Manual - Haneberg Geoscience
Contents
1. Figure 2 Theoretical Background Almost all existing spatially distributed rational slope stability models are based on variations of the infinite slope idealization Although no slope perfectly satisfies the assumptions of the infinite slope model many if not most natural landslides have relatively low thickness to length ratios and are predominantly translational Therefore although it is not suited for detailed design level investigations the infinite slope idealization provides a useful reconnaissance level approximation that can help to identify areas in which more detailed field investigations and office calculations are warranted It is in essence a reconnaissance scale tool in much the same sense as a quadrangle or watershed scale geologic map See Haneberg 2004 A rational probabilistic method for spatially distributed landslide hazard assessment Environmental amp Engineering Geosciences v 10 p 27 43 for a more complete discussion of the methods used by PISA m and a complete list of references Haneberg 2000 Deterministic and probabilistic approaches to geologic hazard assessment Environmental amp Engineering Geosciences v 6 no 1 p 209 226 provides an overview of probabilistic methods including a discussion of probabilistic slope stability analyses SHaneberg Geoescience 39th Avenue SW Seattle WA 98146 aes ae 0846 info haneberg com www haneberg com Static Slope Stability PISA m is based on the2. PISA m accepts maps including DEMs in either Arc ASCII grid format or Surfer ASCII grid format In each case the file consists of a header followed by a grid of values representing elevations soil unit types or forest cover types Although the grids are identical between the two formats the headers are not Therefore users must specify which format is to be read Specifying the wrong format will produce a run time error and the program will stop If you have a map file that is not in one of the two ASCII grid formats you can convert it using many different GIS programs The Arc ASCII grid format in particular in an almost universal file format The free program Landserf www landserf org reads many common DEM formats and will export Arc ASCII grid files Arc ASCII Grid Input and Output Here is an example of the 6 line header for an Arc ASCII grid file ncols 450 nrows 300 xllcorner 1402500 0 yllicorner 150050 0 cellsize 50 0 nodata_value 32766 0 dione a inne Rie ae cere Seattle WA 98146 aes ae aues nfo erg com www haneberg com The ncols and nrows values are the numbers of columns and rows in the DEM The next two variables xllcorner and yllcorner are the geographic coordinates of the lower left hand corner of the DEM They are typically given as UTM coordinates or some kind of local coordinates for example state plane coordinates in the United States The fifth variable cellsize is the DEM grid spacing and m
3. Variance is the square of the standard deviation of a random variable 7Haneberg Geoescience 39th Avenue SW Seattle WA 98146 aes ae 0846 info haneberg com www haneberg com Uniform Distribution X X max X min 2 2 s X nax a x 12 Extreme Value Type I Distribution a 0 577216 B mB x o Triangular Distribution max apex min X 2 s Bd Meas E Siel Talea ia X max X max E X min pi 18 P PERT Distribution X x ax AX pest X min 6 2 s Z X nax X min x 36 Slope Angle Means and Variances 4 a b 5 a b 6 a b 7 a b Slope angle variances are treated differently than geotechnical variables The mean value for slope at DEM grid point r c is estimated using a standard second order accurate finite difference approximation 2 2 Cae 24 Cane Cie 2As arctan aks 8 Haneberg Geoescience 39th Avenue SW Seattle WA 98146 ane gas 0846 info haneberg com www haneberg com where f is in radians PISA m assumes that the elevation error in the input DEM is constant throughout the map area In such a case a FOSM expression for the slope angle variance at point r c is 2 2 2 2 op Op op op op B Bs Bc Pee s 9 rate ae an OZ e y Evaluation of the derivatives yields 2 2 3 8 As s 10 4 As a 7 Ba sa Ze in which the variance has units of rad Examination of equation
