CRWR Online Report 97-6
Water Quality Master Planning for Austin
by
Christine Michele Dartiguenave, Ing?nieur ECLille
Graduate Research Assistant
and
David R. Maidment
Principal Investigator
December 1997
CENTER FOR RESEARCH IN WATER RESOURCES
Bureau of Engineering Research ? The University of Texas at Austin
J.J. Pickle Research Campus ? Austin, TX 78712-4497
This document is available online via World Wide Web at
http://www.ce.utexas.edu/centers/crwr/reports/online.html
iv
Acknowledgements
I would like to thank my advisor, Dr. David Maidment, for his support through this
project. I am also grateful to Dr. Francisco Olivera and Dr. Michael Barrett for their
constant assistance throughout this research.
I would like to thank the City of Austin, which funded this project, and more particularly
Ed Peacock, Pat Hartigan, Leila Gosselink and Ellen Wadworth. I am especially grateful
to Ellen for her comments and for her friendship.
I have much appreciated the help and support I received from the members of Dr.
Maidment?s GIS Research team: Kwabena Asante, Ferdinand Hellweger, Connie
Hinojos, Cindy How, Ann Quenzer, Seann Reed and Maggie Ye Ruan.
Last but not least, I would like to thank my family, who is always there for me.
December 1997
v
Abstract
Water Quality Master Planning for Austin
Christine Michele Dartiguenave, M.S.E.
The University of Texas at Austin, 1997
Supervisor: David R. Maidment
The goal of this research is the creation of a non-point source pollution water
quality model using a Geographic Information System. The area chosen for the study is
the City of Austin, which partly overlays the recharge zone of the Edwards Aquifer. A
model based on raster data that takes into account the presence of the recharge zone was
created both in ArcView and in Arc/Info for mean annual flows and pollutant loadings.
The model is able to perform the following tasks: 1) compute current pollutant loadings
for TSS, BOD, COD, TOC, DP, TP, NH
3
, TKN, NO
3
, TN, Cu, Pb and Zn, 2) compute
future loadings for the year 2040 for the same constituents, 3) model the effect of located
and regional Best Management Practices. The model was designed so that it could deal
with different sets of input parameters and locations.
vi
Table of Contents
List of Tables ................................................................................................................. x
List of Figures............................................................................................................... xi
List of Procedures........................................................................................................ xvi
Chapter 1 Introduction.................................................................................................... 1
1.1  Background .................................................................................................... 1
1.2  Methodology .................................................................................................. 4
1.3  Assumptions................................................................................................... 7
Chapter 2 Creation of a base map ................................................................................... 9
2.1 Area of study................................................................................................... 9
2.1.1 Location.............................................................................................. 9
2.1.2 Projection: Texas State Mapping System........................................... 13
2.2 USGS stations............................................................................................... 14
2.2.1 Locations.......................................................................................... 14
2.2.2 Generate the point coverage .............................................................. 17
2.2.3 Adjust the coverage........................................................................... 19
2.3 Environmental Integrity Index sites ............................................................... 27
2.3.1 Locate the stations ............................................................................ 27
2.3.2 Create a point coverage in ArcView .................................................. 30
2.4 Retrieve information at the stations ............................................................... 31
2.4.1 Retrieve the grid values..................................................................... 31
2.4.2 Characterize the stations.................................................................... 32
2.4.3 Delete the fields ................................................................................ 33
Chapter 3 GIS topography characterization................................................................... 35
3.1 Digital Elevation model (DEM)..................................................................... 35
3.1.1 30m DEM......................................................................................... 35
3.1.2 Use of a DEM................................................................................... 39
vii
Table of Contents (cont.)
3.2 DEM processing............................................................................................ 40
3.2.1 Pre-processing .................................................................................. 40
3.2.2 Merging/Projection ........................................................................... 41
3.2.3 Eliminate the no data cells................................................................. 42
3.2.4 Burn in process ................................................................................. 43
3.2.5 Burning walls.................................................................................... 47
3.2.6 Flowdirection/Flowaccumulation computation .................................. 48
3.3 Validation of the method............................................................................... 49
3.3.1 Quantitative assessment of the topographic representation................. 49
3.3.2 Qualitative assessment of the topographic representation................... 51
3.4 Creek and watershed delineation ................................................................... 53
3.4.1 Method ............................................................................................. 53
3.4.2 Define the upstream limit of a creek.................................................. 55
3.4.3 Getting rid of the dangling polygons ................................................. 56
Chapter 4 Input parameters........................................................................................... 60
4.1 Precipitation.................................................................................................. 60
4.2 Land use ....................................................................................................... 62
4.2.1 Current land use................................................................................ 62
4.2.2 Future land use.................................................................................. 67
Chapter 5 Discharge ..................................................................................................... 75
5.1 Computation method..................................................................................... 75
5.1.1 Two modes of contribution ............................................................... 75
5.1.2 Discharge produced by each cell ....................................................... 78
5.1.3 Total discharge.................................................................................. 79
5.1.4 Discharge computation...................................................................... 80
5.2 Recharge....................................................................................................... 82
5.2.1 Difference between recharge and non recharge zones ........................ 82
5.2.2 Recharge losses coefficients.............................................................. 82
viii
Table of Contents (cont.)
5.2.3 Calculating flows with recharge losses .............................................. 88
5.3 Flow calibration ............................................................................................ 89
5.3.1 Observed discharges ......................................................................... 90
5.3.2 Average discharge and probabilistic approach ................................... 91
5.3.3 Calibration method............................................................................ 96
5.4 Discharge computation................................................................................ 106
Chapter 6 Load........................................................................................................... 109
6.1 External load............................................................................................... 109
6.1.1 Event Mean Concentration.............................................................. 109
6.1.2 Load computation method............................................................... 112
6.2 Channel erosion .......................................................................................... 122
6.2.1 Model ............................................................................................. 122
6.2.2 Erosion coefficients......................................................................... 123
6.3 Construction load........................................................................................ 128
6.3.1 Zone to be developed ...................................................................... 128
6.3.2 Construction load computation........................................................ 131
Chapter 7 Best Management Practices ........................................................................ 133
7.1 Located BMPs............................................................................................. 133
7.1.1 Effects of BMPs defined by load removed....................................... 133
7.1.2 Effects of BMPs defined by efficiency ............................................ 137
7.2 Non located BMPs ...................................................................................... 144
7.2.1 BMP zones ..................................................................................... 144
7.2.2 Removal efficiencies....................................................................... 149
7.2.3 Load corrected by the BMPs ........................................................... 151
7.2.4 Effect of non-discharge BMPs on channel erosion........................... 156
Chapter 8 The ArcView Model................................................................................... 159
8.1 ArcView non-point source pollution extension ............................................ 159
8.1.1 Extension installation...................................................................... 159
ix
Table of Contents (cont.)
8.1.2 Extension description...................................................................... 161
8.1.3 Extension scripts............................................................................. 166
8.1.4 Extension creation........................................................................... 169
8.2 Flow computation ....................................................................................... 170
8.2.1 Input/Output files............................................................................ 170
8.2.2 Running Qual.Flow......................................................................... 172
8.3 Load computation ....................................................................................... 182
8.3.1 Input/Output files............................................................................ 182
8.3.2 Running Qual.Load......................................................................... 187
8.4 Best Management Practices......................................................................... 193
8.4.1 Located BMPs defined by load removed ......................................... 193
8.4.2 Located BMPs defined by efficiency............................................... 198
8.4.3 Non located BMPs defined by efficiency......................................... 205
 Chapter 9 Conclusions and Recommendations........................................................... 220
Appendix A  Data Dictionary ..................................................................................... 225
Appendix B  CDROM................................................................................................ 239
Appendix C  Avenue scripts ....................................................................................... 247
Glossary..................................................................................................................... 298
Bibliography .............................................................................................................. 299
Vita ......................................................................................................................... 300
x
List of Tables
Table 2.1: Watersheds within the DEM study area..................................................... 9
Table 2.2: Watersheds under study.......................................................................... 12
Table 2.3: Study projection file .............................................................................. 14
Table 2.4: USGS stations ........................................................................................ 15
Table 2.5: USGS stations coordinates in decimal degrees (stat.dat).......................... 17
Table 2.6: Conversion from geographic to state plane coordinates (sta_prj) ............. 18
Table 2.7: Scanned map projection file (stamap_prj) ............................................... 28
Table 3.1: Watersheds areas comparison for Waller Creek ...................................... 36
Table 4.1: Land use categories for the study............................................................ 62
Table 4.2: Urban watersheds ................................................................................... 63
Table 4.3 Land use-Impervious cover relationships................................................ 64
Table 4.4: Extra City of Austin land uses categories................................................ 64
Table 4.5: USG/City of Austin land uses classifications .......................................... 65
Table 5.1: Base flow, direct runoff and total flow at the USGS stations based on
impervious cover/runoff coefficient relationships.................................... 81
Table 5.2: Recharge coefficients ............................................................................. 87
Table 5.3: Mean and standard deviation of log
10
Q ................................................... 95
Table 5.4: Observed and predicted flows at the USGS stations (before flow
correction).............................................................................................. 98
Table 5.5 Correction coefficients for gauged watersheds ...................................... 100
Table 5.6: Correction coefficient for downstream portions of USGS watersheds.... 104
Table 5.7: USGS number/Correction coefficient relationship................................. 105
Table 6.1: Impervious cover/EMC relationship ..................................................... 110
Table 6.2: TOC erosion coefficients...................................................................... 124
Table 6.3: TN erosion coefficients......................................................................... 125
Table 6.4: TP erosion coefficients ......................................................................... 126
Table 6.5: TSS erosion coefficients....................................................................... 127
Table 6.6: Erosion relationships ............................................................................ 128
Table 6.7: Comparaison between current loads and construction loads for TSS ..... 132
Table 7.1: Percentage of BMPs per BMP zones..................................................... 145
Table 7.2: Capture volume/Impervious Cover relationships................................... 150
Table 7.3: SED1, SAND2, SAND3 average event removal efficiencies ................. 150
Table 8.1: Description of Scripts........................................................................... 164
xi
List of Figures
Figure 1.1: Study area ................................................................................................ 3
Figure 1.2: Location of study sites in drainage area..................................................... 4
Figure 1.3: Non-point source pollution model............................................................. 5
Figure 1.4: Digital Elevation Model ........................................................................... 6
Figure 2.1: Austin watersheds .................................................................................. 10
Figure 2.2: Edwards Aquifer in Austin ..................................................................... 11
Figure 2.3: Study Watersheds................................................................................... 12
Figure 2.4: Station location ...................................................................................... 20
Figure 2.5: Choose the grids (Qual.Pick) .................................................................. 21
Figure 2.6: Choose a point coverage (Qual.Pick) ...................................................... 21
Figure 2.7: Overwrite an existing field (Qual.Pick)................................................... 22
Figure 2.8: Create a new point coverage (Qual.Addpoint)......................................... 23
Figure 2.9: Choose the coverage to modify (Qual.Addpoint)..................................... 23
Figure 2.10: Snap option (Qual.Addpoint).................................................................. 24
Figure 2.11: Choose a line coverage for the snap option (Qual.Addpoint) ................... 24
Figure 2.12: Successful snap (Qual.Addpoint)............................................................ 25
Figure 2.13: Edit the fields (Qual.Addpoint)............................................................... 25
Figure 2.14: Gage location before and after correction................................................ 26
Figure 2.15: Cells junction ......................................................................................... 27
Figure 2.16: 1:24,000 USGS scanned map (detail)...................................................... 29
Figure 2.17: Double line roads ................................................................................... 30
Figure 2.18: Name and path of the new coverage (Qual.Addpoint) ............................. 31
Figure 2.19: Choose a destination table (Qual.Join) .................................................... 33
Figure 2.20: Choose a table to edit (Qual.Delete)........................................................ 34
Figure 2.21: Choose the fields to delete (Qual.Delete) ................................................ 34
Figure 3.1: USGS 1:24,000 quadrant sheets.............................................................. 35
Figure 3.2: Delineated Watershed vs. Digitized Watershed (Waller Creek) ............... 37
Figure 3.3: Comparison between 30m and 90m DEMs ............................................. 38
Figure 3.4: Flowdirection and Flowaccumulation grids............................................. 40
Figure 3.5: Burn in process....................................................................................... 44
Figure 3.6: Comparison between the USGS stations drainage areas obtained from
the USGS and delineated with the DEMs................................................ 51
Figure 3.7: Comparison between digitized and delineated watersheds....................... 52
Figure 3.8: Difference between the commands streamline and gridline ..................... 53
Figure 3.9: Stream network for different thresholds (100 to 10,000 cells).................. 54
Figure 3.10: Creeks draining at least 64 acres in Bull Creek Watershed ...................... 56
Figure 3.11: Dangling polygons ................................................................................. 58
Figure 4.1: Model input and output........................................................................... 60
Figure 4.2: Annual precipitation at the Austin airport ............................................... 61
Figure 4.3: Urban and Non urban watersheds ........................................................... 63
Figure 4.4: Current land use ..................................................................................... 66
Figure 4.5: Current impervious cover ....................................................................... 67
Figure 4.6: Impervious cover increase in the traffic serial zones................................ 68
xii
List of Figures (cont.)
Figure 4.7: Future impervious cover defined by the traffic serial zones ..................... 70
Figure 4.8: Future impervious cover......................................................................... 73
Figure 5.1: The two modes of contribution of precipitation....................................... 76
Figure 5.2: Relationship between direct runoff coefficient and impervious cover ...... 77
Figure 5.3: Relationship between base flow coefficient and impervious cover........... 77
Figure 5.4: Direct runoff produced by each cell ........................................................ 79
Figure 5.5: Example of watersheds in the recharge zone ........................................... 83
Figure 5.6: Flow length in the recharge zone............................................................. 85
Figure 5.7: Flow calibration ..................................................................................... 90
Figure 5.8: Daily mean discharge at Barton Creek at Loop 360................................. 92
Figure 5.9: Lognormal distribution for Barton Creek at Loop 360............................. 93
Figure 5.10: Lognormal distribution for Bear Creek at FM 1826................................. 93
Figure 5.11: Lognormal distribution for Bull Creek at Loop 360................................. 94
Figure 5.12: Lognormal distribution for Onion Creek at US 183................................. 94
Figure 5.13 Calibration zones.................................................................................... 97
Figure 5.14 Relationship between flow correction and impervious cover ................. 101
Figure 5.15: Correction coefficients.......................................................................... 103
Figure 6.1 Load produced by each cell (e.g. direct runoff) ..................................... 113
Figure 6.2: Comparison between measured and predicted concentrations at the
USGS stations ...................................................................................... 119
Figure 6.3 Comparison between measured and predicted loads at the USGS
stations................................................................................................. 121
Figure 6.4: TOC erosion vs. impervious cover........................................................ 124
Figure 6.5: TN erosion vs. impervious cover .......................................................... 125
Figure 6.6: TP erosion vs. impervious cover........................................................... 126
Figure 6.7: TSS erosion vs. impervious cover......................................................... 127
Figure 6.8: Error in conversion from vector to grid................................................. 129
Figure 6.9: Assumption for percentage of development .......................................... 131
Figure 7.1: Located Best Management Practices..................................................... 134
Figure 7.2: Computation for located BMPs defined by load removed...................... 135
Figure 7.3: Removal load grid for located BMPs defined by efficiency................... 138
Figure 7.4: Corrected load...................................................................................... 138
Figure 7.5: Total BMPs removal............................................................................. 139
Figure 7.6: BMP classification ............................................................................... 141
Figure 7.7: Classification for non-nested watersheds............................................... 142
Figure 7.8: City jurisdiction.................................................................................... 147
Figure 7.9: Future conditions BMP zones............................................................... 148
Figure 7.10: Effective impervious cover................................................................... 157
Figure 8.1: Command to install the extension ......................................................... 160
Figure 8.2: Extensions window............................................................................... 161
Figure 8.3: View based buttons, tool and menus ..................................................... 162
Figure 8.4: Script customization window................................................................ 166
Figure 8.5: Load an extension script ....................................................................... 167
xiii
List of Figures (cont.)
Figure 8.6: Script Manager..................................................................................... 168
Figure 8.7: An Extension Script.............................................................................. 168
Figure 8.8: Input files (Qual.Flow) ......................................................................... 170
Figure 8.9: Output files (Qual.Flow)....................................................................... 172
Figure 8.10: Analysis extent and cell size (Qual.Flow) ............................................. 173
Figure 8.11: Working directory (Qual.Flow)............................................................. 174
Figure 8.12: Choose an impervious cover theme (Qual.Flow)................................... 174
Figure 8.13: Choose an impervious cover field (Qual.Flow) ..................................... 175
Figure 8.14 Choose a flowdirection grid (Qual.Flow) .............................................. 175
Figure 8.15: Choose a correction grid (Qual.Flow) ................................................... 176
Figure 8.16: Recharge zone (Qual.Flow) .................................................................. 176
Figure 8.17: Choose a cell recharge grid (Qual.Flow)............................................... 176
Figure 8.18 Choose a recharge grid (Qual.Flow)...................................................... 177
Figure 8.19: Name of the output grid (Qual.Flow) .................................................... 177
Figure 8.20: Recompute the runoff coefficients (Qual.Flow)..................................... 178
Figure 8.21: Overwrite an existing field (Qual.Flow)................................................ 178
Figure 8.22: Renaming a runoff coefficient field (Qual.Flow)................................... 178
Figure 8.23: Default impervious cover/direct runoff coefficient relationship
(Qual.Flow).......................................................................................... 179
Figure 8.24: Modifying the impervious cover/diect runoff coefficient relatioship
(Qual.Flow).......................................................................................... 179
Figure 8.25: Default impervious cover/base flow runoff coefficients relationship
(Qual.Flow).......................................................................................... 180
Figure 8.26: Modifying the impervious cover/base flow coefficients relationship
(Qual.Flow).......................................................................................... 180
Figure 8.27: Impervious cover attribute table (Qual.Flow)........................................ 181
Figure 8.28: Error message (Qual.Flow)................................................................... 181
Figure 8.29: Input themes (Qual.Load)..................................................................... 183
Figure 8.30: Inputs and outputs (Qual.Load)............................................................. 184
Figure 8.31: Add tables (Qual.Load) ........................................................................ 185
Figure 8.32: Direct runoff EMCs table (Qual.Load).................................................. 185
Figure 8.33: Base flow EMC table (Qual.Load)........................................................ 186
Figure 8.34: Choose a direct runoff EMCs table (Qual.Load).................................... 187
Figure 8.35: Choose a base flow EMCs table (Qual.Load)........................................ 187
Figure 8.36: Choose the constituent(s) to model (Qual.Load).................................... 188
Figure 8.37: Name the load grid (Qual.Load) ........................................................... 188
Figure 8.38: Choose an impervious cover theme (Qual.Load)................................... 189
Figure 8.39: Choose a flowdirection grid (Qual.Load) .............................................. 189
Figure 8.40: Choose a water land use theme (Qual.Load) ......................................... 190
Figure 8.41: Choose a corrected runoff cell grid (Qual.Load).................................... 190
Figure 8.42: Choose a corrected base flow cell grid (Qual.Load) .............................. 190
Figure 8.43: Recharge zone (Qual.Load) .................................................................. 191
Figure 8.44: Choose a cell recharge grid (Qual.Load) ............................................... 191
xiv
List of Figures (cont.)
Figure 8.45: Choose a grid with the flow without recharge (Qual.Load).................... 192
Figure 8.46: Input files (Qual.BMPload) .................................................................. 193
Figure 8.47: Choose the working directory (Qual.BMPload)..................................... 194
Figure 8.48: Name  of the removed load grid (Qual.Load)........................................ 194
Figure 8.49: Choose a flowdirection grid.................................................................. 195
Figure 8.50: Choose a BMP point coverage (Qual.BMPload) ................................... 195
Figure 8.51: BMPs point coverage attributes table.................................................... 195
Figure 8.52: Choose a removed load field (Qual.BMPload) ...................................... 196
Figure 8.53: Final Message to user (Qual.BMPload)................................................. 196
Figure 8.54: Input and output themes (Qual.BMPload)............................................. 197
Figure 8.55: Input files (Qual.BMPeff)..................................................................... 199
Figure 8.56: Choose the working directory (Qual.BMPeff)....................................... 200
Figure 8.57: Name of the output grid (Qual.BMPeff)................................................ 200
Figure 8.58: Choose a flow direction grid (Qual.BMPeff)......................................... 200
Figure 8.59: Choose a flowaccumulation grid (Qual.BMPeff)................................... 201
Figure 8.60: Choose a BMP point coverage (Qual.BMPeff)...................................... 201
Figure 8.61: BMP point coverage attribute table (Qual.BMPeff)............................... 201
Figure 8.62: Choose a BMP efficiency field (Qual.BMPeff) ..................................... 202
Figure 8.63: Correct the efficiency field (Qual.BMPeff) ........................................... 202
Figure 8.64: Choose an observed drainage area (Qual.BMPeff) ................................ 203
Figure 8.65: Choose an initial load grid (Qual.BMPeff)............................................ 203
Figure 8.66: Choose a watershed zones grid (Qual.BMPeff) ..................................... 203
Figure 8.67: Final message to user (Qual.BMPeff) ................................................... 204
Figure 8.68: Input and output files (Qual.BMPeff).................................................... 204
Figure 8.69: Input tables (Qual.BMPfut) .................................................................. 205
Figure 8.70: Inputs themes (Qual.BMPfut) ............................................................... 206
Figure 8.71: Inputs and outputs (Qual.BMPfut) ........................................................ 208
Figure 8.72: Average Capture Volume table (Qual.BMPfut)..................................... 209
Figure 8.73: BMPs zones table (Qual.BMPfut)......................................................... 209
Figure 8.74: Efficiency table (Qual.BMPfut) ............................................................ 211
Figure 8.75: Choose a working directory (Qual.BMPfut).......................................... 212
Figure 8.76: Consider a recharge zone (Qual.BMPfut).............................................. 212
Figure 8.77: Choose an average capture volume table (Qual.BMPfut)....................... 212
Figure 8.78: Choose a BMP zones table (Qual.BMPfut) ........................................... 213
Figure 8.79: Choose an efficiency table (Qual.BMPfut)............................................ 213
Figure 8.80: Choose a direct runoff EMC table (Qual.BMPfut)................................. 213
Figure 8.81: Choose the constituent(s) to model (Qual.BMPfut) ............................... 214
Figure 8.82: Name the output load grid for BOD (Qual.BMPfut).............................. 215
Figure 8.83: Choose an initial load grid for BOD (Qual.BMPfut) ............................. 215
Figure 8.84: Choose an impervious cover theme (Qual.BMPfut)............................... 216
Figure 8.85: Choose a flow direction grid (Qual.BMPfut)......................................... 216
Figure 8.86: Choose a BMP zones grid (Qual.BMPfut) ............................................ 216
Figure 8.87: Choose a corrected cell runoff grid (Qual.BMPfut)............................... 217
xv
List of Figures (cont.)
Figure 8.88: Choose a buildup grid (Qual.BMPfut)................................................... 217
Figure 8.89: Choose a water land use theme (Qual.BMPfut)..................................... 217
Figure 8.90: Choose a predicted flow grid (Qual.BMPfut)........................................ 218
Figure 8.91: Choose a total flow grid without recharge (Qual.BMPfut)..................... 218
Figure 8.92: Choose a cell recharge grid (Qual.BMPfut)........................................... 218
Figure 8.93: Final message to user (Qual.BMPfut) ................................................... 219
xvi
List of Procedures
Procedure 2.1: Create a point coverage in state plane coordinates (ptcov.aml).......... 18
Procedure 5.1: Discharge computation..................................................................... 80
Procedure 5.2: Discharge computation (with flow correction) ................................ 108
Procedure 6.1: Load computation .......................................................................... 115
Procedure 7.1: Flow corrected with non-discharge BMPs ...................................... 153
Procedure 7.2: BMPs corrected load ...................................................................... 155
  1
Chapter 1: Introduction
1.1 BACKGROUND
 Non-point source pollution is a leading cause of water quality problems. For a
long time it was considered negligible in comparison with point-source pollution for
which extensive legislation has been developed. The importance of non-point source
pollution in water quality issues was eventually acknowledged in the 1987 Amendment
to the Clean Water Act, which created the section 319 Non-Point Source Management
Program. The Environmental Protection Agency defines non-point source pollution as
water pollution being caused by rainfall or snowmelt moving over and through the
ground. The runoff carries natural and human-made pollutants deposited on the land
surface to receiving waters.
 Beginning in the early 1970?s, the City of Austin has implemented a storm
runoff-monitoring program. The data gathered over many years of operation since then
constitute an important and unique source of information on storm water quality in the
City. The City has also required the installation of Best Management Practices (BMPs),
such as ponds or sand filters, to reduce pollutant loading.
 Because the quantity of pollutants deposited is directly related to the level of
development, the growth of Austin will increase the impact of non-point source pollution
on urban creeks. To find solutions to the non-point source pollution problem, the City
desires to determine the actual and projected non-point source loadings at a set of eighty
Environmental Integrity Index sites. These sites are locations on streams which are
  2
periodically sampled and assessed using an Environmental Integrity Index comprised of
physical, chemical and biological measures of environmental quality (City of Austin
Drainage Utility Department, 1997).
 Austin?s storm water monitoring program does not provide information on
pollution loading for the entire City. The research presented here includes extrapolating
observed non-point source loading at monitoring sites to the eighty index sites and
calculations for both current and future conditions, where future conditions correspond to
the land use predicted for the year 2040. Current (1990) land use conditions estimated by
the City were used then assumptions were developed for various urbanization scenarios
for the next 50 years to arrive at year 2040 conditions.
 Figure 1.1 defines the location of the study area in Texas and Figure 1.2 shows
the location of the sample sites used in this study, which are the United States Geological
Survey (USGS) stations, and the Environmental Integrity Index (EII) sites. The study
region in Figure 1.2 is defined by the watersheds under study in the project and is
described in more detail in Chapter 2.
  3
 
Figure 1.1: Study area
 
 
  4
Figure 1.2: Location of study sites in drainage area
1.2 METHODOLOGY
 Previous studies conducted at the Center for Research in Water Resources have
shown GIS to be a valuable tool in the analysis of non-point source pollution problems.
Pawel Mizgalewicz modeled agrochemical transport in the Iowa-Cedar basin
(Mizgalewicz and Maidment, 1996) and Bill Saunders did an assessment of non-point
source pollution in the San Antonio-Nueces basin (Saunders and Maidment, 1996). Both
  5
studies used Geographic Information Systems (GIS) to characterize the land surface (land
use, impervious cover?). GIS is a computer system capable of storing and using data
describing locations at the surface of the earth. Information can be associated with an
object on a map and spatial operations can be conducted on that object. Operations such
as union, intersection or selection according to specific criteria can be implemented. The
GIS software programs used in these projects are Arc/Info and ArcView, developed by
the Environmental Systems Research Institute (ESRI).
 The input parameters necessary to determine non-point source pollution loading
include precipitation and land use. Relationships derived from the observed data are used
to link land use to impervious cover, and impervious cover to runoff coefficients and
Event Mean Concentrations (EMCs). Figure 1.3 illustrates this concept.
 
 
 
 
 
 
 
Figure 1.3: Non-point source pollution model
 GIS converts a vector representation (coverage) of the impervious cover for a
given area to a raster representation. By applying the necessary relationships, a runoff
 
 
         MODEL
 INPUT  OUTPUT
 Precipitation
 Land use
 Discharge
 Expected Mean
   Concentration
 Load
  6
coefficient grid and an EMC grid can be derived. The load produced by each cell can
then be determined by multiplying these grids with a precipitation grid:
 load = runoff coefficient * EMC * precipitation volume
 
 However, the path followed by the water through the landscape is needed to
determine the total loading contribution at any cell. The water flows in the direction of
steepest descent, which is determined by the topography of the area. A Digital Elevation
Model (DEM), which consists of a sampled array of elevations at regularly spaced
intervals (Figure 1.4), is used to determine the path of the water as described in more
detail in Chapter 3.
 
