10 lt h lt 3 x 10 cm Al though WP4 measurements are generally used for pressure heads below 10 cm we applied the WP4 potentiameter to the higher pressure heads up to approximately 3 x 10 cm with considerable care as suggested by Macek et al 2013 Volumetric water contents for the WP4 measure ments were determined from the gravimetric water con tents and the bulk density of the soil After slowly saturating the soil samples from the bot tom the water supply was closed and evaporation was al Estimating the unsaturated hydraulic conductivity of Andisols using the evaporation method 5 low to start using a fan to blow air away from the soil surface in a 25 C constant temperature room Pressure heads were monitored using five tensiometers connected to pressure transducers at 1 2 3 5 and 10 cm depths Cumulative amounts of evaporation were calculated from measurements of the soil
267. ure head simulations By com parison the pressure range of the flat region of the Mie Andisol is wider and the soil water capacity smaller than of the Kumamoto Andisol Fig 4a versus and 4c We emphasize that the discrepancies in the pressure head were apparent when optimizing only the conductivity parame ters case 1 and then only for the Mie Andisol but not for the Kumamoto soil We also note that measurements of water retention data in the flat part of the retention function are often subject to errors It is not easy to precisely determine the water con tent and pressure head relationships when the soil water capacity is very small Pressure plates are generally used to measure water retention in this region Nonequilibrium conditions poor contact between the soil sample and the plate Cresswell et al 2008 Bittelli and Flury 2009 and hysteresis in the sample preparation often affect the mea surements For this reason it may be better to optimize at least the first subregion parameters 0 711 w2 also But as long as water retention data over a wide range of pressure heads are available and can be used in the objective func tion as Durner 1994 also suggested case 3 optimization should yield the best overall results We mention some concern about the value of the pore connectivity coefficient 4 which is often fixed at 0 5 fol Bstimating the unsaturated hydraulic conductivity of Andisols using the evapora
268. wn in Table 1 These results suggest that when reliable water retention data are available and used in the objective function it is possible to predict K A by optimizing only the two conductivity parameters Ks This implies that as long as the water retention parameters can be properly determined using observed water retention data the number of parameters in Mualem type soil hy draulic functions even for the bimodal VG model as given by Eg 3 should not pose a problem in the optimization Results for the Mie Andisol were different Case 1 for this soil failed to fit the sudden pressure drop at h 50 cm after about 3 5 days in Fig 3b with the fitted pres sure heads being greater than the observations Cases 2 and 3 improved the agreement between observed and fitted pressure heads As the number of optimized parameter in creases the bimodal VG model clearly has more flexibility in fitting the pressure head data Improved fitting of the pressure head data could be achieved also by sacrificing the close fit of the water retention data However com pared to the differences between the fitted and observed pressure heads in Fig 3b the fitted water retention curves in Fig 4c were very similar for all three cases The bi modal water retention curve of Fig 4c has a relatively flat region between about 50 cm and 10 cm Since the soil water capacity d0 dh is small in that flat region the abrupt pressure drop below
269. yo 2002 Andisols cover 17 of the land surface in Japan where they are widely used for agricul ture Water flow and solute transport processes in Andisols are of considerable interest because of their unigue phys ical and chemical properties They typically have a very low bulk density and a well developed aggregated struc ture Because of this Andisols usually exhibit a compos ite stepwise water retention function reflecting distinct Dept of Civil and Environmental Engineering Bogor Agricultural Univ Indonesia 2Graduate School of Bioresources Mie Univ Tsu Mie 514 8507 J apan Corresponding authour 3Dept of Mechanical Engineering Federal University of Rio de Janeiro UFRJ Rio de Janeiro RJ Brazil 2013 9 3 2013 9 20 but interacting inter aggregate and intra aggregate pore re gions Miyamoto et al 2003 Several bimodal or multimodal functions have been pro posed over the years to account for the additive effects of inter and intra aggregate pore regions to the overall soil hydraulic properties Peters and Klavetter 1988 Othmer et al 1991 Gerke and van Genuchten 1993 Mallants et al 1997 Mohanty et al 1997 One frequently used multimodal formulation stems from Durner 1992 1994 who developed a composite retention function by summing multiple van Genuchten VG models

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