4. 10 shows that the slope angle variance will be inversely proportional to slope angle In other words a given elevation error will have a larger influence on slope angle uncertainty when the points being used to calculate the slope angle are similar in value than when they are different Probability of Sliding Once the mean and variance of the factor of safety have been calculated results can be expressed in terms of the probability of sliding or a slope reliability index The former requires an assumption about the underlying probability distribution of the factor of safety whereas the latter does not Numerical experiments using Monte Carlo simulations have suggest that the factor of safety distribution is generally described more faithfully by a lognormal distribution than the normal distribution The probability of sliding is obtained from the cumulative distribution function for a specified probability distribution having the calculated mean and variance and evaluated at the critical value of FS 1 or Prob FS lt 1 CDF FS 1 11 in which CDF FS 1 is the cumulative distribution function of FS evaluated at the limiting value of FS 1 Equation 10 can be evaluated for any cumulative distribution function defined by a mean and variance so it is not necessary to assume that the results are normally distributed PISA m assumes that FS follows a lognormal distribution The probability of stability is the complement of the probability
5. North South and elevation values PISA m calculates a cell size value from the x and y data ranges and will return an error message and quit if the cell size calculated from the x information does not equal that calculated from the y information If that happens check your input file for mistakes in the x and y value ranges Surfer ASCII grid files do not contain a no data value but PISA m requires one and will prompt the user to enter a no data value from the keyboard In the example used here the DEM being read has a no data value of 32766 the default value for some GIS programs Because the Surfer format does not recognize the existence of no data values and the no data value is much smaller than any of the real 7Haneberg Geoescience SW Seattle WA 98146 aes ae neue ROGNE bar com www haneberg com elevation values it appears as the lowest elevation value Users should be aware that no data values far outside the range of the elevation data can complicate plotting in Surfer and perhaps other programs because the vertical axis will be automatically scaled to range from the no data value in this case an elevation of 32766 to the maximum elevation value It may help to specify the no data value as the smallest of the elevation values or zero Programs specifically designed to deal with raster GIS data generally deal with no data values much better than does Surfer Input File Consistency Regardless of which map format is
6. an approach that is firmly established in the geotechnical hydrological and geographical information system literature A mean value of F S is first calculated using the mean values of each of the independent variables or FS FS x 2 For uncorrelated independent variables the variance or second moment about the mean of FS can then be estimated by the first order truncated Taylor series dione a a Rie ae see Seattle WA 98146 aes ae aues nfo erg com www haneberg com E Daj 2 3 in which s is the variance of the i independent variable The terms in parentheses are evaluated using mean values for each of the independent variables implying that each of the derivatives is a constant and their squares are lengthy equations when all of the variables in equation 1 are included The expressions used in PISA m were derived using the symbolic manipulation capabilities of the computer program Mathematica and the resulting expanded version of equation 3 occupies 26 lines in the Fortran source code Input Probability Distributions Although FOSM approximations are often associated with normal distributions this is not a necessary restriction Any distribution for which a mean and variance can be derived can be used although significant errors can arise if the distribution is not symmetric or nearly so Therefore PISA m may not be appropriate if there is evidence that one or more of the input variables follows a strongly asy
7. factor of safety against sliding for a forested infinite slope C Cs la V2 Year Ve Vm H D cos Ptang FS 1 l D Yar Yn H D sinf cos in which c cohesive strength contributed by tree roots force area c cohesive strength of soil force area q uniform surcharge due to weight of vegetation force area Ym unit weight of moist soil above phreatic surface weight volume Y sar unit weight of saturated soil below phreatic surface weight volume y unit weight of water 9810 N m of 62 4 lb ft D thickness of soil above slip surface length H height of phreatic surface above slip surface normalized relative to soil thickness dimensionless 6 slope angle degrees angle of internal friction degrees The influence of groundwater is incorporated using a slope parallel phreatic surface so that the pore water pressure is the pressure exerted by a column of water equal in height to that of the phreatic surface above a potential slip surface This is a common but not necessary assumption for infinite slope analyses It is however reasonable in cases where a relatively permeable surficial deposit is underlain by less permeable bedrock The variable H represents a normalized phreatic surface height that has a range of 0 to 1 for non artesian conditions PISA m incorporates the effects of parameter uncertainty and variability using first order second moment FOSM approximations