 
 
 
Figure 1.4: Digital Elevation Model
 There are three main differences between this and the two previous CRWR
studies cited earlier. The first is the size of the study area. The fact that the Austin area is
considerably smaller means that a smaller cell size for the grid was needed to get a good
representation of the topography. This greater resolution was possible because of the
availability of topographic data with a 30-meter cell size. The second difference is the
inclusion of base flow. It was assumed in the Austin study that the path of the base flow
 45  44 38  45
 34 40  50  60
 58  31  30  53
 50  45  32  22
 Average
elevation
30 m
  7
was identical to the path of the direct runoff but that they have different pollutant
concentrations. The third difference is that this study assesses the effects of Best
Management Practices on loadings.
1.3 ASSUMPTIONS
The general methodology presented above implies a few assumptions and choices,
concerning the time scale, the surface representation and the processes affecting the fate
of a constituent.
? Time scale
 All calculations are done on a mean annual basis. Non-point source pollutants
are carried by storm water runoff. Since runoff coefficients are directly related to land
use and since EMC values are either related to land use or are constant, the pollutant load
is directly proportional to the amount of rainfall. In the Austin area, precipitation varies
widely from year to year. Hence the average annual loading value computed over several
years indicates the expected values of the annual loadings which occur but does measure
the variability of that loading. The objective of the study is not to define a very accurate
value for the loading but to rank the different watersheds to determine the areas with
greater problems. Moreover, the advantage of the annual scale is that the time lag
between rainfall and flow does not have to be considered. The analysis is spatially
intensive but time averaged.
 Assuming that the parameters used are not time dependent (i.e. the EMCs are
constant), monthly loading values can be generated by weighting the total load by the
  8
percentage of rainfall for each month. Further studies are being conducted to test this
assumption.
 
? Non-point source versus point source discharge
 The model assumes that the storm water follows the natural topography to reach
the receiving water. However, in reality, the water can be captured at an inlet and can
discharge through a storm drain. Storm sewers can modify the location where the
discharge and water quality impacts occur, but the total loading in the creek remains the
same if the drains discharge to the same watershed. A major problem in modeling occurs
where the sewers collect the water from one watershed and discharge to another. As no
detailed description of the storm sewers system exists for Austin, they have not been
considered in this study.
 
? Conservative constituents
 All the constituents are considered to be conservative: there are no losses due to
chemical reactions or biochemical degradations (true for total dissolved solids (TSS) and
dissolved metals). The short travel time to the Environmental Integrity Index sites
justifies ignoring decay.
9
Chapter 2: Creation of a base map
 This model requires a spatial representation in a Geographic Information System
of the study area. The first step in constructing this representation consists in locating the
area of interest and representing it in the GIS. It is then essential to correctly locate the
points representing the monitoring stations and the EII sites.
2.1 AREA OF STUDY
2.1.1 Location
 Austin is located in south central Texas at approximately 98?W longitude and
30?N latitude (Figure 1.1). The study area is the drainage area of the Colorado River that
ranges from the outlet of Lake Travis at Mansfield Dam to the junction of Wilbarger
Creek with the Colorado River, comprising approximately 2,300 km
2
 and forty five
watersheds (Table 2.1 and Figure 2.1).
 Table 2.1: Watersheds within the DEM study area
 Barton  Country Club  Harris Branch  Onion  Waller
 Bear  Decker  Huck's Slough  Rinard  Walnut
 Bee  Dry  Johnson  Shoal  West Bouldin
 Blunn  Dry North  Lake Austin  Slaughter  West Bull
 Boggy  Eanes  Little Barton  South Boggy  Williamson
 Bull  East Bouldin  Little Bear  South Fork  
 Buttermilk  Elm  Little Bee  Tannehill  
 Carson  Fort Branch  Little Walnut  Taylor Slough No  
 Colorado  Gilleland  Marble  Taylor Slough So  
 Cottonmouth  Harper's
Branch
 North Fork  Town Lake  
 
10
 
Figure 2.1: Austin watersheds
  This area covers part of Travis County, where Austin is located, as well as part
of Bastrop, Hays and Blanco counties (Figure 1.1). The county boundary between Travis
and Williamson counties coincides with the boundary of the drainage area.
 It is also important to note the location of the recharge and contributing zone of
the Edwards Aquifer (Figure 2.2). There is a difference between the northern recharge
zone (north of the Colorado River) and the southern recharge zone (south of the Colorado
River). While extensive studies have been conducted in the southern recharge zone, due
to the presence of Barton Springs, little has been done on the northern recharge zone.
11
Hence this study will only estimate the effect of the southern recharge where more
stringent rules have been established.
 
 
Figure 2.2: Edwards Aquifer in Austin
 The objective of the City of Austin is to estimate pollutant loads in 18
watersheds (including 2 subwatersheds) within the study area. These watersheds, shown
in Figure 2.3, are (Table 2.2):
 
 
 
12
 Table 2.2: Watersheds under study
 Barton  Country Club  Little Barton  Waller
 Blunn  East Bouldin  Little Walnut  Walnut
 Boggy  Fort Branch  Shoal  West Bouldin
 Bull  Harper?s Branch  Tannehill  West Bull
 Buttermilk  Johnson  Town Lake  Williamson
 
 
 
 
Figure 2.3: Study Watersheds
 Two subwatersheds drain to watersheds in the study area and are considered as
well. The load and discharge from these watersheds must be taken into account in the
total load.
13
 These two subwatersheds are:
?  West Bull, included in Bull
?  Little Barton, included in Barton
During the study, Eanes watershed was added to the list of watersheds. Since the
computations have been conducted for the whole area defined in Figure 2.1, adding this
watershed did not required any additional study.
 The size of the region does not affect the methodology, so it is convenient to
define the whole area as a watershed draining toward the Colorado River. This watershed
was delimited in Arc/Info and contains approximately 2.5 million 30-meter cells: its
drainage area is approximately 2,300 km
2
.
2.1.2 Projection: Texas State Mapping System
 For a small scale study such as this, the projection chosen system is the State
Plane Mapping System because it is the standard map projection for the City of Austin.
In the United States, the State Plane System was developed in the 1930s. It was based on
the North American Datum 1927 (NAD27) whose coordinates are based on the foot as
the length measure. It was developed in order to provide local reference systems that
were tied to a national datum. Small States use a single State Plane zone while larger
states such as Texas are divided into several zones. Different projections are used
depending on the extent of the States. Lambert Conformal Conic projections are used for
rectangular zones with a larger east-west than north-south extent. Transverse Mercator
projections are used to define zones with a larger north-south extent.
14
 While the NAD-27 State Plane System has been superseded by the NAD-83
System (based on the meter), maps in NAD-27 coordinates are still in use. At the
beginning of the study the coverages provided by the City of Austin were defined with
NAD27, so this datum was chosen for the study. Table 2.3 describes the projection file
used. There are five State Plane zones in Texas. The zone 5376, covering Central Texas,
is used in this study
 Table 2.3: Study projection file
 projection state
 units feet
 zone 5376
 datum NAD27
 parameters
 end
 
 During the course of the study, the City of Austin chose to switch to NAD83. As
it would have meant redefining almost everything accomplished up to that point, the
datum NAD27 was retained for the study. At some point, all the data should be
converted to the newer projection. However, the results described in this document will
remain valid.
2.2 USGS STATIONS
2.2.1 Locations
 The locations of the USGS stations located in the study area (32 stations, Table
2.4) were obtained from the USGS web site related to the Water Data for Texas
(http://txwww.cr.usgs.gov/cgi-bin/txnwis). Their geographic coordinates are given in
degrees, minutes and seconds.
15
 Table 2.4: USGS stations
 USGS #  Name  Latitude  Longitude  Period of record  of daily-mean discharge
 8154510  Colorado River below Mansfield
Dam
 30? 23' 30"  97? 54' 28"  10/01/1974-09/30/1990
 8154700  Bull Creek at Loop 360  30? 22' 19"  97? 47' 04"  07/18/1978-active
 8154900  Lake Austin  30? 18' 53"  97? 47' 10"  Not available
 8155200  Barton Creek at SH 71 Near Oak
Hill
 30? 17' 46"  97? 55' 31"  02/07/1978-10/15/1982 and 01/01/1989-active
 8155240  Barton Creek at Lost Creek Blvd  30? 16' 28"  97? 50' 39"  12/28/1988-active
 8155260  Barton Creek near Camp Craft Road  30? 16' 12"  97? 49' 43"  09/01/1982-10/11/1988
 8155300  Barton Creek at Loop 360  30? 14' 40"  97? 48' 07"  02/01/1977-active
 8155550  West Bouldin Creek at Riverside
Drive
 30? 15' 49"  97? 45' 17"  04/21/1985-04/22/1985, 06/05/1985-06/07/1985
 8156700  Shoal Creek at NW. Park  30? 20' 50"  97? 44' 41"  03/28/1975-09/30/1984
 8156800  Shoal Creek at West 12
th
 Street  30? 16' 35"  97? 45' 00"  01/08/1983-07/27/1983 and 09/07/1983-active
 8157000  Waller Creek at 38
th
 Street  30? 17' 49"  97? 43' 36"  04/01/1955-10/23/1980
 8157500  Waller Creek at 23
rd
 Street  30? 17' 08"  97? 44' 01"  01/01/1955-10/23/1980
 8158000  Colorado River at Austin  30? 14' 40"  97? 41' 39"  03/01/1898-active station
 8158050  Boggy Creek at US Highway 183  30? 15' 47"  97? 40' 20"  03/02/1976-05/25/1976, 01/25/1977-03/09/1977,
06/16/1977-09/30/1986
 8158100  Walnut Creek at FM 1325  30? 24' 35"  97? 42' 41"  10/19/1984-10/23/1984, 05/13/1985-05/15/1985,
10/18/1985-10/20/1985, 09/05/1986-09/07/1986
 8158200  Walnut Creek at Dessau Road  30? 22' 30"  97? 39' 37"  05/13/1985-05/15/1985, 02/03/1986-02/04/1986,
05/16/1986-05/18/1986
 8158300  Ferguson Branch at Springdale Road  30? 19' 53"  97? 39' 12"  Not available
 8158380  Little Walnut Creek at Georgian
Drive
 30? 21' 15"  97? 41' 52"  02/21/1985-02/24/1985, 05/12/1985-05/13/1985,
10/18/185-10/20/1985, 04/29/1986-05/02/1986
 8158600  Walnut Creek at Webberville Road  30? 16' 59"  97? 39' 17"  05/27/1966-active
 8158820  Bear Creek at FM Rd 1626 near
Manchaca
 30? 08' 25"  97? 50' 50"  Not available
 8158840  Slaughter Creek at FM Rd 1826  30? 12' 32"  97? 54' 11"  01/16/1978-active
 8158880  Boggy Creek at Circle S Road  30? 10' 50"  97? 46' 55"  06/05/1985-06/06/1985, 10/14/1985-10/15/1985,
05/15/1986-05/15/1986
16
 
 Table 2.4 (continued): USGS stations
 USGS #  Name  Latitude  Longitude  Period of record  of daily-mean discharge
 8158920  Williamson Creek at Oak Hill  30? 14' 06"  97? 51' 36"  01/10/1978-03/08/1993
 
 8158922  Williamson Creek at Brush Country
Blvd
 30? 13' 34"  97? 50' 28"  03/11/1993-active
 8158927  Williamson Creek at Brush Country
Road
 30? 13' 36"  97? 50' 28"  10/01/1984-09/30/1985
 8158930  Williamson Creek at Manchaca
Road
 30? 13' 16"  97? 47' 36"  10/01/1984-09/30/1985
 8158970  Williamson Creek at Jimmy Clay
Road
 30? 11' 21"  97? 43' 56"  09/11/1975-09/30/1986
 8159000  Onion Creek at US Highway 183  30? 10' 40"  97? 41' 18"  06/01/1924-02/28/1930, 03/23/1976-active
 8158700  Onion Creek near Driftwood  30? 04' 59"  98? 00' 29"  07/01/1979-active
 8158800  Onion Creek at Buda  30? 05' 09"  97? 50' 52"  07/01/1979-09/30/1983 and 01/01/1992-active
 8158810  Bear Creek below FM Rd 1826 near
Driftwood
 30? 09' 19"  97? 56' 23"  07/07/1979-active
 8158825  Little Bear Creek at FM Road 1626
near Manchaca
 30? 07' 31"  97? 51' 43"  Not available
17
 
 To be used in the GIS system, these data were first converted to decimal degrees
according to the equation:
 
 The coordinates are stored in a text file (stat.dat) shown in Table 2.5, which is
used to build the point coverage in Arc/Info.
 Table 2.5: USGS stations coordinates in decimal degrees (stat.dat)
 1 ?98.0806 30.4208
 2 ?97.9078 30.3917
 3 ?97.7844 30.3719
 4 ?97.7861 30.3147
 5 ?97.9253 30.2961
 ?
 end
2.2.2 Generate the point coverage
? Step by step
 The point coverage was built in Arc/Info from the data in a text file (e.g. stat.dat)
 Arc: generate stations
 Generate: input stat.dat
 Generate: points
 Generate: quit
 Arc: build stations point
 Arc: addxy stations
 
 The result is a point coverage of the stations in geographic coordinates, which is
then converted to the State Plane projection system used in the study. The input and
3600
Seconds
 +
60
Minutes
 + Degrees = (DD) Degrees Decimal
18
output parameters of the projection from geographic to state plane are written in a text
file (sta_prj) used in the projection (Table 2.6).
 Table 2.6: Conversion from geographic to state plane coordinates (sta_prj)
 Input
 Projection geographic
 Datum NAD27
 Units dd
 Parameters
 Output
 Projection state plane
 Zone 5376
 Datum NAD27
 Units feet
 Parameters
 End
 
 The coverage stations in geographic coordinates can now be converted into the
coverage station in state plane coordinates.
 Arc: project cover stations station sta_prj
? Using Arc Macro Language
 Arc Macro Language (AML) is the programming language of Arc/Info. AML
enables one to write a program which will automate many tasks. To create a point
coverage, an AML called ptcov.aml (Procedure 2.1) was created in a text editor.
 Procedure 2.1: Create a point coverage in state plane coordinates (ptcov.aml)
 Generate stat
 Input [response?name and path of the input file?]
 Points
 Quit
 Build stat points
 Addxy stat
 Project cover stat [response?name and path of the coverage?] sta_prj
 &return
 This program is run in Arc by using the AML command &run:
19
 Arc: &run ptcov
 The program will prompt for the name and path of the input file and the new point
coverage.
2.2.3 Adjust the coverage
 The USGS stations are used to determine the actual flow in the creeks; therefore,
it is important that their gage locations are accurately located in the stream network grid
representing the delineated creeks (section 3.4). However, this is often not the case and
so corrections have to be made with either Arc/Info (ArcTools) or ArcView.
? Adjustment of gage locations with Arctools
 Arview3 enables one to check if a station is located on a creek by a point by
point verification, but it can not be used to modify the position of the stations. Only
Arc/Info allows an adjustment of the data by making corrections in the associated grid
using Arctools. The coverage of the stations first must be converted to a grid, whose
points will be compared with a stream network grid.
 Arc: grid
 Grid: station_gr = pointgrid (station)
 
 ArcView is then used as an interface to display these grids to check if the
stations are located in the creeks. If it is not true, then the grid must be modified in order
for the stations to be at the ?right? place. Once the grid with the stations has been
manually corrected, it is reconverted into a point coverage.
 Grid: station_sta = gridpoint (station_gr)
 
20
 However, the Arctools display environment is not very user friendly, and it is
quite time-consuming to swing back and forth between ArcView, and Arctools.
? Adjustment of gage locations with ArcView
 The process described above is time consuming however. ArcView has its own
programming language called Avenue, which enables the user to develop new functions.
An avenue program, also called a script, can be used to create the desired function and
hence be able to solve the problem in a better computing environment.
 The first step is to create a program which quickly and automatically determines
if a station is correctly located in the creek. The principle is to use a grid of the streams
where the value of the cells containing the creeks is one. All other cells are no data cells
(Figure 2.4). The value of the grid at the location of the stations indicates wether they are
correctly located in the creeks.
 
 
 
 
 
 
Figure 2.4: Station location
 This process is done by using a script called Qual.Pick (Appendix C),
customized with the button  which is accessible when the View window is active.
          No data
 1
21
This program allows one to obtain the values of several grids at the locations given by a
point coverage. When clicking on , a series of message boxes prompt the user for the
 grid(s) (Figure 2.5) and the point coverage (Figure 2.6) to use in the program.
 
 
Figure 2.5: Choose the grids (Qual.Pick)
 
 
Figure 2.6: Choose a point coverage (Qual.Pick)
 Several grids may be selected. However in this case, the only grid to select
(crk100_gr) is a creek grid whose cell value is one in the creeks and no data elsewhere,
the creeks being defined as the cells with a drainage area bigger than 100 cells. For each
point in the point coverage, the program writes the value associated to the grid cell where
22
the point is located to a new field added to the attribute table of the point coverage. By
default, the name of the grid the value is taken from is also the name of the field. If the
field already exists, a message box prompts the user either to choose a new name or to
overwrite the existing field (Figure 2.7).
 
 
Figure 2.7: Overwrite an existing field (Qual.Pick)
 Whether a point is in a creek can then be checked by looking at its value in the
new field, which is either 1 or no data.  In the second case, the location of the point must
be modified so that it will eventually be located in the creek. The modification is done
with the script Qual.Addpoint (Appendix C), customized with the tool . This tool is
activated when the button is depressed. A new point is created by clicking on its desired
location on the view. A message box gives the alternative between creating a new point
coverage and modifying an existing one (Figure 2.8).
 
23
 
Figure 2.8: Create a new point coverage (Qual.Addpoint)
 
 If the objective is to modify the stations' point coverage, the answer is ?no?.
Another message box prompts for the name of the coverage to modify (Figure 2.9).
Figure 2.9: Choose the coverage to modify (Qual.Addpoint)
 
 Once the point coverage has been chosen, the user is asked wether he wants to
use the snap option. This option allows one to ascertain that a point is exactly located on
a given line coverage representing the creeks, which is the vector representation of a
considered grid stream network. This option is activated by answering ?yes? to the
message box shown in Figure 2.10.
24
 
Figure 2.10: Snap option (Qual.Addpoint)
 
 A message box prompts for the line coverage filename to use (Figure 2.11). The
line coverage must correspond to the grid representation of the creeks. In this case, the
coverage (crk100_cv) used is the creeks corresponding to a threshold, i.e. a drainage area,
of 100 cells).
 
Figure 2.11: Choose a line coverage for the snap option (Qual.Addpoint)
 
 The next message box tells the user wether the point has been successfully
snapped to the chosen line coverage. If the procedure has been successful, the following
message box appears (Figure 2.12).
 
25
 
Figure 2.12: Successful snap (Qual.Addpoint)
 
 However, if the distance from the point to the line is larger than the tolerance
value, the point can not be snapped and the message ?No line theme found? appears. The
point remains at the location first chosen.
 The user then has the option to edit the fields for the new point. For a new
coverage, the only existing field is the field ?id?. Other fields can be added by using the
commands Table/Start Editing and Edit/Add Field in ArcView. For an existing coverage,
a message box listing up to the first ten fields appears (Figure 2.13).
 
 
Figure 2.13: Edit the fields (Qual.Addpoint)
 Figure 2.14 shows the location of a particular gage before and after the
correction.
26
 
 
Figure 2.14: Gage location before and after correction
 Once all the stations have been modified, the old points have become obsolete
and must be deleted by highlighting their record in the attribute table and by using the
commands Table/Start Editing and Edit/Delete Records.
 The new point coverage must be checked as some points located on the line may
also be at the junction of two cells, and hence have no data for grid value (Figure 2.15).
27
To avoid this problem, the grid can be used as a background theme when locating the
points.
 
Figure 2.15: Cell junction
2.3 ENVIRONMENTAL INTEGRITY INDEX SITES
2.3.1 Locate the stations
 Locating the Environmental Integrity Index stations required a different approach
since their geographic coordinates were not available. At the beginning of the study, a
Global Positioning System (GPS) was used to locate 45 Environmental Integrity Index
sites. The same procedure used for the USGS stations was then applied to create the
corresponding point coverage for those sites.
 The City of Austin eventually provided a point coverage of new sites, which
included the Environmental Integrity Index stations. However, there were additional
stations to consider and two new sources of information became available, a scanned
map and a detailed roads coverage (double line roads). This made it possible to locate the
Environmental Integrity Index stations by direct comparison with a scanned map.
? Scanned map
 Scanned map images of USGS topographic sheets for the Austin area were
obtained from Horizons Technologies (http://www.horizons.com), Inc at a scale of
 Cell junction
(no data)
28
1:24,000. These map images were in geographic coordinates and had to be converted to
State Plane coordinates. The projection file included a X and Y raster shift which was
defined empirically by Francisco Olivera so that the streams defined from the 30m
digital elevation model reasonably matched the blue line representation of the same
streams on the USGS map image. The map was converted to a grid, which was projected
according to the projection file shown in Table 2.7. It was finally reconverted back to a
map.
Arc: grid
Grid: imagegrid austin.tif aust_geo colors
Grid: project grid aust_geo aust_stp stamap_prj
Grid: gridimage aust_stp colors austinsp.tif TIFF
 Table 2.7: Scanned map projection file (stamap_prj)
Projection STATEPLANE
Zone 5376
Datum NAD27
Zunits NO
Units FEET
Spheroid CLARKE1866
Xshift 112.0000000000
Yshift -69.0000000000
Parameters
End
 The result is a map (Figure 2.16) which can serve as a background to the other
coverages or grids displayed.
 
29
 
Figure 2.16: 1:24,000 USGS scanned map (detail)
 The map can be used to directly locate the points representing the stations if their
location is shown on the equivalent paper USGS topo sheet. It can also be used as a new
source to confirm the location of the creeks.
? Double line roads
 The double line road coverage also gives important information about the area
(Figure 2.17). Combined with the scanned maps, this coverage enables one to locate the
points more accurately, as the stations are often referenced using street name.
30
 
Figure 2.17: Double line roads coverage of Austin
2.3.2 Create a point coverage in ArcView
 Since the locations of the Environmnetal Integrity Index stations were shown on
a USGS map similar to the  scanned map, it was possible to create the point coverage by
clicking directly on the View window in ArcView at the desired location. The script used
to create the point coverage is the same that was used to modify the USGS coverage
previously (Qual.Addpoint, Appendix C). This script also guarantees that the points are
located in the creeks.
 The script is first used to create a new point coverage and then to add new points
to it as was shown for the USGS stations. Hence the answer to the first message box,
asking the user wether he, or she, wants to create a new point coverage is ?yes?. The next
31
message box prompts the user for the path and the name of the new point coverage
(Figure 2.18).
 
 
Figure 2.18: Name and path of the new coverage (Qual.Addpoint)
 The field ?id? is created automatically in the attribute table of the point coverage.
Other fields can be added by editing the table by using the commands Table/Start
Editing and Edit/Addfield. Other points are added by using the procedure described for
the USGS stations.
2.4 RETRIEVE INFORMATION AT THE STATIONS
2.4.1 Retrieve the grid values
 The goal of the project is to get the loads and watershed properties (impervious
cover, discharge, percentage of land use...) at the Environmental Integrity Index sites.
ArcView includes an information button  which enables the user to get the
32
information from an attribute table for any location. This process is efficient when
dealing with a limited number of points but it soon begins to be time-consuming for
large numbers of points.
 The script Qual.Pick presented in section 2.2.3 was written to allow all the
information to be gathered in one step. This script allows the user to select a point
coverage and one (or several) grid(s), and  to retrieve the values of the grid(s) at the
location of the points. The values are written in fields in the point coverage attribute
table named by default after the corresponding grids. However, if a field already exists, a
message box gives the user a choice between renaming the field and overwriting the
already existing one.
2.4.2 Characterize the stations
 Information concerning the stations can be gathered and written in Excel files.
To be used in Arc/Info or ArcView, the data must be converted either to a .dbf or a .txt
format, by using the option File/Save as in Excel.
 In Arc/Info Tables, some data related to a coverage can be permanently added to
the attributes table of the coverage. In ArcView however, the join function enables one to
edit the attribute table with the new data only in that project. The original attribute table
is not modified. Since it is more convenient to work with tabular data in ArcView, a
script was written to allow two tables to be permanently joined in ArcView.
 Without a script, the more convenient way to add data contained in one table to a
corresponding attribute table in ArcView is to join the two tables, then to add new fields
corresponding to those which have just been joined and set the new field values equal to
33
the joined field values. The last step is to remove the join, which yields an attribute table
with only the manually added fields. The same approach was used in the script
Qual.Join, which just automates this process (Appendix C). The script can be run by
clicking on the button  which appears when a table is active. Four message boxes
prompt the user respectively for:
? a destination table (Figure 2.19)
? a common field for the destination table
? a source table
? a common field for the source table
 
Figure 2.19: Choose a destination table (Qual.Join)
 The destination table is the table the fields are joined to. The common field is the
field used to relate the records of the destination and source tables.
2.4.3 Delete the fields
 Data retrieval and table joinS may create numerous fields in a table. When the
field are no longer used, it is wise to delete them. The delete command in ArcView
(Table/Start Editing, then Edit/Delete Field) enables one to delete one field at a time.
Given the large number of fields which may have to be deleted, the script Qual.Delete
34
(Appendix C) was written to allow several fields to be deleted in one step. This script is
activated with the button , which is visible when a table is active. A message box
appears by clicking on the button, prompting the user for the table to edit (Figure 2.20).
 
Figure 2.20: Choose a table to edit (Qual.Delete)
 A second message box prompts for the list of fields to delete (Figure 2.21). Note
that some of the fields are read-only fields (e.g. shape) and cannot be deleted.
 
Figure 2.21: Choose the fields to delete (Qual.Delete)
 After confirmation that the fields chosen are really the ones which must be
deleted, the deleting operation takes place.
  35
Chapter 3: GIS topography characterization
3.1 DIGITAL ELEVATION MODEL (DEM)
3.1.1 30m DEM
 The study area includes Austin and its immediate surroundings, and can be
represented by twenty-seven 7.5? USGS quadrants, each of them corresponding to an
elevation grid called Digital Elevation Model (DEM) (Figure 3.1). Each cell of the grid
is assigned the average elevation of the area represented by the cell. Each quadrant is
composed of 466 rows and 406 columns: the total area in Figure 3.1 is represented by
about 5 million 30-meter cells and covers about 4,600 km
2
.
 
Figure 3.1: USGS 1:24,000 quadrant sheets
  36
 The study area (outline in red in Figure 3.1) covers an area of 2,300 km
2
.
 Digital Elevation Models consist of a sampled array of elevations for ground
positions at regularly spaced intervals. They are used to define the direction of the flow
according to the topography and the drainage areas for any cell. Francisco Olivera did a
study of Austin based on 90m DEMs (Olivera, Maidment and Charbeneau, 1996). When
this study was done, 90m was the finest cell size available for the whole area. The results
show that the delineation is not good at all for some of the drainage areas. For example,
there is a 44% relative error between the areas observed on the field (about 5.7 mi
2
) and
delineated (8.2 mi
2
) for Waller Creek, which is a small urban watershed (Figure 3.2).
Moreover, the differences are more important at the gages located in the watershed
(Table 3.1).
 The use of 30m DEMs, which were available at the time for only part of the area,
greatly improves the delineation. Table 3.1 shows the different values obtained (from the
USGS and by delineation) for the drainage areas of the USGS stations located within the
Waller Creek watershed. The maximum relative error is less than 5%. Figure 3.2 shows
the differences between the digitized watersheds and those based on 30m or 90m DEMs
for Waller Creek.
 Table 3.1: Watersheds areas comparison for Waller Creek
 Stations (Waller Creek) 38
th
23
rd
 USGS 2.31 mi
2
4.13 mi
2
 30m DEM 2.39 mi
2
4.33 mi
2
 Relative error (30m) 3.5% 4.8%
 90m DEM 5.18 mi
2
6.65 mi
2
 Relative error (90m)            124%             61%
  37
Figure 3.2: Delineated Watershed vs. Digitized Watershed (Waller Creek)
 The comparison between the areas defined by the 30m and 90m DEMs
underlines the fact that the difference of cells size (90m to 30m) enables one to greatly
improve the delineation.
 It was very important to define as accurately as possible the drainage areas
corresponding to the USGS gauged stations as their data are used to build the model.
  38
There was a need to improve the delineation based on the 90m DEMs. In parallel with
this project, the City of Austin worked with a contractor to provide 30m DEMs for the
whole drainage area. The new availability for the whole Austin area of 30m DEMs which
enables to improve ten times the accuracy (Figure 3.3) allows one to really consider the
use of GIS for city-scale modeling. Each DEM being composed of about 190,000 cells,
the total area is represented by more than 5 million cells.
 
 
Figure 3.3: Comparison between 30m and 90m DEMs
 
  39
 While the comparison between the delineation obtained with the two types of
DEMs shows the greater accuracy of the 30m DEMs because of the smaller cell size,
there are however two main drawbacks to their use:
? they are more disk storage consuming.
? the computations take longer: for 5 million cells, the execution time for a
flowdirection or a flowaccumulation function is about one hour.
3.1.2 Use of a DEM
 A DEM is a representation of the topography of a given area. It is used to create
two further grids (Figure 3.4):
? a Flowdirection grid, which indicates the path of the water through the landscape.
The cell value corresponds to one of the eight geographic directions (north, northwest...)
indicating the direction of steepest slope.
? a Flowaccumulation grid, which defines the size of the drainage area. Each cell as its
value the number of cells located upstream, whose drainage passes through the given
cell.
 A variation to the Flowaccumulation is to associate a value or ?weight? (e.g.
runoff produced in a cell) to each cell and to sum this value instead of summing the
number of cells. This concept is the backbone of the model: once the cells have been
characterized, it is straightforward to obtain the sum of the characteristics values of the
upstream cells.
 
 
  40
 
 
 
 
 
 
 
 
 
 
 
Figure 3.4: Flowdirection and Flowaccumulation Grids
Figure 3.4: Flowdirection and Flowaccumulation grids
3.2 DEM PROCESSING
3.2.1 Pre-processing
 Twenty-seven USGS 7.5?quadrants are needed to cover the total area, each of
them being represented by a different DEM. In their initial format, the DEMs (source:
Vernon F. Meyer and Associates, Inc) cannot be used in GIS. They have to go through
 1  8 4
 4 1
 16
 4  8
 1  1  2  4
 128  64  1  ?
 64 N
 128  NE
 1 E
 2 SE
 4 S
 8 SO
 16 O
 32 NO
 0  1 1
 5 0
 0
 0  0
 0  9  12  0
 0  0  0  15
 45  44 38
 34 40
 45
 50  60
 58  31  30  53
 50  45  32  22
 DEM  Flowdirection Flow path
 Flowaccumulation 8 directions
  41
two pre-processing steps, to be reblocked and to be converted from USGS format to
Arc/Info lattice or grid format.
 
 %dd if=input_file of=output_file cbs=1024 conv=unblock
 %arc
 Arc: demlattice output_file output_dem
 (Convert a DEM in USGS or TAME format to a lattice)
 
 The resulting files can now be displayed either in Arc/Info or ArcView.
3.2.2 Merging/Projection
 The following two steps consist of merging all the quadrants together and
projecting the resulting DEM into the state plane coordinate system.
? Merge the grids
 In Arc/Info, each command must be typed within a few lines. Given the
important number of grids to merge, it was necessary to proceed in two steps.
 
 Grid: alldem = merge ( austn_e , austn_w , bastrpsw , beecave, buda , coupland ,
creedmor , drift , dripsprg, elgin_w , hamcross , henly , jollyvil , lyttsprg , manfiel ,
manor , montop , mountcty , oakhill , pflug_e , pflug_w , roughhol )
 
 Grid: alldem1 = merge ( alldem , shinghhi , signalhi , utley , webber , yeager )
? Project to state plane
 The resulting DEM is in the UTM (Universal Transverse Mercator) projection
system. It needs to be projected into the state plane projection system. The datum
NAD27 used in the project is based on the foot as the length measure. The 30m cell size
  42
is hence converted to a 100ft cell size and all the elevations values are resampled onto
the new grid during the map projection process.
 Grid: dem_st = project ( alldem1 , # , # , 100 )
 Project: output
 Project: projection state
 Project: zone 5376
 Project: units feet
 Project: parameters
 Project: end
 
3.2.3 Eliminate the no data cells
 As the borders of the grids are not perfectly adjusted, some no data cells are
created at the quadrant borders during the merging process. These cells can be viewed by
displaying the projected DEM in ArcView. It is very important to eliminate these no data
cells since otherwise they would act as sinks for the water. These cells must be assigned
a value, the average value of the surrounding cells, by editing the DEM grid dem_st
using Arctools. The procedure to check that all no data cells have been eliminated
consists of focusing on different zones of interest within the area where there should not
be any no data cells beside the ones due to the merging process (quadrants borders). For
each zone studied, the no data cells are assigned the value zero, as there is no zero in the
original grid. Then a grid can be created, with value one at the no data cells and no data
elsewhere. The number of remaining no data cells is obtained by describing the grid in
Arc/Info.
 
 Grid: xxx = con ( isnull (dem_st) , 0 , dem_st )
 Grid: yyy = con ( xxx == 0 , 1 )
 Grid: list yyy.vat
 
  43
 Record VALUE COUNT
           1 1 5
 
 In this case, there are 5 no data cells left. The editing process is carried on until
the average value of the surrounding cells has been assigned to each no data cell.
3.2.4 Burn in process
 The goal of the study is to determine the non-point source pollutant loads in
Austin creeks. So it is important that the delineated creeks match the observed creeks. To
guarantee that, the creeks are imbedded in the grid through a ?burn in? process. A large
elevation value is added to the elevation grid (10,000 ft in this case), so that any cell of
the new grid has an elevation higher than the maximum elevation in the original grid. A
grid containing only the creeks at their initial elevation value is then merged with the
raised DEM so that the resulting DEM has a thin, deep trench at the stream locations and
a normal landscape elsewhere.
 The burn in process is important because the real creeks do not always
correspond to the creeks defined by the DEM. For example, assuming that a creek is
coming into the cell with elevation 38 in Figure 3.5.a, according to the DEM it is then
going to the cell located in the direction of steepest descent. The corresponding flow path
is shown by the shaded cells in Figure 3.5.a. In reality, the true creek trajectory may be
different (Figure 3.5.b). The ?burn in? procedure is applied to guarantee that the
?correct? trajectory is obtained (Figure 3.5.c).
 
 
 
  44
 
 
 
 
 
 
Figure 3.5: Burn in process
 This procedure can be done either in Arc/Info grid or in ArcView. The Arc/Info
method is presented here. The method in ArcView is available on the internet (Olivera,
1996).
 
? Complete the stream coverage
 As the digitized creek coverage provided by the City of Austin does not cover
the whole study region, it must be augmented with streams from another source, which is
the EPA Reach File 3 (RF3). For Austin, those files are 12090205 (205_st) and
12090301 (301_st).
 
 3.5.c Burnt in DEM
 45  44 38
 34 40
 45
 50  60
 58  31  30  53
 50  45  32  22
 45  44 38
 34 40
 45
 50  60
 58  31  30  53
 50  45  32  22
 145  144 138
 134 140
 145
 150  160
 158  131  130  153
 150  145  132  122
   38
 34 
 
  
   30  
   22
 145  144 38
 34 140
 145
 150  160
 158  131  30  153
 150  145  132  22
 
 3.5.a DEM creek  3.5.b Digitized creek
    Digitized creek     Raised DEM  Burnt in DEM
  45
 There are two solutions to augment the streams:
? convert the coverages to grids, use the merge command to combine the two creek
coverages, and then make the appropriate corrections in Arctools.
? proceed directly with the coverages, make the corrections in Arcedit and use a script
written by Zichuan Ye (Qual.Mergethm, Appendix C) in ArcView to merge them as
there is no command in Arc/Info to merge arc coverages.
 As the conversions to grid and then back to a coverage modify slightly the
coverages, to obtain a creek coverage as close as possible to the original, the second
method was implemented. The part of the RF3 to be used is selected in ArcView,
converted first to a shapefile and then to an arc coverage called rf3_cplt. Since the
coverages creeks and rf3_cplt do not match at their junction, rf3_cplt is corrected in
Arc/Info Arcedit.
Arc: arcedit
 The first steps consist in defining the edit coverage, the edit feature (arcs in this
case), the back coverage and the back environment as well as the drawing environment.
Arcedit: ec rf3_cplt
Arcedit: ef arcs
Arcedit: backenvironment arc
Arcedit: backcoverage creeks 2
Arcedit: drawenvironment arc
Arcedit: mape rf3_cplt
Arcedit: &station 9999
Arcedit: draw
 Since arc is the edit feature, only arcs can be deleted. Hence if the line to be
deleted is just a part of an arc, it must be first defined as an arc by using the command
split, and then deleted.
  46
 
Arcedit: select *
Arcedit: split
Arcedit: select *
Arcedit: delete
Arcedit: save
 As the coverages come from two different sources (City of Austin and EPA),
they do not match exactly. Some links must be established between them.
Arcedit: ec rf3_cplt
Arcedit: ef link
Arcedit: backcoverage creeks 2
Arcedit: backenvironment arc node
Arcedit: drawenvironment arc node link
Arcedit: mape rf3_cplt
Arcedit: &station 9999
Arcedit: draw
Arcedit: snapcoverage creeks
Arcedit: linkfeatures node node
Arcedit: snapping closest *
Arcedit: limitautolink box
Arcedit: autolink
Arcedit: adjust
Arcedit: save
 The coverages rf3_cplt and creeks must then be joined in ArcView by using the
script Qual.Mergetheme ( 
 
or QualTools/Merge Themes
 
) to create burn_crk, the
stream network used in the burn in process. In fact a grid form of the water bodies, which
takes into account both lakes and creeks, is used in the process.
 
 
 
  47
? Burn in
 The first step is to convert the digitized network of lakes and creeks into two
grids in State Plane coordinates, and merge them together to create a grid of value one.
 Grid: lakes_gr = polygrid ( lakes )
 Grid: creek_gr = polygrid ( burn_crk )
 Grid: str_gr = merge ( lakes_gr , creek_gr )
 Grid: water1_gr = con  ( str_gr , 1 )
 Grid: water_gr = water1_gr * dem_st
 
 Gaps in the stream network are corrected in Arctools, because one of the
following procedures consists in filling the sinks. A gap in a creek prevents the water
from flowing and this creek will be considered as a sink and filled. Finally, the water
grid (water_gr) is merged with the DEM to which 10,000 ft has been added.
 
 Grid: dem_pls = dem_st + 10000
 Grid: burn_dem = merge ( water_gr , dem_pls)
 
 The order of the terms in the merge command is important. The values of the
second grid will be taken only for the cells in which the first grid has no data. The result
of the command merge( dem_pls , water_gr ) is then dem_pls.
3.2.5 Burning walls
 In some areas, the DEM delineated watersheds may not match the ?real?
watersheds, because the zone is too flat or because of storm sewers which divert the
runoff. The City of Austin was concerned with these differences, especially for Blunn
and West Bouldin watersheds. A procedure was created so that the watershed boundaries
can be forced to be where they are supposed to be (same concept as the burn in process).
  48
Instead of digging trenches, walls are built. The coverage wsheds being the polygon
coverage of the ?real? watersheds, the procedure is:
 
 Arc: build wsheds line
 Arc: grid
 Grid: wshed_gr = linegrid ( wsheds )
 Grid: wall1 = con ( wshed_gr  , 1 )
 Grid: wall2 = wall1 * dem_st
 Grid: wall20k = wall2 + 20000
 Grid: burnw_dem = merge ( water_gr , wall20k , dem_pls )
 
 This procedure affects the original topography: the ?forced boundaries? must be
at the highest elevations in the watersheds. Since the water must flow from the
boundaries toward the creek, the elevations of the cells located between the original and
the ?forced? boundaries must also be modified through a filling process (section 3.2.6).
The information given by the DEM is not used anymore. As the study is based on the
topography, this procedure was eventually not used.
3.2.6 Flowdirection/Flowaccumulation computation
 The DEM on which the creeks have been burnt in must undergo one last
procedure before being used to create the flowdirection and flowaccumulation grids. If a
cell is surrounded by higher elevation cells, the water is trapped in that cell and can not
flow. It can really happen if, for example, the water infiltrates through the bottom of a
lake. In the case studied here however, these cells must be corrected by using the
function fill, which modifies the elevation values to eliminate these problems. As this
function is based on the direction of the flow, it enables one to create also the
flowdirection grid, burn_fdr.
  49
 
 Grid: fill burn_dem burn_fil # # burn_fdr
 
 The flowaccumulation grid is computed from the flowdirection grid.
 
 Grid: burn_fac = flowaccumulation ( burn_fdr )
3.3 VALIDATION OF THE METHOD
 It is necessary to check the validity of the chosen approach for the entire area.
The model is correct only if the DEM gives an adequate representation of the
topography.
3.3.1 Quantitative assessment of the topographic representation
 With the flowaccumulation grid, the drainage basin of any cell of the grid can be
determined. The areas of the basins corresponding to the USGS stations can be obtained
from the USGS web site (http://txwww.cr.usgs.gov/cgi-bin/txnwis). By delineating the
basins, a comparison between the areas can be done (Figure 3.6). The watersheds can be
delineated either in Arc/Info or ArcView.
 In Arc/Info, the delineation is based on a grid representation of the USGS
stations point coverage.
 Grid: setcell 100
 Grid: usgs_gr = pointgrid ( usgs_cv )
 
 The USGS watersheds are then delineated using the watershed function and
converted from a grid to a coverage:
 Grid: usgswshd_gr = watershed ( burn_fdr , usgs_gr )
 Grid: usgswshd_cv = gridpoly ( usgswshd_gr)
 
  50
  The delineation in ArcView uses the script Qual.Watershed, customized with
the button 
 
and the menu QualTools/Watershed (Appendix C). A series of message
boxes prompt the user for the names of the output watershed grid and coverage, as well
as for the input point coverage and flow direction grid. The last message box prompts the
user for a ranking field. This field is used to identify the different points and their
corresponding watershed. The values in that field must be integer numbers different for
each record. They also must be within a range of 1,000,000 to be displayed in ArcView
(integer lookup table range).
 The drainage areas match quite well except in one case (station 8159000, Onion
at US 183) where it appears that there is a problem of definition regarding what should
be considered as the watershed. From a quantitative point of view the match of areas is
good.
  51
Comparison between the USGS watersheds areas 
obtained from the USGS and from the 30m DEMs
0
20
40
60
80
100
120
140
160
180
8155260 8155300 8155240 8155200 8158810 8158050 8154700 8158800 8158700 8159000 8156700 8156800 8158840 8157500 8157000 8158600 8158920 8158970
USGS stations
Area (mi
2
)
 DEM area (sqmi)
Reference area (sqmi)
Figure 3.6: Comparison between the USGS stations drainage areas obtained from the
USGS and delineated with the DEMs
3.3.2 Qualitative assessment of the topographic representation
 It is not enough that the area values match. The delineated basin boundaries must
equally correspond to the real ones. Digitized watersheds, based on field observations,
are available for the Austin region. A comparison with DEM delineated watersheds
shows that the model gives good results, except for some flat areas (Figure 3.7).
  52
However, the results are good enough for the watersheds under study to carry on this
approach.
 
Figure 3.7: Comparison between digitized and delineated watersheds
  53
3.4 CREEK AND WATERSHED DELINEATION
3.4.1 Method
 A creek can be defined according to a flow accumulation value: the cells whose
drainage area is bigger than a given threshold are considered to be in the creek.
 Grid: crk100_gr = con ( burn_fac > 100 , 1 )
 Grid: crk100_cv = streamline ( crk100_gr , burn_fdr )
 Grid: lk100 = streamlink ( crk100_gr , burn_fdr )
 Grid: wshd100_gr = watershed ( burn_fdr , lnk100 )
 Grid: wshd100_cv = gridpoly ( wshd100_gr )
 
 The conversion from grid to arc coverage uses the function streamline instead of
the function gridline. Gridline does not allow parallel lines if they are too close and
creates instead a node (Figure 3.8).
 
 
 
Figure 3.8: Difference between the commands streamline and gridline
 The creeks can also be delineated in ArcView by using the script Qual.Creek
(Appendix C). This script can be run by clicking on the button 
 
or by using the
command QualTools/Creek. The user is prompted for a flowdirection grid and a
 Streamline  Gridline
  54
flowaccumulation grid, and for a creek threshold (number of 100ft cells). Two files are
created: a creek grid and the associated line coverage.
 Several creeks and watersheds networks can be used corresponding to different
degrees of accuracy. Figure 3.9 represents the creeks delineated threshold values ranging
from 100 to 10,000 cells.
 
Figure 3.9: Stream network for different thresholds (100 to 10,000 cells)
  55
 It is possible to compare the location of the delineated creeks with the stream
network of the scanned 1:24,000 USGS maps. The results are correct, except in a few
cases for which the digitized creeks do not correspond to the streams on the map.
3.4.2 Define the upstream limit of a creek
 A creek can be defined by a threshold value. All cells whose drainage area is
bigger than a given value are considered to be in a creek. The upstream limit of the
stream network can hence be found by looking for the first cells in the different creeks
where the drainage area is greater than that threshold value. Each cell is 100ft*100ft =
10,000 ft
2
 = 0.2296 acres in area.
 For example, for a threshold of 64 acres (279 cells), the procedure is:
 Grid: crk279 = con ( burn_fac > 279 , 1 )
 Grid: fac279 = flowaccumulation ( burn_fdr , crk279 )
 Grid: pt279 = con ( crk279 == 1 and fac279 == 0 , burn_fac )
 Grid: pt279_cv1 = gridpoint ( pt279 )
 Grid: project cover pt279_cv1 pt279_geo
 Grid: addxy pt279_geo
 Grid: project cover pt279_geo pt279_cv
 Grid: crk279_cv = streamline ( crk279 , burn_fdr )
 
 The result is a point coverage (Figure 3.10) representing the upstream limit of
the streams defined as the point with a drainage zone of at least 64 acres (279 cells).
 
  56
 
Figure 3.10: Creeks draining at least 64 acres in Bull Creek Watershed
 An ArcView script (Qual.Creeklimit, Appendix C) allows the user to build a grid
containing the points representing the limit of the creeks for a chosen threshold. This
script can be run by clicking on the button  or by using the command
QualTools/Creek limit when a View is active. The user is prompted for a
flowaccumulation grid and a flowdirection grid, and for a creek threshold (number of
100ft cells).
3.4.3 Getting rid of the dangling polygons
 A comparison between the watershed grid and the polygon coverage produced by
the Gridpoly function shows that some ?extra? watersheds (dangling polygons) appear
  57
during the conversion to the vector form. They are small polygons (a few cells) which
have the same grid-code as a larger polygon with which they share a corner, but not a
side. They are listed as separate records in the polygon attribute table.
 A script to eliminate the dangling polygons was written by Zichuan Ye as part of
an ArcView based watershed delineation application developed by Environmental
Systems Research Institute (ESRI, Inc.) for the Texas Natural Resource Conservation
Commission (TNRCC). This script (Qual.HydroZdslv) allows one to change the grid-
code in dangling polygons to that of an adjacent polygon that does share a side. The
script is customized with the button 
 
and the command QualTools/Dangling. The
user is prompted to enter the name of a polygon coverage (e.g. wshd) and of the
associated polyline coverage. Both may have the same name. After running the script,
the "dissolve" function in Arc/Info allows the user to merge the dangling polygons with
the polygons with the same grid-code.
 
 Arc: dissolve wshd wshd_diss grid-code
 
 Some dangling polygons may remain in two cases:
?     a no data cell is inside a watershed: the solution is to set its grid-code to the
watershed grid-code.
?     a cell with a grid-code among no data cells: the solution is to set its grid-code to a
specific value corresponding to no data (i.e. ?9999).
  58
 
Figure 3.11: Dangling polygons
 The modifications are made manually by editing the polygon attribute table in
ArcView. For example, if wshd_diss is the watershed coverage obtained after running the
script, its attribute table is modified according to the previous description.
 In Arc Info, to get rid of the second problem (cells in the no data field which
have now the value -9999), the reselect command is used to keep only the cells with a
positive value.
 
 Arc: reselect wshddiss wshddiss1
 Reselecting POLYGON features from WSHDDISS to create WSHDDISS1
 Enter a logical expression. (Enter a blank line when finished)
 >: res grid-code > 0
 >:
 Do you wish to re-enter expression (Y/N)? n
 Do you wish to enter another expression (Y/N)? n
 no data
 same
 grid-code
 dangling
polygon
 -9999
 Reselect
 Dissolve
 same
 grid-code
  59
 
 The resulting coverage is then dissolved to eliminate the first problem.
 Arc: dissolve wshddiss1 wshddiss2 grid-code
 
 The final coverage wshddiss2 has the same number of polygons as the grid.
 
 The digital elevation model has been processed and the flowaccumulation and
flowdirection grids on which the model is based have been created. Watersheds and
creeks have been delineated and compared with observed data.
  60
Chapter 4: Input parameters
 The load is equal to the product of the discharge and the concentration, which
both depend on precipitation and on land use. These two elements are the input
parameters of the model (Figure 4.1).
 
 
 
MODELE
MODEL
INPUT OUTPUT
Precipitation
Land use
Discharge
Load
Figure 4.1: Model input and output
4.1 PRECIPITATION
 The annual average rainfall given by the City of Austin to use for loading
computation is 31.08 inches. It was computed according to EPA procedures using hourly
data collected at the Austin airport during the period 1948-1993. Any ?event? that did
not generate at least 0.05 inches of rainfall within 6 hours was deleted. The mean annual
storm event is one that occurs, on average, 51.8 times a year, has a volume of 0.60
inches, a duration of 7.8 hours, an average intensity of 0.106 inches/hour, and with 172.1
hours between storm event midpoints. In Austin, it rains about every 7 days on average.
  61
 Annual precipitation data may be obtained from the National Climatic Data
Center (NCDC) Website (http://www.ncdc.noaa.gov/coop-precip.html). There are three
stations in Austin, but the Airport site is the only one with a continuous record since
1948. The average annual value for this period is 32.00 inches. For the period 1985-
1994, the annual average rainfall volume is 34.37 inches. The value used (31.08 inches)
underestimates slightly the volume of precipitation. However, in comparison with the
variations in annual precipitation from year to year (from 12 to 55 inches), the difference
is negligible (Figure 4.2).
 
Annual precipitation (in/yr) at the Austin Airport
0
10
20
30
40
50
60
1950 1955 1960 1965 1970 1975 1980 1985 1990 1995
Year
Pr
e
c
ipit
a
t
ion (
in/y
r
)
Precipitation(in/yr)
Average 1948-1994
Average 1985-1994
 Figure 4.2: Annual precipitation at the Austin airport
  62
4.2 LAND USE
 The discharge depends on the part of the rainfall which contributes to the flow.
This percentage is assumed to be related to the land use through relationships with the
impervious cover.
4.2.1 Current land use
? Impervious cover/Land use relationships
 The City of Austin has chosen to classify land use into nine categories (plus
water) for its Water Quality Master Planning project (Table 4.1).
 
 Table 4.1: Land use categories for the study
 Single Family  Office  Park
 Multi Family  Industrial  Transportation
 Commercial  Civic  Undeveloped
 
 The City has assigned to each category a range of impervious cover shown in
Table 4.1, which is used to determine the runoff coefficients and the concentrations of
the constituents (EMCs). A distinction was made between urban and non urban areas
(Figure 4.3). The urban areas correspond to the city chore where each land use is
assumed to have a higher impervious cover. The urban areas were assigned the upper
limit of the range and the non urban areas the lower limit. The urban areas include the
following watersheds (Table 4.2).
 
 
  63
 Table 4 2: Urban watersheds
 Blunn  Town Lake  Buttermilk
 East Bouldin  Johnson  Little Walnut
 West Bouldin  Shoal  Fort Branch
 Harper?s Branch  Waller  Tannehill
 Country Club  Boggy  
 
 
 
Figure 4.3: Urban and Non urban watersheds
 The relationship between the land use and the impervious cover are shown in
Table 4.3 for the land use categories considered.
 
 
 
  64
 Table 4.3: Land use-Impervious cover relationship
 Land use  Impervious cover (%)
 Category  Code  Urban  Non urban
 Single family  100, 113  40  30
 Multi family  200  80  45
 Commercial  300  95  60
 Office  400  95  60
 Industrial  500, 560  95  60
 Civic  600  70  30
 Park  700  15  5
 Transportation  800, 870  100  85
 Undeveloped  900, 999  15  5
 Water  940  100  100
 
 Most streets and roads are included in the overall land use they support. The
transportation land use is reserved for only the largest of roadways (IH-35, MoPac) or for
other uses such as railroads, but not for average city streets.
? Land use coverage
 The Planning and Development Department of the City of Austin supplied the
land use coverage used in the model. It contains some extra categories, which have to be
reclassified among the existing ones (Table 4.4).
 Table 4.4: Extra City of Austin land uses categories
 Coverage  New classification
 Code  Category  Code  Category
 113  Mobile home  100  Single family
 560  Open extraction  500  Industrial
 870  Utilities  800  Transportation
 999  Unknown  900  Undeveloped
 
 The category ?utilities? was defined as equivalent to transportation.
 The land use coverage supplied by the City (landuse) does not cover the entire
study area and must be supplemented with the USGS land use coverage which can be
  65
downloaded from the EPA (EPAluse, http://www.tnris.state.tx.us/ftparea.html). The first
step is to keep only the part of EPAluse which is inside the study area defined by the
polygon coverage border. This new coverage is then used to complete the missing part.
Those coverages come from two different sources. The city land use was updated in 1990
whereas the USGS land use was created in the 1960?s. However, as the missing parts are
located in mostly undeveloped areas, the land use has little changed during the interval.
 Arc: intersect EPAluse border luseborder
 Arc: union landuse luseborder finluse
 
 The resulting polygon coverage finluse contains the fields from the two input
coverages. The objective is to obtain a coverage following the City of Austin
classification for the entire study region. The principle is to create a new land use code
column in the attribute table (newlandusecode). The values in this field are equal to the
City codes when applicable. However, USGS data used to complete the land use
coverage employ a different code, which has first to be converted to the City standard
(Table 4.5).
 Table 4.5: USGS/City of Austin land uses classifications
 USGS  City of Austin
 Code  Category  Code  Category
 11  Residential  100  Single family
 12  Commercial services  300  Commercial
 13  Industrial  500  Industry
 14  Transportation  800  Transportation
 16  Mixed urban or build-up land  600  Civic
 17  Other urban or build-up land  600  Civic
 21-43  Cropland, pasture, orchards, groves,
vineyards, agriculture, forest
 900  Undeveloped
 53  Reservoir  940  Water
 75  Strip mines, quarries  900  Undeveloped
 77  Mixed barren lands  900  Undeveloped
 
  66
 The edited newlandusecode field is used to dissolve the coverage in Arc/Info so
that the resulting coverage represents the different land use polygons according to the
City of Austin classification (Figure 4.4).
 
Figure 4.4: Current land use
 The impervious cover can then be directly obtained (Figure 4.5) by applying the
land use/impervious cover relationships to create the corresponding IC fields in the
coverage attribute table.
 
  67
Figure 4.5: Current impervious cover
4.2.2 Future land use
? Traffic Serial Zones
 It is difficult to accurately forecast the future distribution of land uses, so there
are represented as an average within the traffic serial zones. The traffic serial zones are
areas used in transportation studies: each zone is delimited by roads with a given traffic.
The predicted future impervious cover was computed by the City of Austin. Starting
from the current land use within the different zones, the City of Austin made some
  68
assumptions about the future development. The impervious cover at any location can
only increase. Figure 4.6 shows the increase between future and current impervious
cover.
 
Figure 4.6: Impervious cover increase in the traffic serial zones
 To compare current and future impervious cover, the current values must first be
averaged over the traffic serial zones. The average value in a zone is computed with the
zonalmean function in Arc/Info Grid.
  69
 Grid: zones_gr = polygrid ( zones )
 Grid: ic_gr = polygrid ( finluse , ic )
 Grid: iczone_avg = zonalmean ( zones , ic_gr )
 
 A script (Qual.Zonalmean, Appendix C) was written so that the zonal average
can also be computed in ArcView. The script was customized with the button . Two
message boxes prompt the user for a zone coverage and for a value theme (grid or
coverage).
 The comparison between current and future average impervious covers in the
traffic serial zones shows that the impervious cover decreases in a few zones. The
problem arises because the current impervious cover is defined in two different ways. To
guarantee an increase in impervious cover, the future impervious cover in the traffic
serial zones must be defined as the higher value of the current and future average values.
This can be done in Arc/Info by taking the difference between the future and current
average impervious cover grid, and by replacing the future impervious cover by the
current one in the future impervious grid in the zone where the difference of impervious
cover is negative.
 Since the traffic serial zones do not cover the whole area, the missing parts have
to be completed. There are two main missing zones. The first consists in the western
parts of Barton, Onion and Bear watersheds while the second corresponds to the part of
Dry and Colorado watersheds. As Barton belongs to the study area, it is important to
complete the zones with an accurate value. It is assumed that this zone has the same
development as the traffic serial zone 43 which is located in Barton (Figure 4.7). For the
other zone, two values are defined corresponding to the average values of the closest
  70
traffic serial zones located in the same watershed. However, the definition in that area is
not very important because they do not belong to the watersheds studied and because
they are at the limit of the study (downstream part of the watershed is missing).  In
Arc/Info the function union enables one to create a complete zone coverage over the
entire study area. The impervious cover corresponding to the new zones are added in the
TSZ field which identifies the different zones.
 