8. used Arc or Surfer all three of the input map files must be of the same format and size That means all of the information in the header lines must be identical among the three input maps and maps of different sizes or geographic extent cannot be combined in a PISA m run Each value or raster in the soil and forest cover map files must correspond to an elevation value in the DEM input file Parameter File Input The fourth input file required by PISA m is a parameter file that contains information about the DEM soil unit map and forest cover unit map being used for the calculations the statistical distributions of geotechnical parameters for each soil and forest cover unit and geotechnical constants such as the unit weight of water consistent with the units being used for the geotechnical variables The illustration below is a ascreen shot of a typical PISA m parameter file opened by a text editor for example TextEdit on a Macintosh or Notepad on a Windows computer Although it makes sense to give the parameter file a par extension for example project_name par this can cause confusion when using the Windows version because Windows will hide the extension This problem does not occur on Macintosh computers Here is a parameter file for the example data set included with your copy of PISA m seismic_d probability in_format arc out_format arc dem asc soils asc trees asc results asc 7sHaneberg Geoescience 39th Avenue SW Sea
9. IS or graphics software is needed to display the results The ASCII grid output produced by PISA m is readable by many popular GIS and graphics programs including the landscape analysis program Landserf which is available for free from www landserf org and the visualization software OpenDX www opendx org Installing and Running PISA m PISA m has been tested using Macintosh OS X 10 4 and Windows XP Both versions are compiled from the same Fortran 95 source code and their usage is almost identical dione a a Rie ae cere Seattle WA 98146 aes ae aues nfo erg com www haneberg com Macintosh The Macintosh version of PISA m runs in a Unix command line environment and is controlled using the Terminal application located in the Utilities folder of the Applications folder It will be easiest to use PISA m if it is located in a directory along your specified file path for example the usr local bin directory So place the pisam file there To see what other locations are on your file path type PATH in the Terminal window and press return You can modify your path but should not try to do so unless you are an experienced Unix user consult with your computer support staff or read a Unix reference book You may want to consult a Macintosh specific reference such as Unix for Mac by Sandra Henry Stocker and Kynn Bartlett ISBN 0 7645 3730 X which will also give a good introduction to Unix file manipulation commands that you may find use
10. PISA m Map Based Probabilistic Infinite Slope Analysis Version 1 0 1 User Manual Updated March 2007 ie Enea e Gemeclion Opiens Hep fle Execute Windows Comecton Options top Soil Units Heip File Execute windows Connection Options 1 m LiDAR DEM Static Probability f Sliding 7jHaneberg Geoescience th Avenue SW Seattle WA 98146 aes ae 0846 info haneberg com www haneberg com PISA m was developed by Haneberg Geoscience 10208 39 Avenue SW Seattle WA 98146 USA www haneberg com info haneberg com Copyright 2006 2007 William C Haneberg All rights reserved Licensees are given permission to make paper copies of this manual for their own use but may not distribute copies of the manual to others without permission Licensees may also make a backup copy of the software or install it on more than one computer as long as no more than one person is using the program at any time Any other duplication of this manual or the accompanying computer program is prohibited Waiver of Liability Haneberg Geoscience does not warrant that this software is free from bugs errors or omissions the product is sold as is Haneberg Geoscience shall not under any circumstances be responsible for any bugs errors or omissions for corrections of any bugs errors or omissions discovered at any time or for providing information about any bugs errors or omissions Haneberg Geoscience does not recommend the use of PISA m for app