 
Figure 4.7: Future impervious cover defined by the traffic serial zones
 
  71
? Comparison between current and future impervious cover
 The average impervious cover value at any location within the area of study can
be obtained by using the function flowaccumulation. The script Qual.Average (Appendix
C) was written so that the average value could be directly computed in ArcView. This
script is customized with the  button and the command QualTools/Average. The
program is based on the principle used in Arc/Info. The required input data are a
flowdirection grid, a flowaccumulation grid and either a coverage or a grid containing the
value to average (in this case, the impervious cover).
 The comparison between the resulting current and future average impervious
covers shows that some problems still remain. The current impervious cover is higher
than the future one for some locations. This is due to the fact that the average definition
smoothes the impervious cover values. For some locations, like in Johnson watershed
where the current impervious cover is equal to 100% (urban transportation), the values
for points located in the upstream part of the watersheds can be very high for current
conditions and lower for future which are averaged. To guarantee that the impervious
cover at any location increases, the problem caused by the difference of accuracy in the
definition of the data has to be solved. The alternatives are to either decrease the current
accuracy or increase the future one. To keep the accuracy of the current coverage, the
future impervious cover is defined from the current one so that the impervious cover is
increasing in each cell (Figure 4.8). The method, presented by Dr. Francisco Olivera,
consists in defining the future impervious cover as the sum of the current one and of a
positive number depending on the average impervious cover value associated with the
traffic serial zone and on the current impervious cover in the cell.
 [4.1]
  72
 
 Where IC and IC
FC 
   are respectively the average future and current impervious
covers over each traffic serial zone.
 This relationship is set up so that:
? IC
F
 > IC
C
? IC
F
 < 1
? The average value of IC
F
 over the TSZ ( IC
F
) is the same as the value
associated to the corresponding TSZ.
? Less developed areas tend to develop more than already developed areas.
IC IC IC
IC IC
IC
FC C
FC
C
=+?
?
?
()*1
1
  73
Figure 4.8: Future Impervious Cover
  74
 The input parameters (precipitation, land use) used in the model have been
defined, as well as the relationships between land use and impervious cover. A
procedure to relate future and current impervious cover has been implemented so that
impervious cover increases with time.
 The input parameters are used with the flowdirection and flowaccumulation
grids previously defined to compute flow, load and BMP effects.
 
  75
Chapter 5: Discharge
5.1 COMPUTATION METHOD
 Several factors were considered in the computation of the discharge. Direct
runoff and base flow components of flows were initially calculated, not accounting for
flow losses in the recharge zone. Then, losses were calculated (in base flow and runoff
components) and subtracted from flows occurring in the recharge zone. Finally, predicted
flows were corrected to match the flows observed at the USGS stations.
5.1.1 Two modes of contribution
 Rainfall contributes to stream discharge in two ways (Figure 5.1):
? by direct (surface) runoff.
? by infiltration and contribution as base flow.
 The discharges computed are annual average data, therefore the lag time between
rainfall and flow does not have to be considered, which greatly simplifies the model
since this lag time is different for direct runoff and for base flow. Two runoff coefficients
determine the percentage of precipitation volume contributing to the discharge as direct
runoff (Rv) or base flow (Rv
bf
) (Figure 5.1).
 
 
 
 
  76
 
 
 
 
 
 
 
 
Figure 5.1: The two modes of contribution of precipitation
 These coefficients are a function of the impervious cover, which is a function of
land use. Relationships between impervious cover (IC) and runoff coefficients (Rv and
Rv
bf
) were calculated by Dr. Michael Barrett of CRWR (Barrett, 197) from observed data
(Figures 5.2 and 5.3).
 
                        Rv = 0.3428 * IC
2 
+ 0.5677* IC + 0.0125, with 0 < IC< 1
 
                        Rv
bf
 = - 0.36 * IC + 0.1904, with 0 < IC < 1
 
 P
 
 Rv * P
 Rv
bf
 * P
 
    Creek
 [5.1.a]
 
 [5.1.b]
  77
 
y = 0.3428x
2
 + 0.5677x + 0.0125
R
2
 = 0.9155
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Impervious Cover
Rv
Non-Recharge Recharge
Figure 5.2: Relationship between direct runoff coefficient and impervious cover
 
y = -0.0036x + 0.1904
R
2
 = 0.902
0.00
0.02
0.04
0.06
0.08
0.10
0.12
0.14
0.16
0.18
0.20
0 1020304050
Impervious Cover (%)
 Rs
Figure 5.3: Relationship between base flow coefficient and impervious cover
 
  78
 
 The relationship used to compute the base flow coefficient yields negative values
for impervious cover values bigger than 52%. Since it must be a positive number, the
base flow coefficient is then set to zero: no base flow occurs when the impervious cover
is bigger than 52%.
 The total amount of rainfall received by a water body contributes to the
discharge, which corresponds to a runoff coefficient of 1. However, the impervious cover
associated with water as a land use (100%) yields a computed total runoff coefficient of
0.923, which was used in the study (evaporation from water body).
5.1.2 Discharge produced by each cell
 The annual precipitation of 31.08 inches is applied uniformly over the region.
The contribution of any given cell to the discharge (in cfs) can be obtained by
multiplying the runoff coefficient by the annual average volume of precipitation and the
necessary units conversion coefficients.
 The direct runoff (Figure 5.4) is found as:
 
189216
5**)/(
=
12*365*86400
)(10000**)/(
=
)/(12*)/(365*)/(86400
)(area **)/(
=)(
2
2
RvyearinP
ftRvyearinP
ftinyeardaysdays
ftCellRvyearinP
cfsQ
r
 [5.2]
  79
and similarly the base flow as:
 
189216
5**)/(
=)(
bf
bf
RvyearinP
cfsQ
 
 to produce the total discharge
Q
t 
(cfs) = Q
r 
+ Q
bf
 
 
Cell area
Runoff coefficients 
(direct runoff)
Precipitation 
Volume of water
produced by each cell
(direct runoff)
Cell area
Figure 5.4: Direct runoff produced by each cell
5.1.3 Total discharge
 The total discharge in any cell is equal to the sum of the contributions of all the
cells located upstream of that cell, which is calculated using the Grid flowaccumulation
function with discharge as the weight grid:
 [5.3]
 [5.4]
  80
 ),( gridQFdirgridlationFlowaccumuQQ
t
cells
upstream
tcell
==
?
 where Fdirgrid is the flowdirection grid and Q
t
grid contains the calculated
discharges contributions from each cell.
5.1.4 Discharge computation
 Discharge can be computed directly from the land use coverage by using a
program in Arc Info. The AML used in the computation allows one to compute the direct
runoff, the base flow and the total flow (Procedure 5.1). The fields corresponding to the
runoff coefficients (runcoef, runcoef_bf) are created in the attribute table of the land use
coverage (fin_luse).
 Procedure 5.1: Discharge computation
 /*FUNCTION: compute the base flow, runoff and the total discharge.
 /*INPUTS: land use coverage (fin_luse) with fields for the runoff coefficients (runcoef
and runcoef_bf), flowdirection grid (burn_fdr), precipitation = 31.08 in/yr.
 /*OUTPUTS: direct runoff grid (runoff), base flow grid (baseflow) and total flow grid
(rawflow) in cfs.
 
 /*-----------------------------------------------
 /*BEGIN AML EXECUTION
 grid
 setcell 100
 
 /*Compute the runoff coefficient grids
 runcoef_gr = polygrid ( fin_luse , runcoef )
 bfruncoef_gr = polygrid ( fin_luse , runcoef_bf )
 
 /*Compute the direct runoff and base flow produced by each cell
 runoff_gr = runcoef_gr * 31.08 * 5 / 189216
 baseflow_gr = bfruncoef_gr * 31.08 * 5 / 189216
 kill runcoef_gr all
 kill bfruncoef_gr all
 
 [5.5]
  81
 /*Compute the total direct runoff, base flow and flow
 runoff = flowaccumulation ( burn_fdr , runoff_gr )
 kill runoff_gr all
 baseflow = flowaccumulation ( burn_fdr, baseflow_gr )
 kill baseflow_gr all
 rawflow = runoff + baseflow
 &return
 
 /*--------------- END OF AML ------------
 
 The three output grids, rawflow, runoff and baseflow, contain respectively the
values of the total discharge, direct runoff and base flow for any cell in the grid. The
values at selected locations (e.g. USGS stations in table 5.1) can be obtained by using the
script Qual.Pick in ArcView (section 2.2.3).
 
 Table 5.1: Base flow, direct runoff and total flow at the USGS stations based on
impervious cover/runoff coefficient relationships
 USGS #  Name  Stormflow
 (cfs)
 Baseflow
 (cfs)
 Totalflow
 (cfs)
 8155300  Barton at Loop 360  15.755  44.162  59.917
 8155240  Barton at Lost Creek  12.785  41.103  53.888
 8155200  Barton at SH 71  9.887  34.652  44.539
 8158810  Bear at FM Road 1826  1.538  4.65  6.188
 8158050  Boggy at US183  13.173  1.42  14.593
 8154700  Bull at Loop 360  5.746  7.288  13.034
 8158800  Onion at Buda  17.353  65.366  82.719
 8158700  Onion at Driftwood  12.195  48.545  60.74
 8159000  Onion at US 183  52.522  117.966  170.488
 8156700  Shoal at NW Park  7.194  0.571  7.765
 8156800  Shoal at W 12th  13.373  1.064  14.436
 8158840  Slaughter at FM Road 1826  2.02  2.936  4.956
 8157500  Waller at 23rd  4.997  0.27  5.268
 8157000  Waller at 38th  2.668  0.178  2.846
 8158600  Walnut at Webberville Road  28.68  12.955  41.635
 8158970  Williamson at Jimmy Clay Road  10.073  7.466  17.539
 8158920  Williamson at Oak Hill  1.783  1.948  3.731
  82
5.2 RECHARGE
5.2.1 Difference between recharge and non recharge zones
 Flows are now calculated for the entire study area. However, in-stream losses for
portions of the watersheds that are in the recharge zone of the Edwards Aquifer must be
taken into account. The losses occur only in the recharge zone. However, flow
computations are conducted at the same manner for watersheds located inside and
outside of the recharge zone, by saying that no losses occur outside of the recharge zone.
However, considering losses (even zero losses) increases the number of operations in the
program, it is better to define a simplified program in the case where no recharge zone
has to be considered. Everything described in section 5.2 is then irrelevant and flows
defined by the Procedure 5.1 are used in further computations (section 5.4) as the flows
obtained after losses. The analysis was originally done in Arc/Info and later transferred to
ArcView and programmed in Avenue for ease of use by the City of Austin. The final
Arc/Info program does not consider the no recharge case, since it aims at explaining the
general, more complicated, methodology. However, the Avenue script for flow
computation offers the user the option not to consider a recharge zone (section 8.2).
5.2.2 Recharge losses coefficients
 Portions of the watersheds in this study overlay either the contributing or the
recharge zone of the Edwards Aquifer (only the southern zone is considered since no data
are available for the northern zone). A study of the Edwards aquifer (Barrett and
Charbeneau, 1996) has determined the annual average aquifer recharge values for the
different creeks flowing through the recharge zone as shown in column 2 of Table 5.2.
  83
 Losses to the recharge zone are assumed to occur in the creeks and to be
proportional to the channel length within the recharge zone. Figure 5.5 shows two of the
watersheds which are partially in the recharge zone (Bear and Little Bear).
 .
 
Figure 5.5: Example of watersheds in the recharge zone
 
 Hence, the recharge at any given cell located in a creek within the recharge zone
is obtained by dividing the total recharge occurring in that creek by the total length of the
  84
channel inside the recharge zone, and by multiplying by the length of the channel in that
cell (Eq. 5.6).
 
 
length cell
zone rechargein creek  ofLength 
rechargecreek  Total
cell
cfs
t coefficien Recharge ?=
?
?
?
?
?
?
 
? Channel length in the recharge zone
 
 The channel length inside the recharge zone is defined by selecting the part of
the main creek in the recharge zone. This is because all the recharge is assumed to occur
only in the streams, and therefore is larger per cell than the runoff which is distributed
over the area. For tributaries corresponding to small drainage areas, the total flow
generated is less than the losses to the recharge, and the flow obtained after subtracting
the losses is negative. Considering that losses occur only in the mainstems, the negative
flows are eliminated in such tributaries.
    The cell size is 100 feet. It is assumed that the flow can only go through the
opposite sides or through the diagonal, thus the length will be either 100 ft or 100ft * ?2,
i.e. 141.4ft (Figure 5.6).
 
 
 
 
 
 
 [5.6]
  85
 
 
recharge
zone
Creek
LV2
Figure 5.6: Flow length in the recharge zone
 The creeks are defined by choosing an appropriate threshold value (1,000 cells)
which enables, for the most part, selection of only the main streams which closely
correspond to the actual GIS stream coverages provided by the City. The portion of the
stream network crk1k_gr (section 3.4) within the recharge zone is then selected by using
the function selectpolygon in Arc/Info.
 Grid: lrech_gr = selectpolygon ( crk1k_gr , recharge )
 
 
 The grid is corrected in Arctools so that only the main streams remain, and then
merged with a grid whose cells have for value 0 (0_gr). The zero valued cells indicate
areas that are not streams.
 Grid: 0_gr = con (burn_fdr , 0 )
 Grid: lrech1 = merge ( lrech_gr , 0_gr )
 
 
 c3c47
  86
 Each creek cell is assigned a value corresponding to the length of the channel in
that cell: the value is either 100ft (longitudinal) or 141.4ft (diagonal). That length is
determined by using the flowdirection grid which codes the flow direction (100ft for
value 1, 4, 16, 64 and 141.4ft for 2, 8, 32, and 128, see Figure 3.4).
 Grid: lrech2 = con(crk1k_gr == 1 and (burn_fdr == 1 or burn_fdr == 4 or burn_fdr
== 16 or burn_fdr == 64 ) , 100 , 141.4 )
 
 
 The length grid (lrech2) is then multiplied by the grid with the main streams
(lrech1) in the recharge zone (whose cell value is 1) to create a grid containing main
creek cells in the recharge zone with channel length (lrech).
 Grid: lrech = lrech1 * lrech2
 
 
 Channel length for creeks in the recharge zone is obtained by adding the length
value of each cell for each creek. The sum of the cell lengths within each watershed is
computed with the function zonalsum in Grid.
 Grid: lcount = zonalsum ( coawshd_gr , lrech )
 
 
 This results in a watershed grid whose grid-code is the total channel length of
each creek in the recharge zone. Note that the recharge value for Bear includes the
recharge value for Bear Creek and Little Bear Creek. Hence the total channel length
corresponding to the discharge value for Bear must be the sum of the channel length
computed for Bear and for Little Bear.
 
 
  87
? Recharge coefficients
 The recharge coefficients applied to each watershed are obtained by dividing the
recharge value by the corresponding channel length (Eq. 5.6). The recharge coefficients
are computed in ArcView and written to the field rechcoef (Table 5.2) in the attributes
table of the watershed coverage (coawshd_cv).
        Table 5.2: Recharge coefficients
 Watershed  Recharge
 (cfs)
 Rech_length
 (ft)
 Rechcoef
 (cfs/ft)
 Newrechcoef **
 (cfs/ft)
 Barton  20  37134  5.39E-04  5386
 Bear*  9  83758  1.08E-04  1075
 Onion  31  58156  5.33E-04  5330
 Slaughter  3.5  61333  5.71E-05  571
 Williamson  1.9  57315  3.32E-05  332
       * including Little Bear
       ** newrechcoef = rechcoef * 10
7
 
 
 The recharge coefficient grid is then created from the coverage. The grid
resulting when using the recharge coefficients, which are very small (10
-4
), as grid-code
is a zero valued grid. To avoid this problem, the field newrechcoef containing the
recharge  coefficients multiplied  by 10
7
 are used instead to create the grid.
 Grid: rechcorr_gr = polygrid ( coawshd_cv , newrechcoef )
 
 
 The recharge flow produced by each cell is obtained by multiplying the
correction coefficient grid (rechcorr_gr) by the recharge channel length grid (lrech), and
then dividing by 10
7
.
 Grid: lcorr_rech = lrech * rechcorr_gr / 10000000
 
  88
 An ArcView script allowing the user to create the grid lcorr_rech is currently
developed at CRWR and should be available by December 15, 1997.
5.2.3 Calculating flows with recharge losses
 
 The flowaccumulation program does not handle negative cell values. Since the
recharge occurs only in the streams whereas the flow is generated over the area, the
losses to the recharge zone are bigger than the flow generated, and the flow generated
when considering the losses is negative. Therefore, the total flow in each cell is
calculated first over the entire study area without considering recharge effects. Then, the
recharge is subtracted.
 The total recharge flow at any cell is obtained by summing the recharge for each
cell by using the flowaccumulation function.
 Grid: rech_fac = flowaccumulation ( burn_fdr , lcorr_rech )
 
 
 For each cell, the total flow (flow0) including the losses in the recharge zone is
obtained by subtracting the recharge flow (rech_fac) to the flow computed in section
5.1.4 (rawflow).
 Grid: flow0 = rawflow ? rech_fac
 
 
 The flow lost at a given location in the recharge zone is assumed to have the
same ratio of base flow to total flow as the flow in that cell. It is then possible to
determine the new values for direct runoff and base flow, as well as their respective
volumes lost in the recharge zone. The ratio of base flow to total flow at any location is
  89
obtained by dividing the base flow by the total flow (without considering the effect of the
recharge zone).
 Grid: partbflow = baseflow / rawflow
 
 This grid partbflow is then multiplied with lcorr_rech, which indicates the
recharge flow produced in each cell, to yield the base flow contributing to the recharge
produced in each cell. Summing over all the cells with the flowaccumulation function, a
grid with the total recharge base flow at any cell is obtained. This grid is then subtracted
from the base flow grid previously obtained (which did not consider recharge) to create
the base flow grid (newbaseflow).
 Grid: rechcellbflow = partbflow * lcorr_rech
 Grid: rechbflow = flowaccumulation ( burn_fdr , rechcellbflow )
 Grid: newbaseflow = baseflow ? rechbflow
5.3 FLOW CALIBRATION
 The method presented in the two previous sections is used to compute predictive
flows reflecting empirical relationships (Eq. 5.1.a and 5.1.b) and recharge zones
assumptions. Calibration to observed values is necessary and important to ensure a
realistic simulation for predictive purposes (Figure 5.7).
 
 
 
 
 
 
  90
 
 
 
 
 
 
Figure 5.7: Flow calibration
5.3.1 Observed discharges
 The available observed data is from the USGS sites. Approximately 30 gauging
stations were located within the study area of which only 20 have a period of record that
includes at least one complete year. Moreover, 17 stations have enough information to be
used as references, but only 8 have values for each year of the period of record chosen
(1985-1994), where the year begins on October 1 and ends on September 30 (water year).
Water years were chosen over calendars years because there was more data available
within a water year.
 Missing annual average values were extrapolated from other data, with
consideration given to the relative locations of the basins studied, their areas and their
geological characteristics (e.g. recharge zone of the Edwards Aquifer).
 The period of record was chosen based on a compromise between three factors.
The objective is to be able to predict current and future variations in pollutant loads as a
 MODEL
 Discharge
 Flow Calibration
 Precipitation
 Land use
  91
function of land use, which is a function of impervious cover. Therefore it is necessary to
describe existing conditions as accurately as possible. A compromise must be reached so
that:
? there are enough data
? the period is short enough so that there are no major modifications in land use.
? the period is long enough so that the discharge values are representative.
 Section 5.3.2 describes a procedure for quantifying streamflow variability that
was examined but could not be implemented, since probability characteristics can not be
extrapolated, and is included in the study for documentation purposes.
5.3.2 Average discharge and probabilistic approach
 The average annual value was used for precipitation and discharge. However, the
period of record for the precipitation data is 1948-1993 and 1985-1994 for the discharge
data. Nevertheless, the difference in the average values for both periods was not
significant for precipitation (32.00 inches versus 34.37 inches for 1985-1994).
 It is equally interesting to note the annual variations of the different discharges
since they are directly related to the loads. Flow calibration is important because
concentrations are fixed for a given impervious cover so that the load is directly
proportional to the flow. For the period of record, the predicted loads are either over or
underestimated. For example, the discharge at Barton Creek at Loop 360 varies from
0.14 cfs to 228 cfs (Figure 5.8). During the wet years, predicted pollutant load, using
mean annual flow as input is largely underestimated whereas during the dry years, it is
correspondingly overestimated.
  92
 
 
Year
0
50
100
150
200
250
1980 1982 1984 1986 1988 1990 1992 1994
DAILY-MEAN DISCHARGE FOR
 BARTON CREEK AT LOOP 360 (1980-1994)
D
a
i
l
y
-
m
ean di
s
c
harge (
c
f
s
)
Figure 5.8: Daily mean discharge at Barton Creek at Loop 360 (1980-1994)
 
 The use of a probabilistic approach, which would give a representation of the
variations from the mean would be more realistic than considering only an average value.
The study of the discharge data for a station with a complete record shows that a
lognormal distribution fits the data well (Figures 5.9-5.12). Table 5.3 shows mean and
standard deviation of log
10
Q used in plotting the lognormal distribution figures.
 
  93
 
LOGNORMAL DISTRIBUTION FOR 
BARTON CREEK AT LOOP 360 
(1980-1994)
0.1
1
10
100
1000
-2 -1 0 1 2
Standard normal variable z
Da
i
l
y
-
m
e
a
n di
sc
ha
r
g
e
 (
c
f
s
)
 Lognormal distribution
Data
Figure 5.9: Lognormal distribution for Barton Creek at Loop 360
 
 
LOGNORMAL DISTRIBUTION FOR BEAR CREEK AT FM 
1826
0.1
1
10
100
-2 -1 0 1 2
Standard normal variable z
Da
i
l
y
-
m
e
a
n di
sc
ha
r
g
e
 (
c
f
s
)
Lognormal
distribution
Data
Figure 5.10: Lognormal distribution for Bear Creek at FM 1826
  94
 
LOGNORMAL DISTRIBUTION FOR BULL CREEK AT 
LOOP 360
1
10
100
-2 -1 0 1 2
Standard normal variable z
Da
i
l
y
-
m
e
a
n di
sc
ha
r
g
e
 (
c
f
s
)
Lognormal distribution
Data
Figure 5.11: Lognormal distribution for Bull Creek at Loop 360
 
LOGNORMAL DISTRIBUTION FOR ONION CREEK AT 
US 183
1
10
100
1000
-2 -1 0 1 2
Standard normal variable z
Da
i
l
y
-
m
e
a
n di
sc
ha
r
g
e
 (
c
f
s
)
Lognormal distribution
Data
Figure 5.12: Lognormal distribution for Onion Creek at US 183
  95
          Table 5.3: Mean and standard deviation of log
10
Q
 Station
 Mean (?)  Standard deviation (?)
 Barton Creek at Loop 360  2.86  2.24
 Bear Creek at FM 1826  1.38  1.18
 Bull Creek at Loop 360  2.54  0.76
 Onion Creek at US 183  3.55  1.59
 Onion near Driftwood  3.47  1.34
 Slaughter Creek at FM 1826  0.59  2.17
 Walnut Creek at Webberville road  3.34  0.69
 
 The pollutant load for a given period is defined as the product of the
concentration and the discharge:
 LOAD = Q * C
 Taking the natural logarithm of this expression:
 Ln(Q*C) = Ln(Q) + Ln(C)
 The concentrations C are lognormally distributed, and Ln(C) is normally
distributed. One property of the normal distribution is that the sum of two normal
distributions is a normal distribution, whose mean is the sum of the means and the
variance the sum of the variances.
 
 Mean (?)
 Variance (?
2
)
 Ln(Q*C) = Ln(Q) * Ln(C)
 ?
Q+C
 = ?
Q
 + ?
C
 ?
2
Q+C 
= ?
Q
2
 + ?
C
2
 
 
 The probabilistic lognormal distributions describe the observed discharges well
which are highly variable (2 orders of magnitude). Hence the natural logarithm of the
pollutant load is the sum of two normally distributed variables Ln(Q) and Ln(C), and its
 [5.9.a]
 [5.9.b]
 [5.9.c]
 [5.7]
 [5.8]
  96
distribution can be characterized by applying the relationships presented above.
However, the parameters used to define concentrations and discharges are usually the
median (50% of probability) and the coefficient of variation. Equations 5.9.b and 5.9.c
use the mean and the variance. For a lognormal distribution, the mean and the variance
can be obtained from the median and from the coefficient of variation by using the
following relationships:
 
 Mean = Median * ()1
2
+CV
 CV = 
?
?
 
 However, extrapolating data to complete missing records prohibits the use of a
probabilistic approach. Therefore average values are used, but their high temporal
variability must be kept in mind. The objective is not to determine a value with a great
accuracy but to give comparative, spatial intensive, information on a situation. The use
of average discharges and loadings values is sufficient to meet this objective.
5.3.3 Calibration method
 The discharge values measured at the gauging stations and computed by the
model do not match perfectly; however they are of the same order of magnitude (Table
5.4). The objective of the calibration is to create, through a correction process, a perfect
match at the USGS stations with the average observed flow.
 The assumption underlying the correction process is that the error is uniformly
distributed within each subwatershed: the errors are attributed to the runoff coefficients,
 [5.10.a]
 
 [5.10.b]
  97
both for base flow and for direct runoff. The recharge flow will not be corrected during
the calibration process since it is based on observed values. Only the runoff coefficients
must be multiplied by a correction factor so that the predicted discharges correspond to
the observed ones.
? Comparison with observed data
 The correction coefficient is first determined for the watersheds for which
observed data are available (Figure 5.13).
 
 
Figure 5.13: Calibration zones
 An observed flow value (Q
obs
) is supplied for each USGS watershed outlet,
which is the location of the corresponding USGS station (Table 5.4). This value can be
  98
compared with the predicted discharge value at the same location (Q
pred
). For nested
watersheds, the comparison can be done for the flow generated within each watershed
(Q
zone_obs
 and Q
zone_pred
).
    Table 5.4: Observed and predicted flow at the USGS stations (before flow correction)
 Usgs#  Name  IC
avg
 (%)
 Q
obs
 (cfs)
 Q
pred
 (cfs)
 Q
zone_ob
 (cfs)
 Q
zone_pred
 (cfs)
 8154700  Barton at Loop 360  16.6  60.3  59.9  -6.3  6.0
 8156700  Barton at Lost Creek  9.0  66.6  53.9  12.6  9.3
 8157000  Barton at SH 71  5.8  54.1  44.5  54.1  44.5
 8155200  Bear at FM Road 1826  6.8  6.5  6.2  6.5  6.2
 8157500  Boggy at US183  53.4  9.1  14.6  9.1  14.6
 8158600  Bull at Loop 360  14.4  16.3  13.0  16.3  13.0
 8156800  Onion at Buda  6.2  40.2  82.7  -22.0  22.0
 8155240  Onion at Driftwood  5.1  62.2  60.7  62.2  60.7
 8158050  Onion at US 183  11.0  91.9  170.5  26.9  59.1
 8155300  Shoal at NW Park  58.3  4.7  7.8  4.7  7.8
 8158920  Shoal at W 12th  54.3  7.7  14.4  3.0  6.7
 8158840  Slaughter at FM Road 1826  12.9  5.8  5.0  5.8  5.0
 8158970  Waller at 23rd  63.2  5.2  5.2  2.5  2.4
 8159000  Waller at 38th  58.5  2.6  2.8  2.7  2.8
 8158810  Walnut at Webberville Rd  28.9  35.6  41.6  35.6  41.6
 8158800  Williamson at Oak Hill  16.1  4.7  3.7  4.7  3.7
 8158700  Williamson at Jimmy Clay Rd  22.6  12.5  17.5  7.9  13.8
 
 Negative Q
zone_ob
 indicate that more flow is lost to the recharge zone than
generated by direct runoff and base flow in that zone (e.g. Barton at Loop 360 and Onion
at Buda for which the recharge values are respectively 8.42 cfs and 31 cfs).
 A correction coefficient is defined for each watershed by relating observed and
predicted flow (without considering the recharge) according to the following
relationship:
 Observed flow = Predicted flow * flow correction ? recharge
 
   [5.11]
  99
 In the case of nested watersheds, the incremental flow value must be considered
as it represents the volume generated within the subpart of the watershed. The correction
coefficient is defined as:
 
 
recharge)(without  flow predicted
rechargeflow observed
 correction flow
+
=
 
 The runoff coefficient/impervious cover relationships used can be evaluated by
the study of the correction coefficients. A value of 1 would mean a perfect match, while
values less than 1 (more than 1) shows that the runoff coefficients have been over-
estimated (under-estimated). The values appear to be distributed from 0.348 (over-
estimated) to 1.344 (under-estimated). However, neglecting certain values (shaded rows
in Table 5.5) for stations within the recharge zone and for Waller whose hydrologic
behavior can not be generalized, it appears that there is a link between the flow
correction and the average impervious cover. In the case of nested watersheds, the
average impervious cover is obtained by using the zonalmean function (section 4.4.2).
 
 
 
 
 
 
 
 [5.12]
  100
 
 Table 5.5: Correction coefficients for gauged watersheds
 Name  IC
avg
(%)
 Flow
correction
 Barton at Loop 360  16.6  0.348
 Onion at Buda  6.2  0.409
 Shoal at W 12th  54.3  0.448
 Shoal at NW Park  58.3  0.603
 Boggy at US183  53.4  0.626
 Onion at US 183  11.0  0.667
 Williamson at Jimmy Clay Road  22.6  0.707
 Walnut at Webberville Road  28.9  0.855
 Waller at 38th  58.5  0.933
 Onion at Driftwood  5.1  1.025
 Waller at 23rd  63.2  1.046
 Bear at FM Road 1826  6.8  1.050
 Slaughter at FM Road 1826  12.9  1.168
 Barton at SH 71  5.8  1.214
 Bull at Loop 360  14.4  1.249
 Williamson at Oak Hill  16.1  1.254
 Barton at Lost Creek  9.0  1.344
 
 The points obtained by representing the correction coefficients versus the
watershed-averaged impervious cover fit a linear function. The flow correction is higher
than one for low impervious covers, which means that the runoff coefficients, and the
discharge, have been underestimated. Similarly, the flow correction is less than one for
high impervious covers, which means that the runoff coefficients and the discharge have
been overestimated (Figure 5.14).
 
  101
 
Flow correction coefficients
y = -0.0131x + 1.3015
R
2
 = 0.8169
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1.1
1.2
1.3
1.4
0 102030405060
ic
coef
Coefficient
Linear (Coefficient)
Figure 5.14: Relationship between flow correction and impervious cover
 
 One explanation to this systematic error may be that the impervious cover has
been defined in two different ways:
? The first definition (Environmental and Conservation Services Department) was used
to establish the relationships between impervious cover and other parameters (runoff,
EMC) using data from water quality sampling sites.
? A second definition (Planning and Development Department) was used to relate land
use and impervious cover with maps for the whole city.
 It would be useful in the future if a more consistent measure of impervious cover
were use by the two Departments.
 
  102
? Flow corrections for watersheds without data
 The flow correction coefficients are calculated for watersheds with sufficient
USGS data. Extrapolation is necessary for watersheds without data. The data has shown
that, except for watersheds which have unique characteristics (e.g. recharge zone, Waller
Creek), a linear relationship can be established between the correction coefficient and
impervious cover (Figure 5.14).
      Extrapolated flow correction coefficient = - 0.0131 * IC(%) + 1.3015
 
For high impervious cover, equation 5.13 gives negative values. Because this
relationship was established with average impervious cover over large watersheds, the
average impervious cover is used in this equation. This ensures that negative values do
not occur.
? Generate a correction grid
 A flow correction grid is created which contains:
1. the correction coefficients directly defined for the subwatersheds for which observed
values are available (the downstream end of a watershed in which USGS
subwatersheds are located takes the correction coefficient of the USGS subwatershed
immediately next to him (Figure 5.15).
2.  otherwise use the extrapolated correction coefficients for ungaged areas.
 [5.13]
  103
Figure 5.15: Correction coefficients
Step 1: Apply the extrapolated flow corrections relationship
First an extrapolated flow correction grid is created by applying equation 5.13 to
a grid whose cell value is the correction corresponding to the average impervious cover
of the watershed in which the cell is located. The average impervious cover grid
(icavgwshd) is created with the function zonalmean as shown below in Arc/Info, or by
using the script Qual.Zonalmean in ArcView (section 4.2.2). A correction coefficient is
hence defined for each watershed.
  104
 Grid: icavgwshd = zonalmean ( coawshd_gr , ic_gr )
 Grid: corcoef1 = -0.0131 * icavgwshd + 1.3015
 
Step 2: Downstream end of watersheds with USGS data
The subwatersheds for which no data area available but which are located
downstream of a USGS watershed are assigned the correction calculated for that USGS
watershed. If a correction coefficient has been calculated for a portion of a watershed (i.e.
for Barton, Onion, Waller and Bull), the whole watershed is assigned the correction
coefficient corresponding to the most downstream subwatershed. The procedure which
modifies the correction in Onion is described below. It must be done for each watershed.
 For Onion:
 Grid-code = 36 in coawshd_gr
 Correction coefficient: 0.667
 Grid: corcoef21 = con ( coawshd_gr == 36 , 0.667 , corcoef1 )
 The different flow correction coefficients to use for each watershed are shown in
Table 5.6.
 Table 5.6: Correction coefficients for downstream portions of USGS watersheds
 Watersheds  Coawshd_gr
 grid code
 Coefficient
 Barton  19  0.348
 Boggy  20  0.626
 Bull  3  1.249
 Onion  36  0.667
 Shoal  6  0.448
 Waller  11  1.046
 Walnut  2  0.855
  105
Step 3
The last step is to assign the directly calculated correction values to the USGS
watersheds. The Grid function reclass allows one to use the one to one relationship
between the USGS number and the correction coefficients to create the correction grid
(zone_corr) from the USGS watersheds grid: this grid contains only the USGS
watersheds. Each cell is assigned the correction coefficient associated to the USGS
number (Table 5.7). The function reclass can only handle integers: the coefficients have
first to be multiplied by 1,000 to meet this criterion.
 Grid: zone_corr = reclass ( zones , corrcoef.txt )
 where corrcoef.txt is the file associating USGS number and correction coefficients *
1,000.
 Table 5.7: USGS number/Correction coefficient relationship
 8154700 : 1249
 8155200 : 1214
 8155240 : 1344
 8155300 : 348
 8156700 : 603
 8156800 : 448
 8157000 : 933
 8157500 : 1046
 8158050 : 626
 8158600 : 855
 8158700 : 1025
 8158800 : 409
 8158810 : 1050
 8158840 : 1168
 8158920 : 1254
 8158970 : 707
 8159000 : 667
 
  106
 The resulting grid is multiplied by 10
-3
 to obtain the real coefficients. As the
input grid is an integer grid, dividing by 1,000 would have created an integer grid with 0
or 1 as cell value.
 Grid: zone_corr1 = 0.001 * zone_corr
 Finally this grid is merged on top of the grid obtained at the end of the step 2
(corcoef27).
 Grid: corcoef = merge ( zone_corr1 , corcoef27 )
 This correction coefficient grid is used in all the future discharge and load
computations. The calibrated runoff coefficients for direct runoff and for base flow are
obtained by multiplying a grid with the original runoff coefficients by the correction
coefficient grid corcoef.
5.4 DISCHARGE COMPUTATION
 
 Recharge and flow corrections were determined from observed data. They are
used in the extrapolation process to future conditions assuming that:
? the recharge zone and recharge rate do not vary.
? the land use/impervious cover relationships remain the same.
? the runoff coefficient/impervious cover relationships remain the same.
? the precipitation value used is 31.08 inches/year.
 
 Any variations in these assumptions require modification of the calibration
process. The calibration parameters defined here (recharge and correction coefficients)
  107
are valid only under these assumptions. It is however certain that the relationships will
vary in the future, due in part to the availability of additional data. This means that the
calibration data is necessary at that point.
 Once the calibration has been done, the computation of the discharge from the
impervious cover is straightforward. Either an AML (Procedure 5.2, Flow.aml) or an
Avenue script (Qual.Flow) can be used to do the computation. They are based on the
same principle and differ only by the language used. An AML allows executing the
commands in series automatically, instead of having to type each line in Arc/Info. The
AML also allows one to summarize the process presented here. The language used in the
Avenue script is slightly different. A description of the Avenue script is given in Chapter
8 and Appendix C.
 
 
 
 
 
 
 
 
 
 
 
 
  108
 Procedure 5.2: Discharge computation (with flow corrections)
 /*--------------FLOW.AML --------
 /*-----------------------------------------------
 /*FUNCTION: compute the discharge
 /*INPUT DATA: impervious cover grid (icfut_gr), flowdirection grid (burn_fdr),
correction grid (corcoef), precipitation (31.08 in/yr), recharge grid (rech_fac), recharge
generated in each cell (lcorr_rech)
 /*-----------------------------------------------
 /*BEGIN AML EXECUTION
 
 grid
 setcell 100
 
 /*Compute the runoff coefficients for direct runoff
 runcoef = 0.3428 *icfut_gr * icfut_gr + 0.5677 * icfut_gr + 0.0125
 
 /*Compute the runoff coefficients for base flow (must be positive)
 bflowcoef0 = -0.36 * icfut_gr + 0.1904
 bflowcoef = con ( bflowcoef0 < 0 , 0 , bflowcoef0 )
 kill bflowcoef0 all
 
 
 /*Compute the corrected direct runoff generated by each cell (cfs)
 runcell = runcoef * 31.08 * 5 * corcoef / 189216
 kill runcoef all
 
 /*Compute the corrected base flow generated by each cell (cfs)
 bflowcell = bflowcoef * 31.08 * 5 * corcoef / 189216
 kill bflowcoef all
 
 /*Compute the total direct runoff, base flow and total flow in each cell in cfs (without
considering recharge)
 runoff0 = flowaccumulation (burn_fdr , runcell )
 baseflow0 = flowaccumulation ( burn_fdr , bflowcell )
 totalflow0 = runoff0 + baseflow0
 
 /*Compute the total flow and base flow with the recharge
 flow_pred = totalflow0 - rech_fac
 partbaseflow = baseflow0 / totalflow0
 rechbfcell = lcorr_rech * partbaseflow
 rechbf_fac = flowaccumulation ( burn_fdr , rechbfcell )
 baseflow = baseflow0 - rechbf_fac
 runoff = flow_pred - baseflow
 &return
 /*--------------- END OF AML --------------------
  109
Chapter 6: Load
 Non-point source pollution can be divided into a land (external) and an in-stream
load component. The land load corresponds to the load generated by the water moving
on or through the ground while the in-stream load is the result of channel erosion. The
external load is computed directly by using expected mean concentrations in runoff. The
channel erosion rate is inferred by computing the difference between observed loads and
those predicted using land surface loads alone.
6.1 EXTERNAL LOAD
6.1.1 Event mean concentration
? Definition
 Constituent concentrations associated with each cell are related to the land use.
For each cell, there are two concentration values, one for direct runoff and the other for
base flow. Mean concentrations are computed from storm event data (event mean
concentrations). The event mean concentration for a storm is the total storm load (mass)
divided by the total runoff volume.
 
 EMC C
M
V
== =
?
?
C(t)Q(t) dt
Q(t) dt
 
 [6.1]
  110
 The loading is estimated by multiplying the EMC by the runoff volume. The
actual instantaneous concentrations observed during a storm may be higher or lower than
the EMC. As EMCs vary from storm to storm, a median or 50
th
 percentile is defined to
characterize a site?s EMC. The variability between different sites and events is quantified
by a median and by a coefficient of variation. Table 6.1 shows the relationships used in
this study: they are defined for an impervious cover defined as a decimal fraction
(0<IC<1).
 Table 6.1: Impervious cover/ EMC relationships
 Constituent  Direct runoff
concentration
 (mg/l)*
 Base flow
concentration in
undeveloped areas
 (mg/l)**
 Base flow
concentration in
developed areas
 (mg/l)
 TSS  190  0  0
 BOD  C=14(IC)+3.5  0.45  0.8
 COD  C=98(IC)+18  12  20
 TOC  C=8.6(IC)+8  2  5
 DP  C=0.24(IC)+0.04  0.014  0.06
 TP  C=0.32(IC)+0.19  0.02  0.12
 NH
3
 C=0.24(IC)+0.13  0.02  0.06
 TKN  C=1.53(IC)+0.13  0.28  0.46
 NO
3
 0.82  0.15  0.6
 TN  1.53(IC)+0.95  0.43  1.06
 Cu  C=0.016(IC)+0.006  NA  NA
 Pb  C=0.038(IC)+0.003  NA  NA
 Zn  C=0.19(IC)  NA  NA
 * Zero EMCs are associated with water land use.
 **Areas with an impervious cover less than 15% are considered undeveloped.
 IC Impervious Cover expressed as a decimal fraction (0<IC<1).
 
 These relationships are defined in the report ?Water Quality and Quantity Inputs
for the Urban Creeks Future Needs Assessment?, by Michael E. Barrett (July 1997). The
values for Total Nitrogen correspond to the sum of the EMCs for TKN and NO
3
.
 
  111
? EMC grids
 Using the relationships in Table 6.1, the EMC grids for direct runoff and base
flow can be created by either of two ways.
 
(a) Starting with a land use or traffic serial zone coverage
The EMC field for each constituent is computed in the land use coverage
attribute table by creating an EMC field for each constituent and applying the IC/EMC
relationships from Table 6.1. It is necessary to use parentheses when typing the equations
since ArcView does the computation from left to right. There is no priority given to
multiplication over addition. For example, the expression a+b*c is computed in ArcView
as (a+b)*c instead of a+(b*c), as normally dictated by mathematical rules.
 The 100% impervious cover associated with water yields high EMCs values for the
water land use. As rainfall contributes directly to the water body, zero EMCs should be
associated with water. The EMCs obtained by applying the relationships shown in Table
6.1 must be corrected for the water land use. The records whose EMCs must be set to
zero must be selected in the attribute table. For current conditions, water corresponds to
the land use code 940 (newlandusecode = 940). For future conditions, water zones are
represented by the traffic serial zones 999 (tsz = 999). The function polygrid is used to
create the EMC grids for direct runoff and base flow by using the corresponding fields in
the attribute table (e.g. bod_emc for BOD direct runoff EMCs and bod_emcbf for BOD
base flow EMCs).
 Grid: setcell 100 (set the cell size to 100ft)
 Grid: emc_gr = polygrid ( finluse , bod_emc )
 Grid: emcbf_gr = polygrid ( finluse , bod_emcbf )
  112
(b) Starting with an impervious cover grid
The other possibility is to start with an impervious cover grid created with the
command polygrid from the land use coverage. The IC/EMC relationships in Table 6.1
are applied to that grid in order to create EMC grids. The EMCs in the water zones must
be set to zero. For future conditions, these zones are characterized by the grid-code 999
(traffic serial zone number) in the traffic serial zones grid zone_gr.
 Build the traffic serial zones grid
 Grid: zone_gr = polygrid ( zones , tsz )
 
 Apply the IC/EMC relationship to the impervious cover grid icfut_gr (e.g. BOD)
 Direct runoff
 Grid: emc_gr0 = 14 * icfut_gr + 3.5
 Base flow
 Grid: emcbf_gr0 =  con ( icfut_gr <= 0.15 , 0.45 , 0.8 )
 
 Correct the water zones
 Grid: emc_gr = con ( zone_gr == 999 , 0 , emc_gr0 )
 Grid: kill emc_gr0 all
 Grid: emcbf_gr = con ( zone_gr == 999 , 0 , emcbf_gr0 )
 Grid: kill emcbf_gr0 all
6.1.2 Load computation method
? Load produced by each cell
 The calibrated discharge and concentration grids for direct runoff and base flow are
multiplied together to generate the direct runoff (Figure 6.1) and base flow loads
produced in each cell. The total load produced in each cell is obtained by adding the
contributions of base flow and direct runoff.
 
 
  113
? Load produced by direct runoff
Load
r
 (kg/year) = EMC(mg/l) * Q
r 
(cfs) * (3.048)
3
(l/ft
3
) * 86400(s/d) * 365(d/yr)
* 10
-6
(kg/mg)
 Grid: loadcell = emc_gr * runcell * 3.048 * 3.048 * 3.048 * 86400 * 365 / 1000000
? Load produced by baseflow
Load
bf 
(kg/year) = EMC
bf
(mg/l) * Q
bf
(cfs) * (3.048)
3
(l/ft
3
) * 86400(s/d) * 365(d/yr)
* 10
-6
 (kg/mg)
 Grid: loadcellbf = emcbf_gr * bflowcell * 3.048 * 3.048 * 3.048 * 86400 * 365 /
1000000
? Total load
Load
t
 (kg/year) = Load
r 
+ Load
bf
 Grid: tloadcell = loadcell + loadcellbf
EMC
(direct runoff) 
Load produced
 by each cell
(direct runoff)
Volume of water 
produced by each cell
(direct runoff)
Figure 6.1: Load produced by each cell (e.g. direct runoff)
 
 
  114
? Total load (without recharge)
 The total load in any cell is obtained by summing the load contribution of all
cells located within the drainage area upstream of the given cell. This procedure is
similar to the discharge computation which uses a weighted flowaccumulation in
Arc/Info Grid.
 Grid: load0 = flowaccumulation ( burn_fdr , tloadcell )
? Recharge load
 Like the difference between the flow generated and lost in the cells located in the
creeks within the recharge zone, the difference between the load generated and lost can
be negative. The problem lies in the fact that the flowaccumulation function cannot
handle negative values. If the grid is entirely negative, the solution is to take its absolute
value and then run the flowaccumulation function and take its negative value. However,
for this research both positive and negative load values are found in the grid. The load
lost in the recharge zone must be computed separately and subtracted from the total load.
 Concentrations are obtained by dividing load by flow. The concentrations in the
water lost in a cell in the recharge zone are assumed to be the same as the concentrations
in the creek at the cell where the recharge occurs. They are the same as the
concentrations in the creek without considering the recharge zone (co), which are
obtained by dividing the total load (load0) by the total flow (totalflow0). The load lost in
each cell of the recharge zone is the product of this concentration and the volume of flow
lost in the cells within the recharge zone (lcorr_rech). The flowaccumulation function is
then used to add the contribution of all the cells to recharge load losses.
  115
 Grid: co = load0 / totalflow0
 Grid: loadcellrech = lcorr_rech * co
 Grid: loadrech = flowaccumulation ( burn_fdr , loadcellrech )
 
 The load lost to the recharge zone is finally subtracted from the total load
previously computed (load0) to obtain the external load (newload).
 Grid: load = load0 - loadrech
? Load computation
 The different steps presented above can be gathered in a program, either in
Arc/Info or ArcView (chapter8). The AML shown below (procedure 6.1) allows the user
to compute the external load directly from an impervious cover grid once the discharge
has been computed. This AML is an example of the load computation for BOD. It must
be edited for each constituent.
 
 Procedure 6.1: Load computation
 /* ----------------------------------------------
 /*-----------------------------------------------
 /*-------------- LOAD.AML ----------------
 *------------------------------------------------
 /*-----------------------------------------------
 /*FUNCTION: compute the load given an impervious cover and a runoff coefficient
coverages.
 /*INPUT GRIDS: impervious cover (icfut_gr, 0<IC<1), traffic serial zones (zone_gr),
direct runoff (runcell) and base flow (bflowcell) generated in each cell (in cfs),
flowdirection (burn_fdr), total flow without recharge (totalflow0), recharge lost in each
cell (lcorr_rech).
 
 /*-----------------------------------------------
 /*BEGIN AML EXECUTION
 
 grid
 setcell 100
 
 /*Compute the EMC for direct runoff and base flow
 emc_gr0 = 14 * icfut_gr + 3.5
  116
 emc_gr = con ( zone_gr == 999 , 0 , emc_gr0 )
 kill emc_gr0 all
 emcbf_gr0 =  con ( icfut_gr <= 0.15 , 0.45 , 0.8 )
 emcbf_gr = con ( zone_gr == 999 , 0 , emcbf_gr0 )
 kill emcbf_gr0 all
 
 /*Compute the load produced by each cell
 loadcell = runcell * emc_gr * 3.048 * 3.048 * 3.048 * 86400 * 365 / 1000000
 loadcellbf = bflowcell * emcbf_gr * 3.048 * 3.048 * 3.048 * 86400 * 365 / 1000000
 tloadcell = loadcell + loadcellbf
 kill loadcell all
 kill loadcellbf all
 
 
 /*Compute the total load (without considering the recharge zone)
 load0 = flowaccumulation ( burn_fdr , tloadcell )
 kill tloadcell all
 
 /*Compute the recharge load
 BOD_co = load0 / totalflow0
 loadcellrech = lcorr_rech * BOD_co
 loadrech = flowaccumulation ( burn_fdr , loadcellrech )
 kill loadcellrech all
 
 
 /*Compute the total load
 BOD_load = load0 - loadrech
 kill load0 all
 kill loadrech all
 
 &return
 /*--------------- END OF AML --------------------
 
? Measured versus predicted values
Concentration
 The predicted land surface loads are divided by the predicted discharges,
converted to concentrations in mg/l, and compared with the concentrations measured at
  117
the USGS stations (Figures 6.2.a-6.2.j). No measured concentrations are available for
copper (Cu), lead (Pb) and zinc (Zn).
 
]/[365*]/[86400*])/[048.3(* [cfs] Flow Predicted
 ]/[10* [kg/yr] Load Predicted
  [mg/l]ion concentrat Predicted
3
6
yrddsftl
kgmg
=
 
 The graphs show that the predicted values for BOD (6.2.a), COD (6.2.c), DP
(6.2.e), NH
3
 (6.2.i) and NO3 (6.2.j) match well the measured ones. The concentrations
for TOC (6.2.b), TP (6.2.d), TSS (6.2.f), TKN (6.2.g) and TN (6.2.h) appear however
constantly underestimated.
Load
The study deals more with loads than with concentration. "Measured" loads can
be estimated by multiplying the measured concentrations by the predicted flows. Even
though they are not really measured loads, these loads are used to evaluate the predicted
loads. Since the discharge value varies for each station, the graphs comparing the loads
(Figures 6.3.a-6.3.j) do not look exactly the same as the graphs comparing the
concentrations. The general trend is the same however: TOC, TP, TSS, TKN and TN are
underestimated.
 [6.2]
  118
 
BOD
0
4
8
12
16
20
048121620
Measured concentrations [mg/l]
P
r
ed
ict
e
d
 co
n
cen
t
r
at
io
n
s
 [
m
g
/l]
 Figure 6.2.a
 
COD
0
20
40
60
80
100
0 2040608010
Measured concentrations [mg/l]
Pr
ed
ict
e
d
 co
n
cen
t
r
at
io
n
s
 [
m
g
/l]
 Figure 6.2.c
 
DP
0
0.1
0.2
0.3
0.4
0.0 0.1 0.2 0.3 0.4
Measured concentrations [mg/l]
P
r
ed
i
c
t
e
d
 co
n
cen
t
r
at
i
o
n
s
 [
m
g
/
l
]
 Figure 6.2.e
 
 
TOC
0
10
20
30
40
50
0 1020304050
Measured concentrations [mg/l]
P
r
ed
ict
e
d
 co
n
cen
t
r
at
io
n
s
 [
m
g
/l]
 Figure 6.2.b
 
TP
0.0
0.5
1.0
1.5
2.0
0.0 0.5 1.0 1.5 2.0
Measured concentrations [mg/l]
P
r
ed
i
c
t
e
d
 co
n
cen
t
r
at
i
o
n
s
 [
m
g
/
l
]
 Figure 6.2.d
 
TSS
0
500
1000
1500
2000
0 500 1000 1500 2000
Measured concentrations [mg/l]
P
r
ed
i
c
t
e
d
 co
n
cen
t
r
at
i
o
n
s
 [
m
g
/
l
]
 Figure 6.2.f
  119
 
TKN
0
0.5
1
1.5
2
2.5
3
3.5
4
0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0
Measured concentrations [mg/l]
Pr
ed
i
c
t
e
d
 co
n
cen
t
r
at
i
o
n
s
 [
m
g
/
l
]
 Figure 6.2.g
 
NH3
0
0.1
0.2
0.3
0.4
0.00.10.20.30.4
Measured concentrations [mg/l]
P
r
ed
ict
e
d
 co
n
cen
t
r
at
io
n
s
 [
m
g
/l]
 Figure 6.2.i
 
TN
0
1
2
3
4
5
012345
Measured concentrations [mg/l]
P
r
ed
i
c
t
e
d
 co
n
cen
t
r
at
i
o
n
s
 [
m
g
/
l
]
 Figure 6.2.h
 
NO3
0
0.2
0.4
0.6
0.8
1
0.0 0.2 0.4 0.6 0.8 1.0
Measured concentrations [mg/l]
P
r
ed
i
c
t
e
d
 co
n
cen
t
r
at
i
o
n
s
 [
m
g
/
l
]
Figure 6.2.j
Figures 6.2: Comparison between measured and predicted concentrations at the USGS
stations
 
 
  120
 
BOD
0.0E+00
5.0E+04
1.0E+05
1.5E+05
2.0E+05
2.5E+05
3.0E+05
0.0E+00 5.0E+04 1.0E+05 1.5E+05 2.0E+05 2.5E+05
Measured load [kg/yr]
Pr
ed
i
c
ted
 l
o
ad
 [kg
/
yr
]
Figure 6.3.a
 
COD
0.0E+00
5.0E+05
1.0E+06
1.5E+06
2.0E+06
0.0E+00 5.0E+05 1.0E+06 1.5E+06 2.0E+06
Measured load [kg/yr]
P
r
ed
ict
e
d
 lo
ad
 [
k
g
/
yr
]
Figure 6.3.c
 
DP
0
1000
2000
3000
4000
5000
0 1000 2000 3000 4000 5000
Measured load [kg/yr]
Pr
ed
i
c
ted
 l
o
ad
 [kg
/
yr
]
Figure 6.3.e
 
TOC 
0.E+00
2.E+05
4.E+05
6.E+05
8.E+05
1.E+06
0.E+00 2.E+05 4.E+05 6.E+05 8.E+05 1.E+06
Measured load [kg/yr]
P
r
e
d
i
c
te
d l
o
a
d
 +
 E
r
os
i
on [k
g/
y
r
]
 Figure 6.3.b
 
TP
0
2500
5000
7500
10000
12500
15000
0 2500 5000 7500 10000 12500 15000
Measured load [kg/yr]
P
r
ed
ict
e
d
 lo
ad
 [
k
g
/
yr
]
 Figure 6.3.d
 
TSS
0.E+00
1.E+07
2.E+07
3.E+07
4.E+07
0.E+00 1.E+07 2.E+07 3.E+07 4.E+07
Measured load [kg/yr]
Pr
ed
i
c
ted
 l
o
ad
 [kg
/
yr
]
 Figure 6.3.f
 
 
  121
 
TKN
0.E+00
1.E+04
2.E+04
3.E+04
4.E+04
5.E+04
6.E+04
0.E+00 1.E+04 2.E+04 3.E+04 4.E+04 5.E+04 6.E+04
Measured load [kg/yr]
P
r
ed
ict
e
d
 lo
ad
 [
k
g
/
yr]
 Figure 6.3.g
 
NH3
0
1000
2000
3000
4000
5000
6000
7000
0 1000 2000 3000 4000 5000 6000 7000
Measured load [kg/yr]
P
r
ed
ict
e
d
 lo
ad
 [
k
g
/
yr
]
 Figure 6.3.i
 
TN
0.E+00
2.E+04
4.E+04
6.E+04
8.E+04
0.E+00 2.E+04 4.E+04 6.E+04 8.E+04
Measured load [kg/yr]
P
r
ed
ict
e
d
 lo
ad
 [
k
g
/
yr
]
 Figure 6.3.h
 
NO3
0
5000
10000
15000
20000
25000
0 5000 10000 15000 20000 25000
Measured load [kg/yr]
P
r
ed
ict
e
d
 lo
ad
 [
k
g
/
yr
]
 Figure 6.3.j
 
 Figures 6.3: Comparison between measured and predicted loads at the USGS stations
 
 Predicted loads are underestimated because they do not take into account the in-
stream loads due to erosion which can be very important (e.g. TSS).
  122
6.2 CHANNEL EROSION
6.2.1 Model
 The second component of non-point source pollution is the in-stream channel
erosion, which is difficult to evaluate directly: it is computed as the difference between
the "measured" and the predicted loads. The effect of the current Best Management
Practices on the loads is assumed to be negligible compared with the uncertainties in
other data (e.g. impervious cover). The effects of current BMPs are not taken into
account in the erosion computation.
 Erosion happens in and aroundthe channel. An erosion coefficient, representing
the load eroded by length of channel can be defined for each watershed where measured
data are available. This coefficient is defined as:
 