11. able 1 7Haneberg Geoescience th Avenue SW Seattle WA 98146 aes ca 0846 info haneberg com www haneberg com Lines 8 13 contain six geotechnical constants used in the calculations the unit weight of water gw the user specified Newmark acceleration threshold an in g the user specifed Newmark displacement dn in centimeters the Arias intensity of the earthquake for Newmark displacement calculations IA in m s the minimum slope angle minslope and the DEM elevation error standard deviation z_ err in units consistent with the DEM The minimum slope value is used to prevent the calculation of extremely high factors of safety for low slopes The equation to calculate the static factor of safety against sliding which is also used by the seismic calculations goes to infinity as the slope angle approaches zero and Fortran will return a not a number NaN result if the slope is zero In order to prevent that potential problem PISA m does not calculate factors of safety for grid points at which the average slope is less than minslope The six values on lines 8 13 may be given in any order and may be set to zero if appropriate for example an and IA may be set to zero for static calculations Although the geotechnical variables will be familiar to most geologists and engineers using PISA m the concept of elevation error standard deviation z_err may not It is a measure of the uncertainty of elevations in the DEM from which slope an
12. alue to help identify locations where a more rigorous analysis may be insightful The FOSM method used by PISA m employs a non iterative solution ideal for GIS based analyses of watersheds or similarly sized areas covered by conventional or high resolution LiDAR digital elevation models The non iterative nature is important because it means that reasonably accurate results can be obtained in a fraction of the time it would take to perform hundreds of iterations in a Monte Carlo simulation PISA m is an excellent complement to qualitative air photo or field based landslide inventories and can be used to evaluate the potential effects of logging or other activities on watershed scale slope stability to assess the potential for landslide problems along transportation or utility corridors to identify critical areas in land use planning and zoning projects and to support EA EIS analyses PISA m is a small program with a very specific job to read in lots of numbers perform some fairly complicated slope stability calculations and save the results in a form that can be used in other programs To that end it has a bare bones command line interface in order to decrease development overhead and allow the same source code to be compiled for both Macintosh and Windows and in theory any version of Unix or Linux for which a Fortran 95 compiler is available In keeping with this bare bones philosophy PISA m produces only numerical output and third party G
13. e files type in the file name and press return It s best not to use file or directory names with spaces when using Unix commands Another way to specify the file is to find it in the Finder copy its name and paste it into the Terminal application before pressing return Once you ve entered the two file names PISA m will give you updates as it reads the files performs calculations and writes the output files For very large DEMs containing millions of points writing the output file is usually the most time consuming portion of the program You can now examine the output files using the Unix cat or for large files cat more command in the Terminal window by opening them in a text editor or importing them into a graphics or GIS program Windows Using PISA m in Windows is similar to using it in the Unix terminal window on a Macintosh although the DOS command line interface is not as useful as the Unix command line You can either double click on the pisam exe icon or use the Run item under the main Windows menu If you choose the second option use Browse to select pisam exe and click to OK button or place pisam exe in the Program Files bin directory You will see a terminal window very similar to the Macintosh window illustrated above prompting you to enter the first of four file names Because pisam runs under DOS on Windows systems it is limited to file names consisting of eight characters or less plus a period followed b
14. ful Once the pisam file is placed in a directory on your path type pisam press the return key You will see a screen that looks like Figure 1 e200 Terminal pisam 86x26 Figure 1 As shown above you ll be prompted to enter the first of two file names one for the input parameter file and the other for the output log file The input parameter file will contain 7 Haneberg Geoescience 10208 39th Avenue SW Seattle WA 98146 206 935 0846 info haneberg com www haneberg com the names of other necessary input and output files The log file will contain a summary of the data and parameters used in the model run The next section describes the input file formats in detail so please read it carefully Input files that depart from the specifications will either cause a run time error or even worse be used in calculations but produce incorrect results especially if inconsistent units are used for the geotechnical variables To make things easier you can change the working directory to the directory containing the input files for your project using the Unix cd command For example if your input files are in the directory my project simulations then you would type my_project simulations You can verify that you ve changed to the correct directory using the command pwd which should return something like Users yourname my_project simulations Whether you type in the complete file path or cd to the directory containing th