? Channel definition
 It is necessary to define the channel where in-stream erosion occurs. There are
two alternatives. The first one is to consider that the channels correspond to the digitized
creeks. The second consists of choosing a flowaccumulation threshold: any cell whose
drainage area is bigger than the threshold value is located in a channel. The problem
however is to define the threshold.
 As the digitized creeks are the result of field observation, they should give a
good representation of the channels. It is not possible to find a flowaccumulation
threshold value for which all delineated creeks correspond to the digitized creeks. The
 
station  theof upstreamlength  channel
load) predicted- load (observed
=ft]-[kg/yrt coefficienErosion 
station at the
 [6.3]
  123
channel length is hence based on the digitized creeks. The channel length is computed by
using the flowdirection grid: a length value related to the direction of the flow is
associated with each cell (section 5.2). The delineated creeks, which are based on the
flowdirection grid, do not correspond exactly to the digitized creeks. Note that the
channel length at any location is hence slightly different from the length which would
have been defined by using the delineated creeks derived from the digital elevation
model.
6.2.2 Erosion coefficients
 An erosion coefficient is defined for each USGS watershed for which data are
available. Erosion is caused by the in-stream flow, which is based on the average
impervious cover. Linear relationships between erosion coefficient and average
impervious cover were hence defined to extrapolate the erosion to the watersheds with no
observed data. Erosion is considered only for the constituents whose predicted load was
underestimated:
? Total Organic Carbon (Table 6.2, Figure 6.4)
? Total Nitrogen (Table 6.3, Figure 6.5, erosion for TKN is not considered)
? Total Phosphorus (Table 6.4, Figure 6.6)
? Total Suspended Solids (Table 6.5, Figure 6.7)
  124
 Total Organic Carbon
   Table 6.2: TOC erosion coefficients
 USGS Station  Channel
length
 Discharge  TOC obs  TOC pred  Erosion  IC
   ft  cfs  kg/yr  kg/yr  kg/yr.ft  %
 Barton at Loop 360  641015  60.3  818933  206397  0.96  16.6
 Barton at Lost Creek  577037  66.6  472801  220249  0.44  9
 Barton at SH 71  455497  54.1  378424  168903  0.46  5.8
 Boggy at US183  110232  9.1  343657  107744  2.14  53.4
 Bull at Loop 360  117563  16.3  320911  89223  1.97  14.4
 Shoal at W 12th  52248  7.7  241999  91528  2.88  54.3
 Walnut at Webberville rd  287253  35.6  496217  313209  0.64  28.9
 Williamson at Oak Hill  32454  4.7  85207  27647  1.77  16.1
TOC Erosion vs. Impervious Cover
y = 0.0348x + 0.5444
R
2
 = 0.5354
0
0.5
1
1.5
2
2.5
3
3.5
102030405060
IC (%)
(
O
bs
e
r
v
e
d
 loa
d -
 Pr
e
dic
t
e
d loa
d)
 / 
U
p
st
r
eam ch
an
n
e
l
 l
e
n
g
t
h
 [
k
g
/
y
r
.
f
t
]
Figure 6.4: TOC erosion vs. impervious cover
 
 
  125
 
 
 Total Nitrogen
   Table 6.3: TN erosion coefficients
 USGS Station  Channel
length
 Discharge  TN obs  TN pred  Erosion  IC
   ft  cfs  kg/yr  kg/yr  kg/yr.ft  %
 Barton at Loop 360  641015  60.3  72649  34549  5.94E-02  16.6
 Barton at Lost Creek  577037  66.6  39147  36677  4.28E-03  9
 Barton at SH 71  455497  54.1  34180  28487  1.25E-02  5.8
 Boggy at US183  110232  9.1  33465  15860  1.60E-01  53.4
 Bull at Loop 360  117563  16.3  29129  13522  1.33E-01  14.4
 Shoal at W 12th  52248  7.7  26404  13479  2.47E-01  54.3
 Walnut at Webberville rd  287253  35.6  68894  46604  7.76E-02  28.9
 Williamson at Oak Hill  32454  4.7  9851  4169  1.75E-01  16.1
 
TN Erosion vs. Impervious Cover
y = 0.0033x + 0.0267
R
2
 = 0.5557
0
0.05
0.1
0.15
0.2
0.25
0.3
102030405060
IC (%)
(
O
b
ser
ved
 l
o
ad
 -
 Pr
ed
i
c
t
e
d
 l
o
ad
)
 /
 U
p
st
r
e
a
m
c
h
a
nne
l
 l
e
ngt
h [
k
g/
y
r
.
f
t
]
Figure 6.5: TN erosion vs. impervious cover
 
  126
 
 Total Phosphorus
   Table 6.4: TP erosion coefficients
 USGS Station  Channel
length
 Discharge  TP obs  TP pred  Erosion  IC
   ft  cfs  kg/yr  kg/yr  kg/yr.ft  %
 Barton at Loop 360  641015  60.3  5710  4205  2.35E-03  16.6
 Barton at Lost Creek  577037  66.6  4166  4393  -3.94E-04  9
 Barton at SH 71  455497  54.1  2615  3257  -1.41E-03  5.8
 Boggy at US183  110232  9.1  12982  3186  8.89E-02  53.4
 Bull at Loop 360  117563  16.3  2375  2179  1.66E-03  14.4
 Shoal at W 12th  52248  7.7  7368  2719  8.90E-02  54.3
 Walnut at Webberville rd  287253  35.6  13963  8814  1.79E-02  28.9
 Williamson at Oak Hill  32454  4.7  1966  695  3.92E-02  16.1
TP Erosion vs. Impervious Cover
y = 0.0019x - 0.0177
R
2
 = 0.8757
-0.02
0
0.02
0.04
0.06
0.08
0.1
102030405060
IC (%)
(O
b
served
 l
o
ad
 - P
r
ed
i
c
ted
 l
o
ad
) /
 
Ups
t
r
e
a
m
 c
h
a
nne
l
 l
e
ngt
h [
k
g/
y
r
.
f
t
]
Figure 6.6: TP erosion vs. impervious cover
  127
 Note that for low impervious covers the relationship yields a negative erosion
(e.g. Barton).
 
 Total Suspended Solids
   Table 6.5: TSS erosion coefficients
 USGS Station  Channel
length
 Discharge  TSS obs  TSS pred  Erosion  IC
   ft  cfs  kg/yr  kg/yr  kg/yr.ft  %
 Barton at Loop 360  641015  60.3  3.07E+07  2.53E+06  44  16.6
 Barton at Lost Creek  577037  66.6  1.03E+07  2.69E+06  13  9
 Barton at SH 71  455497  54.1  1.27E+07  2.03E+06  23  5.8
 Boggy at US183  110232  9.1  1.45E+07  1.40E+06  119  53.4
 Bull at Loop 360  117563  16.3  1.68E+07  1.22E+06  132  14.4
 Shoal at W 12th  52248  7.7  9.63E+06  1.21E+06  161  54.3
 Walnut at Webberville rd  287253  35.6  3.20E+07  4.16E+06  97  28.9
 Williamson at Oak Hill  32454  4.7  1.73E+06  3.77E+05  42  16.1
TSS Erosion vs. Impervious Cover
y = 2.2629x + 22.836
R
2
 = 0.6083
0
20
40
60
80
100
120
140
160
180
102030405060
IC (%)
(
O
b
ser
ved
 lo
ad
 -
 P
r
ed
ict
e
d
 L
o
a
d
 )
 / 
U
p
st
r
eam ch
an
n
e
l len
g
t
h
Figure 6.7: TSS erosion vs. impervious cover
  128
 The relationships between erosion and average impervious cover are summerized
in table 6.6.
   Table 6.6: Erosion relationships
 Constituent  Equation  R
2
 TSS  y = 2.2629 * IC(%) + 22.836  0.61
 TN  y = 0.0033 * IC(%) + 0.0267  0.56
 TOC  y = 0.0348 * IC(%) + 0.5444  0.54
 TP  y = 0.0019 *IC(%) - 0.0177  0.88
6.3 CONSTRUCTION LOAD
 The construction load is computed in a slightly different way. This load is
generated during the construction period on all vacant land areas. The first step consists
of locating these areas.
6.3.1 Zones to be developed
 Newly developed areas are defined as the zones where the land use goes from
undeveloped under current conditions to developed for future conditions. The percentage
of area within each traffic serial zone which is going to be developed is determined as the
difference between the current and the future average undeveloped land use percentage
for each zone. The current undeveloped conditions can be determined by averaging the
land use distribution over the cells within the various traffic serial zones. The principle is
to attribute the value 1 to all the cells corresponding to the undeveloped land use and 0 to
the others. The average value of the cells over the traffic serial zones gives the average
undeveloped land use percentage for each zone. This value can be computed in Arc/Info
  129
with the function zonalmean (as shown below) or in ArcView with the script
Qual.Average.
 When creating the grid for the undeveloped land use (value 0 or 1), it is
important to select the cells from a grid containing all land uses. If this grid is directly
built from the land use coverage, one cell may be attributed several land uses. This can
be verified by creating several grids corresponding to the different land uses and adding
their percentage: the total values will be more than 100%, especially in small zones. This
error comes from the discretization process which converts a coverage to a grid. By
selecting the land uses from a grid, each cell can be only attributed the dominant land use
in that cell (Figure 6.8).
 
 
 
 
 
 
 
 
 
 
Figure 6.8: Error in conversion from vector to grid
 The land use grid is based on the newcode field of the current land use coverage.
 2 values for
the same cell
  130
 Grid: luse_gr = polygrid ( finluse , newcode )
 The cells corresponding to undeveloped (land use code 900) are then selected.
 Grid: undev_gr = con ( luse_gr == 900 , 1 , 0 )
 The cell value is finally averaged over each Traffic Serial Zone.
 Grid: undev_avg = zonalmean ( zone , undev_gr )
 
 Any cell of this grid gives the average percentage of the area within the
corresponding traffic serial zone designated as current undeveloped land use. The future
undeveloped percentage is obtained directly in the table characterizing the traffic serial
zones since it is one of the parameter for which predictions were made under future
conditions by the City of Austin?s Planning Department. The difference between these
two values gives the percentage of each traffic serial zone which is going to be
developed.
 The exact distribution of the part of the zones to be developed is not known. The
assumption made to solve this problem is that considering that a given percentage of the
total area is going to be totally developed is the same as considering that the whole area
will be partially developed (Figure 6.9).
 
 
 
 
 
 
  131
 
 
 
 
 
 
Figure 6.9: Assumption for percentage of development
 A grid (buildup) containing the ratio of development in each cell is created.
6.3.2 CONSTRUCTION LOAD COMPUTATION
 Construction load is only computed for total suspended solids (TSS). The City of
Austin supplied a TSS EMC of 600mg/l, i.e. more than three times the value used in the
study (190 mg/l), and an average runoff coefficient of 0.5 to use in the construction load
computation. This runoff coefficient corresponds to an impervious cover of 62%. The
discharge and the load produced by each cell are first defined, and then the
flowaccumulation function allows one to compute the total construction load (tss_b). The
units of this load are kg/number of years of construction. In this case, the construction
period chosen is 45 years, hence the annual load is obtained by dividing this load by 45.
 Grid: flow_b = buildup * 0.5 * 31.08 * 5 / 189216
 Grid: tss = flow_b * 600 * 3.048 * 3.048 * 3.048 * 86400 * 365 / 100000
 Grid: tss_b = flowaccumulation ( burn_fdr , tss )
 
 x % of the area has
a development
amount of 100%
 100 % of the area
has a development
amount of x%
  132
 Table 6.7 shows a comparison between current loads and construction loads both
expressed in kg/yr. Constructions are not important in urban watersheds, which are
already developed. Therefore construction loads for these watersheds are less than
current loads (Waller, Shoal, Boggy). On the other hand, the currently mostly
undeveloped watersheds (Onion, Bear, Barton, Slaughter and Williamson) are going to
be developed: construction loads are bigger than current loads for these watersheds.
 Table 6.7: Comparison between current loads and construction loads for TSS
 Usgs#  Name  Construction
load
 Current load  Construction load
/ Current load
  kg/yr  kg/yr  
 8157500  Waller at 23rd  7.63E+02  8.35E+05  0.04
 8157000  Waller at 38th  5.65E+02  4.22E+05  0.06
 8156800  Shoal at W 12th  8.25E+03  1.21E+06  0.31
 8156700  Shoal at NW Park  7.13E+03  7.36E+05  0.44
 8158050  Boggy at US183  2.13E+04  1.40E+06  0.69
 8158600  Walnut at Webberville Road  2.68E+05  4.16E+06  2.89
 8154700  Bull at Loop 360  8.27E+04  1.22E+06  3.06
 8158970  Williamson at Jimmy Clay
Road
 1.06E+05  1.23E+06  3.88
 8158920  Williamson at Oak Hill  3.31E+04  3.77E+05  3.94
 8158840  Slaughter at FM Road 1826  6.29E+04  4.00E+05  7.08
 8155240  Barton at Lost Creek  5.02E+05  2.69E+06  8.39
 8155300  Barton at Loop 360  5.28E+05  2.53E+06  9.41
 8155200  Barton at SH 71  4.55E+05  2.03E+06  10.06
 8158810  Bear at FM Road 1826  7.95E+04  2.74E+05  13.06
 8158700  Onion at Driftwood  6.60E+05  2.11E+06  14.05
 8159000  Onion at US 183  2.03E+06  5.16E+06  17.73
 8158800  Onion at Buda  9.32E+05  1.41E+06  29.68
 
 External loads have been computed based on impervious cover/event mean
concentration relationships. In-stream erosion has been defined from the difference
between observed loads and predicted external loads. Construction loads have also been
computed.
  133
Chapter 7 Best Management Practices
 To reduce non-point source pollution loading, the City of Austin uses Best
Management Practices (BMPs) such as ponds or sand filters. The objective of this project
is to study the effectiveness of existing and planned BMPs. The action of the BMPs is
modeled by two different ways, depending whether the BMP?s location is known.
7.1 LOCATED BMPS
 Located BMPs are defined by a point in a point coverage and by their effect on
the load, defined either by load removed or by efficiency. It is easier to model the BMPs
defined by load removed than by efficiency since, in the second case, the load removed
depends on the value of the incoming load. The located BMPs in this study were defined
by load removed. The second approach was also developed and is explained in section
7.1.2.
7.1.1 Effects of BMPs defined by load removed
 The City of Austin staff has compiled the loads removed of different constituents
at the located BMPs and has created point coverages corresponding to their location by
geocoding (Figure 7.1). Two types of BMPs (residential city1, commercial com1pd27)
are considered for current conditions and three types (residential cityf1, commercial
com1pd27 and retrofit future1) for future conditions. The point coverages to use for
residential and commercial BMPs are the same for both conditions. The loads removed
by commercial BMPs remain between current and future conditions; thus the model is
  134
run only once for this coverage. However, loads removed from residential BMPs increase
between current and future conditions and the model must be run for each scenario. 361
BMPs are represented in Figure 7.1: 121 residential, 229 commercial and 11 retrofit.
 
 
 
Figure 7.1: Located Best Management Practices
 
  135
 The total load removed by the BMPs upstream of any cell is determined by
doing a weighted flowaccumulation on a grid which has for values the loads removed at
the BMPs and no data elsewhere (Figure 7.2). Each type of BMP is studied separately to
obtain the effect of each category. However, if the objective is to get the total load
removed, the BMPs can all be modeled together by using a unique point coverage.
 The City of Austin supplied tables containing the loads removed associated with
each BMP category. These tables were saved as .dbf files and added in ArcView. The
one to one relationship existing between the records in these tables and in the
corresponding BMPs coverages attributes table allows one to join the tables together,
using the script Qual.Join in ArcView (section 2.4.2). Once the tables have been edited,
the grids corresponding to the point coverage are created so that the cell value at the
BMPs is equal to the mass of constituent removed.
 
 
BMP grid Removed load grid
cell size
BMP
i
Load
i
BMP
I+1
Load
I+1
Load
I
Load
I 
+ Load
I+1
Weighted
Flowaccumulation
Figure 7.2: Computation for located BMPs defined by load removed
  136
? Analysis using Arc/Info
 For example, considering the point coverage city1 (residential for current
conditions) and the field tss, which indicate the TSS load removed, the procedure is:
 Create a grid point coverage
 Grid: tss_pt = pointgrid ( city1 , tss )
 
 Sum the loads removed
 Grid: tss_cc = flowaccumulation ( burn_fdr , tss_pt )
 
 Since the flowaccumulation function does not handle negative values, if the grid
contains both negative and positive values (e.g. for NO
3
), two positive grids must be
created. The first one contains the cells with positive values. The second one contains the
absolute values of the cells with negative values. A flowaccumulation is done for each
grid and the second grid is subtracted from the first one.
 Grid: no3_pt = pointgrid ( city1 , no3 )
 Grid: no3_ptp = con ( no3_pt > 0 , no3_pt )
 Grid: no3_ptn = con ( no3_pt <= 0 , - no3_pt )
 Grid: no3_ccp = flowaccumulation ( burn_fdr , no3_ptp )
 Grid: no3_ccn = flowaccumulation ( burn_fdr , no3_ptp )
 Grid: no3_cc = no3_ccp - no3_ccn
? Analysis using ArcView
 The BMPs can also be modeled in ArcView. The script Qual.BMPload (section
8.4.1 and Appendix C) used to model the BMPs is also based on the principle developed
in this section.
  137
7.1.2 Effects of BMPs defined by efficiency
 BMPs are usually defined by their removal efficiency, i.e. the percentage of the
incoming load which is removed. Although the BMPs used in this study are defined by
the mass removed, a procedure in the case where they are defined by the removal
efficiency is created. This approach is more complicated because the mass of load
removed now depends on both the BMP efficiency and the incoming load.
 
Initial load upstream of the BMP
           New load =
(Initial load ? Removed load) downstream of the BMP
where Removed load = Removal efficiency * Initial load at the BMP
     = eff
BMP
 * load
BMP
 
 
 For one BMP, the principle also uses the flowaccumulation function to create a
removed load grid. For cells that have loads removed, the value for that cell is the actual
load removed (Figure 7.3).
 
 
 
 
 
 
 
 
  138
 
 
cell value =
eff * load
BMP
no data
BMP grid
weighted
flowaccumulation
Removed load grid
0
eff*load
BMP
Figure 7.3: Removal load grid for located BMPs defined by efficiency
 This removed load grid is subtracted from the initial load grid to create the new
load grid after load removal at the BMPs. In Figure 7.4, the lowest loads are represented
in blue and the highest in red.
 
Figure 7.4: Corrected load
 Initial load
 Removed load
 Corrected load
  139
 In the case of nested BMPs, the load removed by the most downstream BMP
(BMP
2
) is affected by the load removed by the BMP upstream (BMP
1
) (Figure 7.5).
 
 Load removed by BMP
2 
= eff
2
 * [load
2
 ? eff
1
*(load
1
)]
 where load1 is the initial load at BMP
1
 and load
2
 the initial load at BMP
2
.
 
 
initial loads 
at BMP?s
BMP2
eff2
  eff1 * load1
Load2
Total BMP removal
BMP1
eff1
eff2 * (load2 - eff1 * load1)
BMP2
eff2
BMP1 removal BMP2 removal
Load1 BMP1
eff1
Figure 7.5: Total BMPs removal
 If BMP
n 
is located downstream of n-1 BMPs of efficiencies eff
1
,..., eff
n-1
, the load
removed by BMP
n
 depends on the incoming load to the BMP
n
, load which has been
treated by n-1 upstream BMPs.
 The general relationship is:
 Load removed by BMP
n
 = eff
n
*(load
n
-eff
n-1
*(load
n-1
-eff
n-2
*(load
n-2
-?)?eff
2
*(load
2
-
eff
1
*load
1
)?)
 [7.1]
 [7.2]
  140
 The existence of nested BMPs is determined by doing a weighted
flowaccumulation. The weight grid is a grid with positive values at the BMPs and no
data elsewhere. Since flowaccumulation adds the value of the cells located upstream of
the cell considered, the value in the new grid is zero for non-nested BMPs and positive
for nested BMPs. The loads removed is first computed for the non-nested (more
upstream) BMPs, which are given the order 0. The other BMPs are located downstream
of at least another BMP and are assigned an order based on the flowaccumulation value
at the BMP. Comparing two BMPs, the downstream BMP has a larger flowaccumulation
value since this value represents the number of cells located upstream of the cell
considered. The watershed of the downstream BMP includes the watershed of the
upstream BMP (Figure 7.6). The maximum order corresponds to the number of nested
BMPs. For example, the watershed on the left in Figure 7.7 contains 4 non-nested BMPs
and 5 nested BMPs. The maximum order is 5.
 The load removed is computed separately for each nested watershed after
computing the load removed by non-nested BMPs. This is done by setting the efficiency
of the BMPs whose order is different from the order considered to zero. For example, if
the order is 1, all the BMPs whose order is different from 1 have a zero removal
efficiency, i.e. only the removal efficiency of the BMP with order 1 is considered. The
number of flowaccumulations needed to compute the load removed is equal to the
number of nested BMPs plus one (the computations for non-nested BMPs are all done at
the same time).
 
 
  141
 
 
Flow accumulation BMP1 = 27 Flow accumulation BMP2 = 66
BMP drainage areas
Figure 7.6: BMP classification
 The flowaccumulation function is precisely the execution time limiting function
of the program. To decrease the execution time, the number of iterations must be
reduced. This can be implemented by modeling each watershed separately. Two
independent watersheds can not have nesting problems and their BMPs can be ordered
totally separately. Figure 7.7 shows the advantage of the method, which in the simple
case of two watersheds, enables one to reduce the number of iterations from 9 to 6. The
advantage will be all the more important when the system being considered is complex.
 
 
  142
 
Flowaccumulation
values: 1 < 2
0
0
0
1
2
6 (instead of 9)
1
0
0
0
0
2
3
4
5
3
Figure 7.7: Classification for non-nested watersheds
 The ranking method is programmed in the scripts Qual.BMPeff and
Qual.BMPcomp, which is a subroutine of Qual.BMPeff (Chapter8 and Appendix C).
 The inconvenience with this procedure is that the BMPs have small drainage
areas. It is important that the Digital Elevation Models used in the study give a very
accurate description of the topography. A comparison between the data gathered in the
field and the BMPs drainage areas determined by delineation shows the 30m cell used in
the study are not accurate enough. However, the use of new sources of data such as the
digital orthophotos with an increased accuracy should enable this approach.
  143
 If observed drainage areas are available, the solution consists in correcting the
efficiency in function of the errors between observed and computed drainage areas. The
computed drainage areas are obtained with the flowaccumulation grid: the
flowaccumulation value indicates the number of cells located upstream of a given cell,
i.e. the number of cells in the drainage area of that cell. For example, if the observed
drainage areas are given in acres, the relationship between computed areas in acres and
flowaccumulation value is, for the cell area in square feet:
 
 
 A coefficient defining the relationship between observed and computed drainage
areas for each BMP can be defined (equation 7.4).
 
 A BMP treats the loads generated in its drainage area with a given removal
efficiency, which must be corrected to be applied to the drainage area computed by the
model. Since the drainage areas for the BMPs are small, the difference between the loads
generated on the observed and on the computed drainage area is assumed to be
proportional to the difference in areas. The load effectively removed at the BMPs can be
obtained by using corrected efficiencies (equation 7.5).
 
 [7.3]
]acre/[ft 43560
][ft area cell * uelation valflowaccumu 
 [acre] area Computed
2
2
=
 [7.4]
area drainage computed
area drainage observed
correction
area
=
  144
 
 
 If the observed area is larger than the computed one, the area correction
coefficient is bigger than 1 and the corrected efficiency is bigger than the initial
efficiency. The method presented in this section applied to the BMPs coverage defined
with corrected efficiencies.
7.2 NON LOCATED BMPS
 In the future, new BMPs will be associated with each new construction. Since it
is not possible to accurately determine with great accuracy the areas which will be
developed, it is difficult if not impossible to know the precise locations of any future
BMP. The approach used for the located BMPs is not valid and the average effect of
BMPs over a given area must be computed instead.
 The planned BMPs treat newly developed areas, which are defined as the zones
where the land use changes from undeveloped under current conditions to developed
under future conditions. It is impossible to precisely locate these areas, therefore the
average development occurring in each traffic zone is used instead (buildup, section
6.3.1).
7.2.1 BMP zones
 The non-located BMPs are assumed to remove the load directly in the cell where
it is generated. Direct runoff load computation has already been explained in Chapter 5.
areacorr
correction * eff eff =
 [7.5]
  145
The other variable needed to compute the removed load in each cell is the associated
BMP removal efficiency.
 Different BMPs are used to treat the newly developed zones: the combination of
BMPs are based on the characteristics (recharge zone?) and on the location (City of
Austin, eastern suburban?) of the watersheds (Table 7.1). Eight zones are defined. A
combination of the five following types of BMP are applied in each zone:
? SED1: sediment pond with ?? water quality volume, ?on-line? or ?off-line? system.
? SAND2: ?on-line? sand filtration system with no pretreatment and ?? water quality
volume.
? SAND3: ?off-line? sand filtration system with pretreatment and ?? water quality
volume.
? COMP: City of Austin?s Composite Ordinance
? SOS: City of Austin?s Save Our Spring Ordinance
 
 Table 7.1: Percentage of BMPs per BMP zones (source: COA=City of Austin)
  Barton Springs Zone
1
 Non-Barton Springs zone
Recharge
Zone
 Contributing
Zone
 COA Jurisdiction
 BMP  COA  Non-
COA
 COA  Non-
COA
 Urban
2
 Eastern
Suburban
3
 Western
Suburban
4
 Non-
COA
 ZONE  1  2  3  4  5  6  7  8
 NONE    100%  73%  14%   100%
 SED1    10%     
SAND2  44%  100%  34%   17%  24%  44%  
 SAND3      10%  62%  56%  
 COMP  36%   36%   
SOS  20%   20%    
 
 
1 
Barton Springs Zone watersheds include Barton, Williamson, Onion, Bear, Little Bear
and Slaughter creeks in recharge and contributing zones.
 
  146
 
2 
Urban watersheds are Shoal, Waller, East Bouldin, West Bouldin, Blunn, Fort,
Tannehill, Buttermilk, Little Walnut, Harper?s Branch, Johnson, Boggy, Town Lake
adjacent and the segment of Barton below Barton Springs road, i.e. the very end of the
watershed (administratively, the city treats this area as an urban watershed). For Shoal
creek only, an urban watershed, apply the SAND2 BMP to 100% of new development
within the northern Edwards recharge zone to reflect the state?s Edwards rule. This is
different from the ?urban scenario? and applies to that portion of Shoal in the recharge
zone.
 
 
3 
Eastern Suburban watersheds are Walnut, Country Club, and Williamson, Bear, Little
Bear and Slaughter downstream of the recharge zone (and all remaining watersheds in
the eastern part of the city).
 
 
4 
Western suburban watershed are Bull, Eanes, Lake Austin, Bee, Little Bee, Taylor
Slough North, Taylor Slough South, Huck Slough and Dry Creek.
 
 This classification is based on the following assumptions:
? Non-COA Barton Springs Contributing Zone and Non-Barton Springs watersheds
are assumed to have no water quality protection regulations (i.e., other cities and
Water Quality Protection Zones provide little or no protection in these areas).
? In Western suburban watersheds, assume that all future projects will have some
control (Lake Austin ordinances (1980/81)). There are no sedimentation controls
because these were not typically allowed as a form of treatment.
? Assumption for Barton Springs zone current conditions is the same for SAND2.
 
? Zones outside of the city jurisdiction but in the Edwards recharge zone (north or
south), apply the SAND2 BMP.
  147
 The recharge and contributing zones are obtained by an Arc/Info union function
with the watersheds, the Edwards Aquifer (Edwards) and the City jurisdiction (juris,
Figure 7.8) coverages.
 