15. gles are calculated Field studies have shown that the elevation error variance varies in space and is spatially correlated meaning that the value applicable to slope angle calculations will be less than DEM wide RMS errors that are sometimes supplied as GIS metadata It can be treated as a constant with a value of zero implying that the DEM elevations are error free if this assumption is justified GPS field studies have shown that in several cases the elevation error standard deviation of conventional DEMs with grid spacing on the order of 10 m for example off the shelf USGS 10 m and 30 m DEMs can have quadrangle wide elevation error variances on the order of 2 to 3 m Because the errors are spatially correlated though the more relevant value is the standard deviation among points spaced 2 As apart where A is the DEM grid spacing which is likely to be on the order of 1 m High resolution LiDAR airborne laser scanner DEMs typically have much lower elevation error standard deviations typically on the order of centimeters Users should consult the following references for more information Fisher P 1998 Improved modeling of elevation error with geostatistics Geolnformatica v 2 p 215 233 Haneberg W C in press Effects of digital elevation model errors on spatially distributed seismic slope stability calculations An example from Seattle Washington Environmental amp Engineering Geosciences Holmes K W Chadwick O A a
16. lications in which bugs errors or omissions could threaten life injury or other significant loss Moreover Haneberg Geoscience does not warrant the suitability of this software or its results for any particular application Considerable professional judgement is required of users when selecting input and interpreting results Some applications of this program may constitute the practice of geology or engineering subject to local licensing laws Under no circumstances shall Haneberg Geoscience be liable for any lost profits lost benefits or any other kind of damages Liability shall be limited to the purchase price of the software license Execution of the PISA m computer program implies your acceptance of these conditions 7sHaneberg Geoescience 39th Avenue SW Seattle WA 98146 aes ae 0846 info haneberg com www haneberg com What is PISA m PISA m is a computer program that performs probabilistic static and seismic slope stability calculations for topography obtained from digital elevation models DEMs It is based on a first order second moment FOSM formulation of the infinite slope equation used by the U S Forest Service slope stability program LISA and DLISA and therefore can include the effects of tree root strength and tree surcharge Although PISA m does not perform a complete rigorous or simplified Newmark analysis it calculates probabilistic Newmark acceleration values and compares them to a user specified critical v
17. mat respectively and tell PISA m what map formats to read and write The choices for each line are arc and surfer In the example shown above the input and output maps are all in Arc ASCII grid format Lines 4 7 contain four file names corresponding to the input DEM the soil unit map the forest cover unit map and the output map The four files must be listed in this order in order for the calculations to be performed correctly Be sure to specify a complete and valid file path if any of the files do not reside in the current working directory Value 2 Result Calculated static mean Static factor of safety mean FS sd Static factor of safety standard deviation Sps probability Static probability of sliding lognormal Prob FS lt 1 reliability Non parametric slope reliability FS 1 Srs seismic_a mean Newmark acceleration mean dy sd Newmark acceleration standard deviation Say robabilit Probability that Newmark acceleration exceeds a user p Y specified threshold Prob ay lt a Non parametric Newmark acceleration reliability reliability a Ari Sa Mean Newmark displacement Dy in cm calculated seismic_d mean Be ibd Spee using Jibson s simplified method sd Option not available s p 0 375 log cm Probability that the Newmark displacement exceeds a user specified threshold Prob Dy gt Daril SNE Non parametric Newmark displacement reliability reliability D _D V s N crit Dy probability T
18. mmetric distribution PISA m takes the customary parameters for each distribution as input and converts them to an equivalent mean and variance if the distribution is not normal Four kinds of non normal distributions are allowed uniform triangular extreme value type I and B PERT Variables following uniform distributions have an equal probability of occurrence between a minimum and a maximum value Extreme value type I distributions which are sometimes referred to as Gumbel distributions are characterized by a location parameter a and a shape parameter p Triangular distributions are characterized by a minimum value a peak value and a maximum value PERT is an acronym for Program Evaluation and Review Technique and the 6 PERT distribution is a variation of the f distribution developed to estimate the duration of complicated engineering projects such as ballistic missile development PERT are also characterized by three variables known as the minimum or optimistic estimate best estimate and maximum or pessimistic estimate but the distribution follows a smooth curve rather than a triangle and more emphasis is placed on the best estimate Lognormal distributions are not included in PISA m because in a FOSM approximation they are indistinguishable from normal distributions their skewness and kurtosis are described by the third and fourth moments about the mean PISA m uses the following conversions for non normal distributions
19. n and standard deviation normal or empirical a location and scale parameter extreme value type I distribution or minimum and maximum uniform distribution are followed by one dummy value If the distribution type is triangular or beta_pert the three numbers are the minimum peak and maximum values triangular or pessimistic most likely and optimistic values PERT phi Angle of internal friction degrees cs Soil cohesive strength pressure cr Root cohesive strength pressure q Tree surcharge pressure d Soil thickness length h Pore pressure coefficient 0 lt h lt 1 gs Saturated unit weight force volume gm Moist unit weight force volume Table 2 This is a change from version 1 0 which used the variance instead of the standard deviation 7Haneberg Geoescience 10208 39th Avenue SW Seattle WA 98146 206 935 0846 info haneberg com www haneberg com After all of the soil units are described the next line contains the word trees and another integer representing the number of forest cover units in the model The example above contains two forest cover units but they occupy different areas than the soil units see Figure 2 which was produced by importing PISA m input and output files into OpenDX Each forest cover unit is described in terms of its root strength cr and surchage q in the same way as the soil unit map variables Note that PISA m assumes that the input variables have consis
20. nd Kyriakidis P C 2000 Error in a USGS 30 meter digital elevation model and its impact on terrain modeling Journal of Hydrology v 233 p 154 173 This is a change from version 1 0 which used the variance of the elevation error 7Haneberg Geoescience SW Seattle WA 98146 aes ae neue ROGNE bar com www haneberg com Line 14 contains the word soil and an integer indicating the number of units in the soil map The example soil map provided with PISA m has two soil units Each of the soil units is described using six variables phi cs d h gs and gm listed in any order The first group of six lines corresponds to soil map unit 1 the second group to soil map unit 2 and so forth See Table 2 for an explanation of the geotechnical variables Each line consists of a variable name typed exactly as shown in the example parameter file above and Table 2 followed by a distribution type none normal empirical uniform triangular extreme or beta_pert and three numbers The word none is used for variables that are to be treated as constants rather than random variables described by a probability distribution It is to be followed by a value for that variable and then two dummy values The dummy arguments can have any value but they must be present because PISA m expects to find three numbers and will produce an error if they are not If the distribution type is normal uniform or extreme then two numbers representing either a mea