Figure 7.8: City jurisdiction
        *   CLL: City Limit Line
        ** ETJS: Extra territorial Jurisdictions
 The CLL (City Limit Line) and ETJs (extra territorial jurisdictions) are within
the City?s jurisdiction. The watersheds are characterized as urban (1), eastern (2) or
western suburban (3) in a new field created in ArcView. A coverage with zones fitting
the criteria in Table 7.1 is created in ArcView (futbmp_cv) by using the selection tool
  148
and are assigned a zone number (in field bmpzone). A grid corresponding to the BMP
zones is then created (Figure 7.9).
 Grid: futbmp_gr = polygrid ( futbmp_cv , bmpzone )
 
Figure 7.9: Future conditions BMP zones
  149
7.2.2 Removal efficiencies
  The BMPs treat only direct runoff. Their effective removal efficiency is a
function of the percentage of the volume of water that they treat (annual capture volume,
ACV) and of their average event removal efficiency (AERE).
 Eff = ACV * AERE
? Capture volume
 A distinction must be made between on-line and off-line BMPs. Off-line BMPs
capture only a certain amount of runoff: the flow greater than the design flow by-passes
the system. The average amount of runoff captured varies with the impervious cover and
the BMP water quality volume (capture volume). For on-line BMPs (e.g. wet ponds), all
runoff enters the BMP and no capture volume analysis is necessary.
 Some on-line sedimentation (SED1) and sand filtration systems are treated as
off-line using a conservative approach which is justified since on-line systems perform
poorly when the runoff volume is greater than the water quality volume.
 For off-line systems, the capture volume is estimated on an annual average basis
as an annual capture volume (ACV) which varies with regulatory requirements:
? Ordinances require a ?? water quality volume regardless of site impervious cover.
? More recent ordinances increase the water quality volume as impervious cover
increases.
 Linear relationships relating average capture volume to impervious cover have
been established by the City of Austin (Table 7.2).
 
 [7.6]
  150
 Table 7.2: Capture volume/Impervious Cover relationships (0<IC<1)
 BMP  ACV (0<ACV<1)
 SED1 , SED2 (??)  0.996 ? 0.4714*IC
 SAND3, COMP  0.9762 ? 0.154*IC
 SOS  1
 
 These relationships show that the percentage of treated direct runoff decreases
when the impervious cover increases since more direct runoff is generated. The capture
volume grids for the different BMPs can be created from the future impervious cover
grid (futic_gr) by applying the equations shown in Table 7.2.
 Grid: acv1 = 0.996 - 0.4714 * futic_gr
 Grid: acv2 = 0.9762 - 0.154 * futic_gr
? Average event removal efficiency
 Over its life, a BMP will achieve 80% (SED1) to 90% (non-degradation BMPs)
of its projected performance. The average event removal efficiency (Table 7.3) which
indicates the load efficiency removal for each constituent takes this factor into account.
  Table 7.3: SED1, SAND2, SAND3 average event removal efficiencies
 Average Event Removal Efficiency
 (%)
 Constituent  SED1  SAND2
 SAND3
 TSS  40  68
 BOD  24  40
 COD  24  52
 TOC  16  48
 NO3   0  -25
 NH3   8  48
 TKN  16  40
 TN  16  24
 DP   0   0
 TP  20  48
 Cu  16  40
 Pb  32  64
 Zn  16  40
  151
 Composite ordinance (COMP) and  Save Our Springs ordinances (SOS) have a
81% removal efficiency.
? Removal efficiencies in the BMP zones
 Grids with the removal efficiency associated to each BMPs zone for each
constituent can be created in Arc/Info by taking the product of the average event removal
efficiency by the associated capture volume for each BMP and by weighting the
contribution of each BMP type within the different zones shown in the grid futbmp_gr.
 Grid: eff1 = con ( futbmp_gr == 1 ,  0.44 * acv1 * SAND2 + 0.36 * acv2 * COMP +
0.2 * SOS , futbmp_gr )
 
 Grid: eff2 = con ( futbmp_gr == 2 , acv1 * SAND2, eff1 )
 
 Grid: eff3 = con ( futbmp_gr == 3 , ( 0.1 * SED1 + 0.34 *  SAND2 ) * acv1 + 0.36 *
COMP * acv2 + 0.2 * SOS , eff2 )
 
 Grid: eff4 = con ( futbmp_gr == 4 or futbmp_gr == 8 , 0 , eff3 )
 
 Grid: eff5 = con ( futbmp_gr == 5 , 0.17 * SAND2 * acv1 + 0.1 * SAND3 * acv2 ,
eff4)
 
 Grid: eff6 = con (futbmp_gr == 6 , 0.24 * SAND2 * acv1 + 0.62 * SAND3 * acv2 ,
bodeff5 )
 
 Grid: eff0 = con ( futbmp_gr == 7 , 0.44 * SAND2 * acv1 + 0.56 * SAND3 * acv2 ,
eff6 )
7.2.3 Load corrected by the BMPs
? Removed load
 The load treated is the load generated in the newly developed areas. The removal
efficiency in each cell (eff0) must be multiplied by the development rate in that cell
(given by the grid buildup, section 6.3.1).
  152
Grid: eff = buildup * eff0
 The resulting efficiency grid (eff) is multiplied by the direct runoff load
generated by each cell (loadcell) to yield the load removed in each cell. A
flowaccumulation produces then the total load removed at any location in the grid
(load0rem).
Grid: loadremcell = loadcell * eff
Grid: load0rem = flowaccumulation (burn_fdr , loadremcell )
 
 If no recharge zone is taken into account, the new load is obtained by simply
subtracting the removed load from the load previously computed (load).
 Grid: newload = load - load0rem
 The method is much more complicated with a recharge zone since the BMPs
modify the in-stream concentrations in two ways:
1. Load removal
2. Direct runoff removal for non discharge BMPs (COMP and SOS).
 Base flow and direct runoff are assumed to be well mixed in the creeks so that
direct runoff and base flow lost in the recharge zone have the same concentration (co) as
the total flow at the location where the losses occur. Since the concentration changes and
the recharge stays constant, the load lost to the recharge zone is also modified and must
be reevaluated. Note that the in-stream concentration modifications caused by the located
BMPs were assumed to be negligible and their effect on the load lost to the recharge
zone was not considered. This is because the calibration was done by neglecting the
  153
effect of the current located BMPs. The impact of the located BMPs on the recharge zone
could however also be implemented if necessary.
? Flow after non discharge BMPs correction
 The direct runoff removed by the non discharge BMPs (COMP and SOS) is
obtained by computing first the flow removal efficiency in the zones where these BMPs
are located (zones 1 and 3), and by multiplying the efficiency grid by the direct runoff
generated in each cell. A flowaccumulation will eventually create a grid containing the
direct runoff retained in the non-discharge BMPs (Procedure 7.1). Without taking into
account the recharge, the new flow (totalflow1) considering the effect of non discharge
BMPs is obtained by subtracting the removed flow from the previous flow value
(totalflow0).
 Procedure 7.1: Flow corrected with non-discharge BMPs
 Direct runoff coefficients (apply IC/direct runoff coefficient relationship)
Grid: runcoef = 0.3428 * icfut_gr * icfut_gr + 0.5677 * icfut_gr + 0.0125
Development rate in zones with non-discharge BMPs
Grid: zone13 = con (futbmp_gr == 1 or futbmp_gr == 3 , buildup )
Removal flow efficiency
Grid: capt13 = zone13 * ( 0.36 * ACV2 * 0.9 + 0.2 * 0.9 )
Direct runoff captured
Grid: runcell_cpt = runcell * capt13
Grid: runcell_cpt0 = flowaccumulation ( burn_fdr , runcell_cpt )
New total flow
Grid: totalflow01 = totalflow0 - runcell_cpt0
  154
? Load after BMPs effect
 The load without considering a recharge zone is computed by subtracting the
removed load from the load without recharge previously computed (load0, section 6.1.2).
 Grid: load01 = load0 ? load0rem (with load0 = co*totalflow0)
 
 The BMPs corrected in-stream concentration co1 is obtained  by dividing the
BMPs corrected load load01 by the non discharge BMPs corrected flow totalflow01.
 
 Grid: co1 = load01/totalflow01
 
 The BMPs corrected load lost to the recharge zone is computed by multiplying
the corrected concentration grid (co1) by the grid containing the recharge volume lost in
each cell (lcorr_rech), and by doing a flowaccumulation.
 Grid: loadcellrech = lcorr_rech * co1
 Grid: rechload = flowaccumulation ( burn_fdr , loadcellrech)
 
 The final corrected load is obtained by subtracting the load lost in the recharge
zone from the BMPs corrected load without considering the recharge (load01).
 
 Grid: newload = load01 ? rechload
 
 
? AML computation
 Procedure 7.2 is an AML which computes the corrected load if the effect of non
discharge BMPs on the flow has been previously computed (i.e. totalflow01). An
Avenue script (Qual.BMPfut, section 8.4.3) enables the user to compute both the
corrected flow and load.
  155
 
 Procedure 7.2: BMPs corrected load
/*----------------------------------------
/*--- CORRECTEDLOAD.AML---
*-----------------------------------------
/*FUNCTION: compute the BMPs corrected load.
/*INPUTS: impervious cover grid (icfut_gr), IC/EMC relationship for direct runoff,
traffic serial zones (zone_gr), direct runoff generated in each cell (runcell), buildup grid
(buildup), removal efficiency grid (e.g bodeff), flowdirection grid (burn_fdr),
concentration grid (co), total flow without recharge (totalflow0), total flow without
recharge after effects of non discharge BMPs (totalflow01), recharge lost in each cell
(lcorr_rech).
/*----------------------------------------
/*BEGIN AML EXECUTION
grid
setcell 100
/*Direct runoff EMC grid
emc_gr0 = 14 * icfut_gr + 3.5
emc_gr = con ( zone_gr == 999 , 0 , emc_gr0 )
kill emc_gr0 all
/*Load removed by the BMPs (without considering recharge)
loadcell = runcell * emc_gr * 3.048 * 3.048 * 3.048 * 86400 * 365 / 1000000
kill emc_gr all
eff = buildup * bodeff
loadremcell = loadcell * eff
kill loadcell all
kill eff all
load0rem = flowaccumulation(burn_fdr , loadremcell )
kill loadremell all
load01= co*totalflow0 - load0rem
kill load0rem all
co1=load01/totaflow01
/*Load lost in the recharge zone
loadcellrech = lcorr_rech*co1
kill co1 all
rechload = flowaccumulation (burn_fdr,  loadcellrech)
kill loadcellrech all
kill co1 all
/*New load after BMPs
newload = load01 - rechload
  156
 The results would however be different if the locations of the BMPs were
known, since the relationship between average impervious cover and load removed is
non-linear. Direct runoff is related to impervious cover by a second order equation while
EMC and capture volume follow a linear relationship. Hence the average value at a
location is not the same as the sum of average values.
7.2.4 Effect of non-discharge BMPs on channel erosion
 Since the COMP and SOS BMPs applied in the City jurisdiction within the
recharge zone are no-discharge BMPs, they decrease the volume of direct runoff in the
streams. Direct runoff causes channel erosion in the streams: since its volume decreases,
the channel erosion also decreases.
 Previous studies conducted in section 6.2 have shown that erosion could be
linearly related to the average impervious cover, which is related to the amount of direct
runoff in the stream. The decreased direct runoff due to the ordinance BMPs can be
translated at the cell level by a decreased runoff coefficient, and hence a decreased
impervious cover, by applying the impervious cover/runoff coefficient relationship for
direct runoff (Figure 7.10).
 
 
 
 
 
  157
Figure 7.10: Effective impervious cover
 The equation relating direct runoff coefficients to impervious cover is:
 Runcoef = 0.3428 * IC
2
 + 0.5677 * IC + 0.0125, with 0<IC<1
 
 Given the value of the direct runoff coefficient (runcoef), the impervious cover
can be obtained by looking for the positive root of this second order equation (eq. 7.8).
 
3428.0*2
)0125.0uncoefR(*3428.0*45677.05677.0
IC
2
?++?
=
 The value of the effective runoff coefficient is obtained in Grid.
 Grid: eff_runcoef = runcoef * ( 1 - capt13 )
 Grid: xx1 = (0.5677)*(0.5677) + 4 * 0.3428 * ( eff_runcoef - 0.0125 )
 Grid: xx2 = sqrt ( xx1 )
 Grid: xx3 = -0.5677 + xx2
 Grid: eff_futic1 = xx3 / 2 / 0.3428
 Grid: efficfut = merge ( eff_futic , icfut_gr )
 [7.8]
 [7.7]
 IC
 Direct
Runoff
 Coefficient
 Direct
 Runoff
 Generated
 Non
discharge
 BMPs
 Effective
 Direct
Runoff
 Effective
 Direct
  Runoff
 Coefficient
 Effective
     IC
  158
 The average effective impervious cover is then obtained by doing a
flowaccumulation.
 Grid: efficfut_fac = flowaccumulation( burn_fdr , efficfut )
 Grid: efficfut_avg1 = efficfut_fac / burn_fac
 Grid: efficfut_avg = merge ( efficfut_avg , efficfut )
 The effective impervious cover grid is then used to compute the new erosion
coefficients.
 
 Best Managements Practices have been modeled in three different ways:
? Located BMPs defined by load removed.
? Located BMPs defined by efficiency.
? Non located BMPs defined by efficiency.
The effects of non-discharge BMPs (COMP and SOS) on discharge and on
erosion (effective impervious cover concept) have also been modeled.
  159
Chapter 8: The ArcView Model
 During this study, Avenue scripts were created to automate several water quality
modeling functions. The water quality model was also converted from Arc/Info to
Avenue. The codes of the scripts are in Appendix C.
 To make the model user-friendly, these scripts were customized with menus and
buttons in a project and an ArcView Extension (Qual.avx) based on that project was
created. The following sections describe the extension, indicate how it was created and
how it can be modified, and show in detail how to use the scripts for computing flows,
loads and BMP effects.
 The objective of this chapter is not to explain the methodology: that has been
done in the previous chapters.
8.1 ARCVIEW NON-POINT SOURCE POLLUTION EXTENSION
8.1.1 Extension installation
 If the menus Qual and QualTools are not in the menu bar when a View window
is active, then the Water Quality extension needs to be installed.
 The Water quality extension, like any other ArcView extension, is installed by
using in the menus the command File/Extensions (Figure 8.1). This command is
accessible when the Project window (The Window with icons representing Views,
Tables, Charts, Layouts and Scripts) is active. By default, the Project window is active in
a new project.
  160
 
 
Figure 8.1: Command to install the extension
 The Extensions window appears (Figure 8.2). Note that it is necessary to select
also the Spatial Analyst extension to be able to use the Water Quality extension: a check
mark must be put in both boxes. The Spatial Analyst extension can be obtained from
ESRI. The Water Quality extension (qual.avx) is the extension created in this study. This
extension is in the CDROM associated with this report (Appendix B). Updated versions
  161
may be obtained from CRWR. The extension file qual.avx must be copied to the
directory esri\av_gis30\ArcView\ext32 in order for it to appear in this list of available
extensions. If the user does not have permission to write to that directory, copying the
file to the c:\temp works also sometimes.
 
Figure 8.2: Extensions window
8.1.2 Extension description
 The Water Quality extension has been installed. New buttons, menus and a new
tool can now be seen. The names, functions and customization of the scripts are shown in
Table 8.1. The scripts are based either on a View or on one or several Tables. If they are
based on View, they can only be run when the View is active. If they are based on Table,
they can only be run when the Table is active. Similarly, buttons, menus and tools are
  162
visible when either a View or a Table is active, depending on the script they are
associated with.
? View based
When a View is active, 13 buttons, 1 tool and 2 menus from the Water Quality
extension are visible (Figure 8.3).
 Buttons
 Tool
 Menus
  
 
Figure 8.3: View based buttons, tool and menus
 The first 5 buttons, associated with the menu Qual, are used for flows, loads, and
BMP effects computation. Their funtion and the input files needed for them are described
in detail in sections 8.2, 8.3 and 8.4. The last 8 buttons, associated with the menu
QualTools, correspond to different utility tools used during the study, and have been
described in Chapters 2, 3 and 4.
  163
? Table operations
 When a table is active, two buttons ( ) and a menu (QualTable) appear.
The first button is used to delete several fields in a table. It corresponds to the first item
in the menu (Delete fields). The second button, corresponding to the second item in the
menu (Join permanently), is used to join permanently two tables (Chapter 2).
 
  164
    Table 8.1: Description of Scripts
 Script name  Menu  Icon  Function
 Qual.Addpoint  Qual/Addpoint
  Creates or adds a point to a point coverage.
 Qual.Average  QualTools/Average
 
 Computes the average based on drainage area.
 Qual.BMPeff  Qual/BMPeff
 
 Computes the load removed by located BMPs defined by
removal efficiency.
 Qual.BMPfut  Qual/BMPfut
 
 Computes the new load after the effect of non located BMPs
defined by removal efficiency.
 Qual.BMPload  Qual/BMPload
 
 Computes the load removed by located BMPs defined by load
removed.
 Qual.Creek  QualTools/Creek
 
 Delineates creeks for a flowaccumulation threshold.
 Qual.Creeklimit  QualTools/Creek limit
 
 Creates gridpoints representing the upstream limit of the
creeks for a flowaccumulation threshold.
 Qual.Delete  QualTable/Delete fields
 
 Deletes several fields in a table.
 Qual.Flow  Qual/Flow
 
 Computes the discharge (cfs).
 
 Qual.HydroZdlsv  QualTools/Dangling
 
 Dangling polygons.
 Qual.Join  QualTable/Join permanently
 
 Permanently joins two tables.
  165
 
 Table 8.1 (cont.): Description of Scripts
 Script name  Menu  Icon  Function
 Qual.Load  Qual/Load
 
 Computes the load (kg/yr).
 
 Qual.Mergetheme  QualTools/Merge themes
 
 Merges two themes.
 Qual.Pick  QualTools/Pick
 
 Retrieves the values of grids for points in a point coverage.
 Qual.Wshd  QualTools/Watershed
 
 Delineates watersheds for points in a point coverage.
 Qual.Zonalmean  QualTools/Zonalmean
 
 Computes the averages within a zone.
 
 
  166
8.1.3 Extension scripts
 The extension scripts are system scripts: they do not appear when clicking on
Scripts in the project window. However, the scripts can be obtained by loading the
system scripts. To know the script corresponding to a given menu or button in a project
(e.g. project austin.apr in Figure 8.4), the user has just to use the Customize window
which appears when using the command Project/Customize accessible when the Project
window is active. For example, in Figure 8.4, the script Qual.Flow is linked to the
command Qual/Flow visible when a view in active (Type: View).
 
Figure 8.4: Script customization window
  167
 To view the script Qual.Flow, the user has then to add a new script by clicking
first on Scripts and then on New in the project window. A Script window called Script1
appears. The script Qual.Flow is obtained by using the command Script/Load System
Script accessible when the Script window is active (Figure 8.5).
 
Figure 8.5: Load an extension script
 The Script Manager, containing the list of system scripts in alphabetical order
appears (Figure 8.6).
  168
 
Figure 8.6: Script Manager
 After selecting the desired script in the Script Manager, this script is written in
the active Script window (Script1, Figure 8.7). The script can be renamed by using the
command Script/Properties.
 
Figure 8.7: An Extension Script
  169
8.1.4 Extension creation
 An extension is created in two steps:
? Create a project with all the scripts and customization which will be in the
extension.
? Write the scripts creating the extension.
? Extension project
 First a project with all the components wanted in the extension is created. The
project must look like the extension: the only difference is that the scripts are visible in
the project whereas they are system scripts and hence invisible in the extension.
 The first step is to add all the scripts needed to the project. It is easier when
creating an extension to use script with the same prefix (e.g. Qual.). Once the scripts
have been added, they need to be customized with buttons, menus and tools by using the
Customize window (Figure 8.4).
? Extension scripts
 Three scripts are needed to build an extension. One script is used to create the
extension (Extension.Make): this script calls a script to install the extension
(Extension.Install) and another to uninstall it (Extension.Uninstall). The Avenue scripts
used to build the extension are in Appendix C. These scripts are easily corrected to
modify the extension. The ArcView Online Help is also very helpful.
 
 The remaining sections of this chapter show the user how to use the scripts for
computing flows, loads and BMP effects.
  170
8.2 FLOW COMPUTATION
 Predicted flow, direct runoff and base flow are computed by using the script
Qual.Flow (Appendix C). Note that this script can also be used to recalibrate the
discharge. This script can be run when a view window is active either by clicking on the
button 
 
or using the command Qual/Flow.
8.2.1 Input/Output files
? Qual.Flow inputs
 Before running the script, the input files needed in the script must be added in
the View window. The number of input files depends whether a recharge zone is
considered. If there is a recharge zone, five files are necessary; otherwise only three files
are required (Figure 8.8).
 
Figure 8.8: Input files (Qual.Flow)
  171
1. Impervious cover coverage or grid (futic, Chapter 4). The attribute table of
the coverage must contain an impervious cover field. The impervious cover
can be expressed either as percentage or as decimal fraction.
2. Flow direction grid (burn_fdr, Chapter 3).
3. Flow correction coefficients grid (corcoef, Chapter 5).
The last two inputs are needed only if a recharge zone is taken into account.
4. Recharge flow grid in cfs (rech_fac, Chapter 5).
5. Cell recharge grid in cfs (lcorr_rech, Chapter 5).
Note that two scripts creating the grids needed for calibration (corcoef for flow
calibration, rech_fac and lcorr_rech for recharge) are currently developed at CRWR and
should be available by December 15, 1997.
? Qual.Flow outputs
 The script creates six output grids if a recharge zone is considered (Figure 8.9)
and five otherwise. These grids are:
1. Corrected direct runoff generated in each cell in cfs (runcel1).
2. Corrected base flow generated in each cell in cfs (bflowc1).
3. Total flow without considering recharge in cfs (tflow01). *
4. Total predicted flow in cfs (flow1).
5. Direct runoff in cfs (runoff1).
6. Base flow in cfs (basefl1).
* Grid computed only if a recharge zone is considered.
  172
The names in italic are the names given by default to the outputs. The number at
the end (1 in this case) enables one to differentiate the files created in different runs.
For example if the file runcel1 already exists, the new corrected direct runoff grid is
called runcel2. All the grids created are added as themes in the view at the top of the
legend. The theme at the top is hence the last file created.
 
 
Figure 8.9: Output files (Qual.Flow)
8.2.2 Running Qual.Flow
 Once the input files have been added to the View, the script can be run by
clicking on the button  or by using the command Qual.Flow. The following section
describes the series of message boxes appearing on the screen during the flow
computation.
  173
 The first window appearing on the screen is the Analysis Properties window,
which is normally accessed through the command Analysis/Properties. This window was
inserted in the program so that the user has to define the analysis extent and the cell size
before the computations begin. It is important since the analysis extent is set by default
to the maximum grid extent, for which the computation length is quite long. Several
options are available to choose an analysis extent (Figure 8.10). Note that option to set
the extent to what can be seen in the View window is Same as Display and not Same as
View.
 
Figure 8.10: Analysis extent and cell size (Qual.Flow)
  174
 
 The following message box (Figure 8.11) prompts the user for the working
directory where the temporary files and the output grids runcel1, bflowc1 and tflow01
will be written. Since these grids are used in the load and BMP computation. It is
important to be able to locate easily these three files.
 
 
 
Figure 8.11: Working directory (Qual.Flow)
 A series of message boxes prompts then for the input files. The first box prompts
the user for the impervious cover theme (Figure 8.12).
 
Figure 8.12: Choose an impervious cover theme (Qual.Flow)
 If the theme chosen is a polygon coverage, then a message box prompts the user
for the name of the impervious cover field in the attribute table (Figure 8.13). If it is a
grid theme, the script automatically assumes that the impervious cover is the value given
in the grid.
  175
 
Figure 8.13: Choose an impervious cover field (Qual.Flow)
The second input file is a flowdirection grid (burn_fdr, Figure 8.14) which is
used to compute flowaccumulation grids. The cell value indicates the direction of the
flow. The grid is based on the topography of the study area (Chapter 3).
 Figure 8.14: Choose a flowdirection grid (Qual.Flow)
The following input (Figure 8.15) is a flow correction grid (corcoef) obtained by
flow calibration. This grid is based on the comparison between observed and predicted
flows based on impervious cover/runoff coefficient relationships. If the volume of
precipitation, the relationships used or the observed values used are modified for current
conditions, the correction grid must be redefined (section 5.3.3).
  176
 
Figure 8.15: Choose a correction grid (Qual.Flow)
 The user is then asked whether he or she wants to consider a recharge zone
(Figure 8.16). The recharge zone makes the computation longer and more complicated.
 
Figure 8.16: Recharge zone (Qual.Flow)
 When considering a recharge zone, two more inputs are needed to model the
recharge flow. The first (Figure 8.17) is a grid with the recharge lost in each cell within
the creeks located in the recharge zone (lcorr_rech, section 5.1.4). The second input
(rech_fac, Figure 8.8) is the result of a flow accumulation on the grid. This grid indicates
the total recharge flow lost upstream of a given cell.
 
Figure 8.17: Choose a cell recharge grid (Qual.Flow)
  177
 
Figure 8.18: Choose a recharge grid (Qual.Flow)
 The user is then asked for the names to give to the direct runoff (runoff1, Figure
8.19), base flow (bflow1) and total flow (flow1) grids.
 
Figure 8.19: Name of the output grid (Qual.Flow)
 If the impervious cover theme is a polygon theme, the runoff coefficients may
have already been calculated during a previous run. It is perhaps not necessary to
recompute them. A message box asks the user whether he wants to redo the computation
(Figure 8.20).
  178
 
 Figure 8.20: Recompute the runoff coefficients (Qual.Flow)
 By default, the names given to the runoff coefficient fields are runcoef for direct
runoff and runcoef_bf for base flow. If a field already exists, a message box asks the user
if he wants to overwrite this field (Figure 8.21).
 
 Figure 8.21: Overwrite an existing field (Qual.Flow)
 By answering "no", a message box appears which prompts the user for the name
to give to the new field (Figure 8.22). Note that the runoff coefficients fields used if the
coefficients are not recomputed are the fields runcoef and runcoef_bf.
 
 Figure 8.22: Renaming a runoff coefficient field (Qual.Flow)
 If the runoff coefficients are computed, a series of message boxes prompt the
user for the impervious cover/runoff coefficient relationships to use. First, a message box
  179
shows the default relationship for direct runoff (Figure 8.23) presented in Chapter 5. The
message box also gives the user the possibility to modify the relationship without
modifying the script.
 
Figure 8.23: Default impervious cover/direct runoff coefficient relationship (Qual.Flow)
 The relationship is defined as a second order equation whose coefficients can be
modified by the user (Figure 8.24). The impervious cover values in the equation are
given as decimal fractions. If the format of the equation changes (third order?) the script
must be modified to accommodate that.
 
 Figure 8.24: Modifying the impervious cover/direct runoff coefficient
        relationship (Qual.Flow)
 
 The process is similar for base flow runoff coefficients. A message box shows
the default relationship defined in the study (Figure 8.25).
 
  180
 
 Figure 8.25: Default impervious cover/base flow runoff coefficients
        relationship (Qual.Flow)
 
 The relationship is defined as a first order equation whose coefficients can be
modified (Figure 8.26). The impervious cover value above which no base flow occurs is
automatically modified. However, if the format of the equation changes (second
order?), the script must be modified and the Extension must be recreated.
 
 Figure 8.26: Modifying the impervious cover/base flow coefficients
             relationship (Qual.Flow)
 
 
 If the impervious cover is a polygon coverage, its attribute table is edited to add
the runoff coefficients fields (Figure 8.27).
 
  181
 
 Figure 8.27: Impervious cover attribute table (Qual.Flow)
 
 The script then calculates the new grids. A message box indicates that the
computation has been completed.
 For an undetermined reason, the error message box shown in Figure 8.28 appears
sometimes. The only solution to eliminate this problem is to save the project and exit
from ArcView. The script should then run without any problem. However, if it still does
not work, the solution is to exit from ArcView again.
 
 
 Figure 8.28: Error message (Qual.Flow)
 
  182
8.3 LOAD COMPUTATION
 The predicted external load for any constituent for which the event mean
concentrations are known is computed with the script Qual.Load. This script can be run
when a View window is active either by clicking on the button 
 
or using the
command Qual/Load.
8.3.1 Input/Output files
? Qual.Load inputs
 Two tables (Figure 8.31) and seven themes (Figure 8.29) are needed as inputs to
the script if a recharge zone is to be considered.
1. Direct runoff EMC table (emcrun.dbf, section 8.3.1)
2. Base flow EMC table (emcbf.dbf, section 8.3.1)
3. Impervious cover coverage or grid (futic, Chapter 4). The attribute table of
the coverage must contain an impervious cover field. The impervious cover
can be expressed either as percentage or as decimal fraction. The program
examines the maximum impervious cover value: if this value is less than the
impervious cover is considered as decimal fraction.
4. Flow direction grid (burn_fdr, Chapter 3)
5. Water land use zones grid (zone_gr, Chapter 6). Water must be given the
grid-code 999 (water code for traffic serial zones).
6. Corrected direct runoff generated in each cell in cfs (runcel1). This grid is an
output of the flow computation.
  183
7. Corrected base flow generated in each cell (bflowc1). This grid is an output
of the flow computation.
The next two grids are required only if a recharge zone is considered.
8. Total flow without considering recharge in cfs (Tflow01).
9. Cell recharge in cfs (lcorr_rech, Chapter 5).
Figure 8.29: Input themes (Qual.Load)
? Qual.Load outputs
 The script creates as many load grids as number of constituents for which the
load is computed. The constituents are chosen by the user in a list based on the
constituents in the EMC tables. Figure 8.30 shows the view obtained after running the
script for BOD, COD and Cu.
 