21. of sliding or 1 Prob FS lt 1 The meaning of the probability given by equation 11 depends on the input variables If one or more of the variables is specified as a constant then it can be interpreted as a conditional probability for that value For example if h 1 is specified o E Rie ae see Seattle WA 98146 aes ae aues nfo erg com www haneberg com for the pore water pressure then the result is calculated probability is conditional upon the existence of complete saturation If h is specified using an extreme value distribution derived from annual piezometric maxima then the result is an annual probability of occurrence Therefore particular attention should be paid to the nature of the input distributions See the following reference for a discussion of the physical meaning of the probabilities calculated by programs such as PISA m and LISA Hammond C Hall D Miller S and Swetik P 1992 Level I Stability Analysis LISA Documentation for Version 2 0 Ogden UT U S Department of Agriculture Forest Service Intermountain Research Station Gen Tech Rep INT 285 190 p Non Parametric Reliability Index An alternative to the probability of sliding and one which does not require an a priori assumption about the form of the output probability density function is the reliability index FS 1 Sp RI 12 in which s is the standard deviation of the factor of safety and unity is the limiting state value of
22. ofessional judgement and knowledge of soil types Values typically range from about 5 cm in sands to 15 or 20 cm in clays and sliding is predicted if the calculated Dy exceeds the threshold Please consult an appropriate engineering geology or geotechnical engineering reference for more details SHaneberg z eoescience Rie ae see Seattle WA 98146 aes ae aues nfo erg com www haneberg com
23. st be exceeded in order for slope movement to begin Movement will not occur if the acceleration as a result of seismic shaking is less than that Therefore if ay gt a y it is unlikely that seismic shaking will trigger a landslide The degree to which landsliding is unlikely is quantified by the probability and reliability index results In contrast if ay lt a then seismic shaking may trigger a landslide if the shaking is prolonged and severe enough and a more thorough rigorous Newmark analysis should be conducted The second seismic option seismic_d estimates the mean Newmark displacement using Jibson s simplified method logo Dy 1 521 log 1 1 993 logo ay 1 546 17 where Dy is the Newmark displacement in centimeters is the Arias intensity in meters per second and ay is the calculated mean Newmark critical acceleration for each grid point in the model Equation 17 is based on a regression analysis of more than 500 strong motion records for 13 different earthquakes It is statistically significant and has a goodness of fit of 7 0 83 and model standard deviation of 0 375 See Jibson et al 1998 US Geological Survey Open File Report 98 113 for details The mean value given by equation 17 and the model standard deviation are used to calculate the probability of that Dy exceeds a user specified critical or a reliability index relative to that critical value Selection of an appropriate critical Dy value requires pr
24. tent units and will perform calculations but return incorrect results if units are mixed If soil thickness is specified using meters then the pressure variables must be specified in units of Pa not kPa Also remember that metric unit weights are given in terms of N m and not kg m The only exception is that the DEM and geotechnical units may be specified using different units because the only connection between them is the slope angle which is always specified in degrees Log File Output PISA m produces a log file that echoes input information the equivalent means and variances used in calculations and other information for future reference PISA m will prompt the user for a file name but no other action is required If the file name is the same as an existing file name PISA m will overwrite the old file Sample Data Set Your copy of PISA m comes with a sample data set that you can use to examine the input file structure especially the parameter file and perform trial simulations It is based on a 501 by 501 lidar DEM of a forested watershed 7Haneberg Geoescience SW Seattle WA 98146 aay hee pane AAO Ghane baro com www haneberg com X Display Users Bill EkRiver watersheds example pisam viz net Xi Display Users bil Elk River watersheds example pisam _viz net Fle Execute Windows Connection Options Hep fle Execute Windows Connection Options Heip Forest C 1 m LiDAR DEM Static Probability f Sliding
25. the factor of safety FS 1 A value of RI 2 for example would indicate that the calculated mean factor of safety lies two standard deviations below the critical value of FS 1 Values near zero indicate that stability or instability is inferred only with little confidence Seismic Slope Stability PISA m performs rudimentary seismic slope stability calculations but does not perform a rigorous or Newmark analysis The seismic_a option performs calculations related to the Newmark critical acceleration with the mean and variance given by a FS 1 sinB 13 and a2 59 2 2 2 fs 2 OFS dp 14 2 FS 1 cos B 5 sin B sre dione a a Rie ae see Seattle WA 98146 aes ae aues nfo erg com www haneberg com where a has units of g gravitational acceleration and A has units of g As with the static factor of safety the probability that a is less than a user specified a is found by from the cumulative distribution function Prob d lt CDF dy i 15 In this case however Monte Carlo simulations conducted during the development of PISA m suggest that ay typically follows a normal not log normal distribution Haneberg 2004 Computational Geosciences with Mathematica Springer Verlag The Newmark critical acceleration reliability index is calculated using a state value as the limiting crit EN Merit 16 The Newmark acceleration ay is the acceleration that mu
26. ttle WA 98146 aes ae 0846 info haneberg com www haneberg com gw 9810 an 0 39 dn 5 IA 2 0 minslope 5 z err 0 05 soils 2 phi normal 33 0 81 0 cs normal 5500 42 0 d uniform 0 1 4 0 h extreme 0 5 0 1 0 gs normal 21500 22 0 gm normal 18000 25 0 phi uniform 32 0 81 0 cs none 10000 39 0 d uniform 0 1 4 0 h extreme 0 5 0 1 0 gs uniform 20000 26 0 gm normal 16500 32 0 trees 2 cr normal 2300 26 0 q normal 240 4 0 cr none 5000 0 0 q normal 1100 17 0 Line 1 of the parameter file contains information about the mode of the model It consists of two words The first is static seismic_a or seismic_d for static conditions seismic conditions in terms of the Newmark critical acceleration or seismic conditions in terms of the Newmark displacement using the simplified method of Jibson et al 1998 US Geological Survey Open File Report 98 113 The second entry on the first line is one of the following words mean sd probability reliability 7Haneberg Geoescience SW Seattle WA 98146 aes ae neue ROGNE bar com www haneberg com This input tells PISA m whether the output file should contain mean values standard deviations probabilities or reliability indices The meanings of each of these with respect to static and seismic slope stability calculations performed by PISA m are listed in Table 1 and described in more detail in the Theoretical Background section Lines 2 and 3 begin with in_ format and out_for
27. ust be in the same units as xllcorner and yllcorner Finally nodata_value is a number assigned to DEM grid points that have no elevation values These might arise in a DEM that does not have a rectangular shape for example a DEM of an irregularly shaped watershed PISA m also uses nodata_value when it writes its results This occurs for DEM grid points at which the slope angle is less than a user specified threshold and no calculations are performed and for the grid points around the edge of the DEM Slope angles are not calculated for points along the edge so nodata_value is used to fill space and create an output file with the same number of rows and columns as the input file The header is followed by 300 rows each consisting of 450 columns of elevation values separated by tabs or white spaces Surfer ASCII Grid Input and Output The header for a Surfer ASCII grid version of the same DEM is DSAA 450 300 1402500 1424950 150050 0 165000 32766 0 4218 1196 The first line of a Surfer ASCII grid file always consists of the identifier DSAA which simply denotes that the file is in Surfer ASCII grid format It does not identify the location or name of the DEM just its format The second line contains the numbers of rows and columns but without any identifiers such as those used in the Arc ASCII grid format The next three lines consist of the minimum and maximum x y and z values in DEMs these typically correspond to the East West
28. y a three character suffix The next section describes the input file formats in detail so please read it carefully Input files that depart from the specifications will either cause a run time error or even worse be used in calculations but produce incorrect results especially if inconsistent units are used for the geotechnical variables Rather than typing long file 7Haneberg Geoescience 39th Avenue SW Seattle WA 98146 aes ae 0846 info haneberg com www haneberg com paths you can drag files from the Desktop to the command line window and then press return Once you ve entered the two file names PISA m will give you updates as it reads the files performs calculations and writes the output files For very large DEMs containing millions of points writing the output file is usually the most time consuming portion of the program You can now examine the output files using a text editor or importing them into a graphics or GIS program Input and Output File Formats PISA m requires four input files three of which are in map form a DEM a soil unit map and a forest cover unit map The DEM consists of a grid of elevation values whereas the soil and forest cover unit maps consist of grids of integer values corresponding to the entries in the parameter file discussed further on in this manual Note that the PISA m file format is different from the original PISA format and input files for the two programs are not interchangeable
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