  184
 
Figure 8.30: Inputs and outputs (Qual.Load)
? Format for EMC tables
 Tables containing the coefficients of the impervious cover/EMCs relationships
are needed to compute the load. The tables must be added to the project by clicking first
on the Project window (qual.apr, Figure 8.31), then on Tables and finally on Add. Two
tables are necessary: one for direct runoff EMCs (emcrun.dbf) and the other for base flow
EMCs (emcbf.dbf).
 
 Direct runoff
 Linear relationships were developed between impervious cover and direct runoff
EMCs (Chapter 6):
 EMC = a+ b*IC, where 0<IC<1 and EMC in mg/l
 Two coefficients, a and b, are needed for each constituent to define the
relationship. The direct runoff EMCs table emcrun.dbf contains three fields (Figure
  185
8.32). The first field contains the names of the constituents, the second the value of the
constant a and the third the value of the first order coefficient b.
 
       Figure 8.31: Add tables (Qual.Load)
 
 
 Figure 8.32: Direct runoff EMCs table
 (Qual.Load)
 
 Polynomial relationships higher than first order can be used without modifying
the script. The values of the n
th
 order coefficients must be written in the (n+2)
th
 column.
However, for any other relationship, the script and the table needs to be modified.
 
 Base flow
 The format of this table is a little different since the base flow EMCs are defined
as constant values for undeveloped and developed areas (Chapter 6). Areas with an
impervious cover less than 15% are considered undeveloped. This limit can be modified
by setting the variable undev to a different value (in percentage) in the script Qual.Load.
  186
 
undev > IC if d                  
=EMC
 undev IC if c                  
bf
?
 The first column in the base flow EMC table contains the names of the
constituents studied. This table must be consistent with the direct runoff EMC tables.
Both tables must have the same number of constituents having exactly the same name
and be in the same order. Error messages appear if the tables are not consistent. The
second column contains the base flow EMCs in mg/l for undeveloped areas and the third
one the base flow EMCs in mg/l for developed areas (Figure 8.33).
 
Figure 8.33: Base flow EMC table (Qual.Load)
  187
8.3.2 Running Qual.Load
 Once the input tables have been added to the Project window and the input
themes to the view, the script Qual.Load can be run by clicking on the button 
 
or by
using the command Qual.Flow.
 
 As for the flow computation, the first window which appears is the Analysis
Properties window prompting the user for the analysis extent and for the cell size to use.
To keep the same extent and cell size used in the flow computation, if they have not been
modified, they just need to be set to current value in the Analysis Properties window.
 Also as for the flow computation, the following message box prompts the user
for the name of the working directory where the temporary files will be written.
 Next the script prompts the user for the EMC tables, first for direct runoff
(emcrun.dbf, Figure 8.34) and then for base flow (Figure 8.35).
 
 
Figure 8.34: Choose a direct runoff EMCs table (Qual.Load)
 
Figure 8.35: Choose a base flow EMCs table (Qual.Load)
  188
 After selecting the EMCs tables, the script prompts the user for the constituents
to model (emcbf.dbf, Figure 8.36). Several constituents may be selected.
 
 Figure 8.36: Choose the constituent(s) to model (Qual.Load)
 
 For each selected constituent a message box prompts the user for the name to
give to the constituent load grid (e.g. BOD in Figure 8.37).
 
Figure 8.37: Name the load grid (Qual.Load)
  189
 A series of message boxes prompts then for the input themes. The first input
theme is the impervious cover theme (futic, Figure 8.38). If the impervious cover is a
polygon coverage then the user is prompted for the name of the impervious cover field.
 
 Figure 8.38: Choose an impervious cover theme (Qual.Load)
 
The user is then prompted for a flowdirection grid (burn_fdr, Figure 8.39).
 Figure 8.39: Choose a flowdirection grid (Qual.Load)
 
 The following message box prompts for a water land use zones grid (zone_gr,
Figure 8.40). This theme is used to correct the EMC grids so that the EMC
corresponding to water is zero. For current conditions, water is defined by the land use
code 940. With the traffic serial zones for future conditions, water is defined by the
traffic serial zone number 999.
  190
 
Figure 8.40: Choose a water land use theme (Qual.Load)
 The script prompts then for a corrected cell runoff grid (runcel1, Figure 8.41).
This grid is an output of the flow computation. It represents the direct runoff generated in
any cell in cfs after applying the flow correction (but not the recharge correction if
applicable).
 
Figure 8.41: Choose a corrected runoff cell grid (Qual.Load)
 The following message box prompts the user for a corrected base flow runoff
grid (Figure 8.42). This grid is also an output of the flow computation. It corresponds to
the amount of base flow in cfs generated by any cell after applying the flow correction
(but not the recharge correction if applicable).
 
 Figure 8.42: Choose a corrected base flow cell grid
  191
 
 A message box asks then the user whether he wants to consider a recharge zone
(Figure 8.43).
 
Figure 8.43: Recharge zone (Qual.Load)
 If the answer  is ?no? then no other inputs are needed. Otherwise two more input
themes are needed. The first input needed is a cell recharge grid which indicates the
recharge lost in any cell (Figure 8.44). This grid is used to compute the load lost in the
recharge (multiplied by the corresponding concentrations).
 The second theme needed is a total flow grid, without considering the recharge
(Figure 8.45). This grid is computed during the flow computation. It is used to compute
the concentration in the flow, assuming that the concentration is the same with and
without a recharge zone.
 
Figure 8.44: Choose a cell recharge grid (Qual.Load)
  192
 
 Figure 8.45: Choose a grid with the flow without recharge (Qual.Load)
 
 The script computes then the load for each constituent selected and adds the new
load grids to the view. A final message indicates that the load computation is finished.
 
 
 
 
  193
8.4 BEST MANAGEMENT PRACTICES
 Best Management practices can be modeled in three different ways:
? Located BMPs defined by mass removed (section 8.4.1).
? Located BMPs defined by efficiency (section 8.4.2).
? Non located BMPs defined by efficiency (section 8.4.3).
8.4.1 Located BMPs defined by load removed
 The script Qual.BMPload (Appendix C) allows the user to compute the load
removed by a set of BMPs described in a point coverage. It can be run either with the
button  or the command Qual/BMPload. Two input files are needed to run the script
(Figure 8.46):
? a flowdirection grid (burn_fdr, Chapter 3)
? a BMP point coverage (city1, Chapter 7). The attribute table must contain a table
with a load removed field. The value in this field can be negative (e.g. NO
3
).
 
Figure 8.46: Input files (Qual.BMPload)
  194
 When running the script, a message box prompts first the user for the name of
the working directory (Figure 8.47).
 
 
Figure 8.47: Choose the working directory (Qual.BMPload)
 The following message box prompts the user for the name to give to the grid
representing the load removed (Figure 8.48).
 
Figure 8.48: Name of the removed load grid (Qual.BMPload)
 
 Two message boxes prompt then for a flowdirection grid (Figure 8.49) and a
BMP point coverage (Figure 8.50).
 
  195
 
Figure 8.49: Choose a flowdirection grid
 
Figure 8.50: Choose a BMP point coverage (Qual.BMPload)
 The next step consists of choosing in the attribute table of the point coverage the
field containing the values of the loads removed. Figure 8.51 shows the attribute table of
the point coverage city1which contains 121 residential BMPs.
 
Figure 8.51: BMPs point coverage attributes table
  196
 For example the field TSS, which gives the loads of TSS removed at the BMP
stations in the point coverage city1 (residential BMPs), can be selected (Figure 8.52).
The script can handle both positive and negative value.
 
Figure 8.52: Choose a removed load field (Qual.BMPload)
 The script computes then the total load removed by the BMPs by doing a
weighted flowaccumulation (Chapter 7).
 The message box ?Input grid has errors? appears for an obscure reason from time
to time. The solution is to exit from ArcView and to reopen the project until the script
works.
 A message box indicates that the removed load grid has been computed (Figure
8.53) and added to the View (Figure 8.54).
 
Figure 8.53: Final Message to user (Qual.BMPload)
  197
 
Figure 8.54: Input and output themes (Qual.BMPload)
  198
8.4.2 Located BMPs defined by efficiency
 The script Qual.BMPeff allows the user to compute the load removed by a set of
BMPs defined by efficiency. The script can be run by clicking on the button 
 
or by
using the command Qual/BMPeff. This script is based on the principle described in
Chapter 7. Like the previous script, Qual.BMPeff computes the load removed by located
BMPs defined in a point coverage. The difference is that the BMPs are defined by
efficiency instead of load removed. Hence the load removed at any BMP depends on
what was removed upstream of that BMP. The load removed is computed as the
difference between the original load and the removed load.
 Note that the script can not handle negative efficiencies yet and needs to be
modified to do so.
? Qual.BMPeff input files
 Five input files are needed (Figure 8.55):
1. Flowdirection grid (burn_fdr, Chapter 3).
2. Flowaccumulation grid (burn_fac, Chapter 3).
3. BMPs point coverage (BMP.shp, Chapter 7). The attribute table must contain
an efficiency field. The efficiencies can be expressed either as percentage or
decimal fraction. If the efficiencies must be corrected, the table must also
contain a field with the observed drainage areas in acres.
4. Initial load grid (e.g. BOD). This grid is the result of the load computation.
  199
5. Watershed zones grid (wshdzone, Chapter 7). This grid is used to determine
if two watersheds are nested. If two BMPs are located in two non-nested
watersheds, then these two BMPS are totally independent (section 7.1.2) and
can be handled at the same time.
Figure 8.55: Input files (Qual.BMPeff)
? Running Qual.BMPeff
 After adding the input files to the view, the script can be run by clicking on the
button  or by using the command Qual/BMPeff.
 The user is first asked to set the analysis extent and the cell size in the Analysis
Properties window. The following message box prompts the user for the name of the
working directory where the temporary files will be written (Figure 8.56).
 
  200
 
Figure 8.56: Choose the working directory (Qual.BMPeff)
 
 The script prompts then for the name of the new load grid, which is the output of
the computation (Figure 8.57).
 
Figure 8.57: Name of the output grid (Qual.BMPeff)
 A series of message boxes then prompt the user for the input files. The first input
is a flowdirection grid (Figure 8.58).
 
 Figure 8.58: Choose a flow direction grid (Qual.BMPeff)
  201
 The second file theme needed is a flowaccumulation grid (Figure 8.59), used to
determine the order in which the BMPs must be considered (Chapter 7). This grid is also
used to obtain the drainage areas.
 
 Figure 8.59: Choose a flowaccumulation grid (Qual.BMPeff)
 
 The next input file is the BMP point coverage (Figure 8.60).
 
 Figure 8.60: Choose a BMP point coverage (Qual.BMPeff)
 
 The attribute table of the coverage must contain an efficiency field (Figure 8.61,
BOD_eff for BOD).
 
 Figure 8.61: BMP point coverage attribute table (Qual.BMPeff)
 
  202
 The following message box (Figure 8.62) prompts the user for the name of the
field containing the efficiency values in the point coverage attribute table. The script can
handle efficiencies written as percentage or decimal fraction. Every value in a field must
be defined however with the same format.
 
 Figure 8.62: Choose a BMP efficiency field (Qual.BMPeff)
 
 The user is then asked whether he or she wants to correct the efficiencies (Figure
8.63).
 
 Figure 8.63: Correct the efficiency field (Qual.BMPeff)
 
 The correction is based on a comparison between observed and modeled
drainage areas (Chapter 7). If ?yes? is the answer to the message box, the script prompts
the user for the observed drainage areas (in acres) field (Figure 8.64).
  203
 
 Figure 8.64: Choose an observed drainage area (Qual.BMPeff)
 
 To get the values of the initial load at the BMPs locations, an initial load grid is
necessary (Figure 8.65).
 
 Figure 8.65: Choose an initial load grid (Qual.BMPeff)
 
 Finally, the user is prompted for a watershed zones grid (wshdzone, Figure 8.66).
This grid is used to define the nested watersheds (section 7.1.2).
 
 
 Figure 8.66: Choose a watershed zones grid (Qual.BMPeff)
 
  204
 The script computes then the new load after the effect of the BMPs. A message
box announces the completion of the program (Figure 8.67) and the new grid is added to
the view (Figure 8.68).
 
 Figure 8.67: Final message to user (Qual.BMPeff)
 
 
 Figure 8.68: Input and output files (Qual.BMPeff)
  205
8.4.3 Non located BMPs defined by efficiency
 The script Qual.BMPfut allows the user to model the effect of non located BMPs
defined by efficiency. This script is customized with the button  and the command
Qual/BMPfut.
? Qual.BMPfut input files
 Four tables (Figure 8.69) and nine themes plus a load grid for each constituent
considered (e.g. for two constituents BOD and COD in Figure 8.70). The last three input
themes (Flow1, Tflow01 and Lcorr_rech in Figure 8.70) are needed only if a recharge
zone is considered.
 
Figure 8.69: Input tables (Qual.BMPfut)
  206
 
Figure 8.70: Inputs themes (Qual.BMPfut)
1. Average capture volume table (acv.dbf, section 8.4.3).
2. BMP zones table (bmpzone.dbf, section 8.4.3).
3. Efficiency table (eff.dbf, section 8.4.3).
4. Direct runoff EMC table (emcrun.dbf, section 8.3.1).
5. Initial load grid (e.g. BOD, COD) for each constituent considered. The load grids are
computed with the script Qual.Load.
6. Impervious cover coverage or grid (futic, Chapter 4). The attribute table of the
coverage must contain an impervious cover field. The impervious cover can be
expressed either as percentage or as decimal fraction.
7. Flow direction grid (burn_fdr, Chapter 3).
8. BMP zones grid (futbmp_gr, Chapter 7).
  207
9. Corrected direct runoff generated in each cell (runcel1). This grid is an output of the
flow computation.
10. Buildup grid (buildup, Chapter 6). This grid contains the development rate assumed
in each cell.
11. Water land use zones grid (zone_gr, Chapter 6). Water must be given the grid code
999.
The remaining input files are required only if a recharge zone is considered.
12. Predicted total flow grid in cfs (flow1). This grid is computed with the flow
computation grid (Qual.Flow).
13. Total flow without considering recharge in cfs (tflow01).
14. Cell recharge in cfs (lcorr_rech, Chapter 5).
? Qual.BMPfut output files
 The script creates a new load grid for each constituent considered. If a recharge
zone is considered and if non discharge BMPs (e.g. COMP, SOS, Chapter 7) are located
within the study area, the script creates also a new flow grid (newflo1). This grid takes
into account the volume of water removed by the non discharge BMPs (e.g. for BOD and
COD in Figure 8.71).
  208
Figure 8.71: Inputs and outputs (Qual.BMPfut)
? Format for input tables
(a) Average capture volume table (Figure 8.72)
Average capture volumes are defined for each BMP. Linear relationships were
established between impervious cover and average capture volume (Chapter 7, Table
7.2).
ACV = a * IC + b, with 0<IC<1 and 0<ACV<1.
Two parameters, a and b, define the relationship for each BMP. The average
capture volume table is built so that each column corresponds to a BMP. The first row
contains the value of the first order coefficient a and the second row the value of the
constant b. The table has as many columns as average capture volume relationships
needed (3 in the study).
  209
Figure 8.72: Average Capture Volume table (Qual.BMPfut)
(b) BMPs zones table (Figure 8.73)
A BMP zone is an area where a specific combination of BMPs is applied. Eight
BMP zones were used in the study (Chapter 7, Table 7.1). The BMP zones table is built
such as each zone corresponds to a row. The zone number is given in the first column (1
to 8 in this case). It corresponds to the grid-code of the cell located within the zone. Each
following column corresponds to a type of BMP. The table gives the contribution of each
BMP in each zone. For example, the first zone is treated by Sand2 (44%), COMP (36%)
and SOS (remaining 20%).
 
Figure 8.73: BMPs zones table (Qual.BMPfut)
 
  210
 
 (c) Efficiency table (Figure 8.74)
 The efficiency table defines the efficiencies of each BMP for each constituent. It
indicates also the Average Capture Volume relationship for each BMP. Finally, it
contains also the flow removal efficiency if the BMP is a non discharge BMP.
 The first column indicates what the information in each row refers to (ACV, non
discharge or a specific constituent). Each following column defines the characteristics of
a type of BMP.
 The first row (ACV) allows the program to determine the average capture volume
relationship to apply to each BMP. The numbers refer to the column number in the
average capture volume table. For example, the number 2 in the first row for the SAND3
column indicates that the coefficient given in the third column (the third column has for
order 2 in the list of fields) of the average capture volume table will be use to compute
the average capture volume for the SAND3 BMP. The second row (non discharge)
contains the flow removal efficiency associated with each BMP. This efficiency is equal
to zero, except for non discharge BMPs (e.g. COMP and SOS which have a 90% flow
removal efficiency). The other rows contain the load removal efficiencies for the
constituent whose name is in the first column.
 Note that it is not necessary that the number of constituents or their order in the
efficiency and in the direct runoff table be identical. However a constituent must have the
same name in the two tables.
  211
 
Figure 8.74: Efficiency table (Qual.BMPfut)
 (d) Direct runoff EMC table (Figure 8.32)
 The direct runoff table is described in section 8.3.1. Its format must be consistent
with the format of the efficiency table (same name). Each constituent given in the
efficiency table must also be defined in the direct runoff table.
? Running Qual.BMPfut
 Once all the inputs have been added to the project, the script can be run by
clicking on the button 
 
or by using the command Qual/BMPfut.
 The user must first set the analysis extent and the cell size in the Analysis
Properties window and then choose the working directory where the temporary files will
be written (Figure 8.75).
  212
 
 
Figure 8.75: Choose a working directory (Qual.BMPfut)
 The user is then asked whether he or she wants to consider a recharge zone
(Figure 8.76).
 
Figure 8.76: Consider a recharge zone (Qual.BMPfut)
 
 The script prompts then the user for a series of tables, which must have been
added previously to the project window. The first table needed is the average capture
volume table (acv.dbf, Figure 8.77).
 
Figure 8.77: Choose an average capture volume table (Qual.BMPfut)
 
  213
 The following message box prompts the user for the BMP zones table which
defines the combination of BMPs within each zone (bmpzone.dbf, Figure 8.78).
 
 
Figure 8.78: Choose a BMP zones table (Qual.BMPfut)
 
 The efficiency table, defining the removal load efficiencies for each BMPs, is
required next (eff.dbf, Figure 8.79).
 
Figure 8.79: Choose an efficiency table (Qual.BMPfut)
 
 The last input table is the direct runoff EMC table (emcrun.dbf, Figure 8.80).
 
Figure 8.80: Choose a direct runoff EMC table (Qual.BMPfut)
  214
 The script uses then the efficiency table to create a list of the constituents for
which the new load grid can be computed. It is necessary for the constituents to be also
defined in the direct runoff EMC table. The user is prompted to choose the constituents
to model (Figure 8.81).
 
 
Figure 8.81: Choose the constituent(s) to model (Qual.BMPfut)
 
 For each selected constituent, the user is prompted for the name to give to the
new load (Figure 8.82) and for the initial load grid to use in the computations (Figure
8.83).
  215
 
Figure 8.82: Name the output load grid for BOD (Qual.BMPfut)
 
 
Figure 8.83: Choose an initial load grid for BOD (Qual.BMPfut)
 
 
 The program prompts then for a series of themes which must have been
previously added to the view. The first theme required is an impervious cover theme
(futic, Figure 8.84). It can be either a grid or a polygon coverage. If it is a polygon
coverage, then another window prompts the user for the name of the impervious cover
field.
  216
 
Figure 8.84: Choose an impervious cover theme (Qual.BMPfut)
 
 The user is prompted next for the flowdirection grid (burn_fdr, Figure 8.85).
 
Figure 8.85: Choose a flow direction grid (Qual.BMPfut)
 
 The following message box prompts the user for a BMP zones grid (futbmp_gr,
Figure 8.86). This grid is used with the BMP zones table to characterize the combination
of BMPs to apply to each cell.
 
Figure 8.86: Choose a BMP zones grid (Qual.BMPfut)
 
 The grid containing the corrected amount of runoff generated in each cell is then
required (runcel1, Figure 8.87).
  217
 
Figure 8.87: Choose a corrected cell runoff grid (Qual.BMPfut)
 The BMPs treat only newly developed area. The development in each cell is
given by a buildup grid (buildup, Figure 8.88) which contains the development averaged
over the traffic serial zones (Chapter 6).
 
 
Figure 8.88: Choose a buildup grid (Qual.BMPfut)
 
 As no pollution is generated in the water, a water land use grid (zone_gr, Figure
8.89) is required to set the EMCs in water land uses zones to zero. Water must be given
the grid code 999, which corresponds to the water code used in the traffic serial zones.
 
Figure 8.89: Choose a water land use theme (Qual.BMPfut)
  218
 The last three inputs are required only if a recharge zone is considered. They are
used to modify the load lost to the recharge zone. The first input is a predicted flow grid
(flow1, Figure 8.90). This grid is obtained by using the flow computation script.
 
Figure 8.90: Choose a predicted flow grid (Qual.BMPfut)
 The second input needed to deal with the recharge is a grid containing the total
flow without considering the recharge (tflow01, Figure 8.91).
 
Figure 8.91: Choose a total flow grid without recharge (Qual.BMPfut)
 Finally, the last input file is grid containing the flow lost to the recharge in each
cell (lcorr_rech, Figure 8.92).
 
Figure 8.92: Choose a cell recharge grid (Qual.BMPfut)
  219
 The scripts uses all the input files to compute the new load(s) accordingly to the
methodology presented in Chapter 7. A message box indicates to the user that the new
grids have been calculated and that the computation is over (Figure 8.93).
 
Figure 8.93: Final message to user (Qual.BMPfut)
 A corrected load grid has been computed for each selected constituent (Figure
8.71). If non-discharge BMPs are considered, the script creates also a new flow grid
(newflow1) which is the predicted flow (flow1) corrected with the flow removed by the
non-discharge BMPs.
  220
Chapter 9: Conclusions and Recommendations
 The goal of this research project was to determine current and future non-point
source pollution loads in Austin streams. Current flows matching observed flows at 17
USGS stations were determined in Arc/Info, and loads based on the flow were
established for 122 sites (Environmental Integrity Index sites, USGS stations and
mouths) within the study area. The effects of both located and non-located BMPs were
modeled. The results can be found in the CDROM (Appendix B). The model was finally
converted to be used in ArcView which possesses a better user interface than Arc/Info.
 This GIS-based non-point source pollution study is composed of three major
steps. First, the data characterizing the study area were gathered by monitoring, doing
field observations or looking into databases (e.g. USGS). Then the impervious
cover/runoff coefficient and impervious cover/event mean concentration relationships
were established. The data used as input to the model (precipitation, impervious cover)
or as references (observed discharges and concentrations) were derived from the
observations available. Finally, these data and relationships were used in a GIS to
compute the predicted flows and loads.
A 30m grid representation of the landscape composed of about 5 million cells
was laid over Austin, and discharge and loads generated at each cell. Weighted
flowaccumulations were done to sum the contribution of all upstream cells at each
downstream cell. Resulting flows were calibrated to match observed values at gages, and
calibration grids were created to adjust flows determined from regional relationships to
allow for local flow variations in particular watersheds.
  221
Land surface loads were computed by multiplying the flows generated in each
cell by the associated event mean concentration, and by summing the contribution of all
upstream cells at each downstream cell. In-stream loads due to erosion were assumed to
be the difference between observed and predicted loads for current conditions. A
relationship relating the erosion load per channel length to the watershed average
impervious cover was established to extrapolate erosion to the watersheds for which no
observed data were available.
The model was created and implemented for the Austin area. The same concept
and much of the same code can however be used for any location for which the
flowdirection grid can be computed and where a flow calibration can be done.
The principal difficulty in the Austin study was to model the recharge zone:
variations in the loads coming into the recharge zone modify also the load lost to the
recharge zone. Another problem arose from the fact that the flowaccumulation function
does not handle negative values. Modifying the function so that it can deal with negative
values would noticeably reduce the computation time.
 An important difference between this study and the non-point source pollution
studies previously done at CRWR was that the Austin study takes into account both
direct runoff and base flow. As the underground topography was not known, base flow
was assumed to have the same path as direct runoff, but different associated pollutant
concentrations (EMC).
 Most of the computations in this project were done in the GIS software Arc/Info
and a discussion of the methodology was presented in Chapters 5 (flow), 6 (load) and 7
  222
(BMPs). The advantage of Arc/Info over ArcView is a decreased computation time due
to the capability to run several programs at the same time. However, the programs in
Arc/Info are not very flexible, and the computing environment is not very user friendly.
 As data vary rapidly, flexibility became a growing concern. The Spatial Analyst
extension developed by ESRI offered the possibility to use grids in ArcView. At the
beginning of the study, ArcView was principally used only to display data or to retrieve
some information from the grids. Its use as a computation environment became more and
more appealing as the number of variables to be modified grew (future BMP
assumptions). ArcView also allowed the creation of a user-friendly environment
employing menus and buttons.
 The model aims at being as flexible as possible. The BMP parameters and the
EMCs can be easily modified and they do not require the analyst to recalibrate the model
(for the load, the erosion calibration is done in Excel). However, any modification of the
current land use conditions, of the precipitation value used, or of the impervious
cover/runoff coefficient relationships will require recalibration of the model. At present,
the calibration was not part of the ArcView version of the model. However, the need for
a totally integrated model in ArcView leads to the need to transpose the calibration
process from Arc/Info to ArcView. In the study, a flow correction coefficient grid
(corcoef) was defined for current conditions and the same grid was applied for future
conditions. This grid was created by using correction coefficients obtained directly from
comparisons between observed and predicted flow and by applying a standard
relationship at ungaged sites. The extrapolation formula relates linearly the flow
correction coefficient to the subwatershed average impervious cover. Since the
  223
impervious cover is modified for future conditions, so will the correction coefficients
based on the equation. The user may decide to modify the correction grid according to
the variations in the impervious cover.
 
 The ultimate objective was to create a basic tool which can be further developed
as knowledge and information concerning non-point source pollution increase. Further
development of the model should be closely related to the feedback from the users. Close
interactions with the City of Austin have allowed the model to be modified according to
the City?s expectations. Further scripts can be easily derived from the five model scripts
developed in Chapter 8. Other programs were developed for the study (separation
between direct runoff and base flow loads, load per jurisdiction type?). There are not
presented in this report as they are just a variation on a general theme.
 A principal innovation in this research is the study of the effects of Best
Management Practices on water quality in a GIS environment. Three different scenarios
were considered:
? Located BMPs defined by load removed.
? Located BMPs defined by efficiency.
? Non located BMPs defined by efficiency.
The two methods dealing with located BMPs rely on the flowaccumulation
function, since each BMP modifies the load downstream of its location. The second
approach was not implemented since the City of Austin supplied the loads removed for
the located BMPs. However it has also been very instructive to develop the more
complex method for located BMPs defined with efficiency. It was this method which
  224
triggered the conversion from Arc/Info to ArcView which offers much more flexibility in
programming, and especially the use of loops programming.
The main problem to solve for future conditions is that the exact location of the
BMPs is not known. The solution is to assume that the effect of the BMPs is not
concentrated in one location but is diffuse over an area. The analogy with located BMPs
would be, instead of considering that the load is removed at the BMP, to assume that the
load is removed in each cell where it is generated within the drainage area. The
difference being that for non located BMPs both BMP location and drainage area are not
known. It must be noted also that, since the relationships used to compute the load
removed are nonlinear, computing the load removed in each cell and then summing over
all the cells or computing the total load removed in the BMP cell will yield different
results.
Future work should concentrate on the use of finer elevation data (orthophotos)
and on the study of the elements which modify the flow path (sewer network). The
model gives the basis of a watershed based water quality non point source pollution
analysis. It should be transformed with the different needs of the users.
225
APPENDIX A
DATA DICTIONARY
226
The data dictionary contains the data used and created in the study in alphabetical
order. The data considered are coverages, shapefiles, grids, tables, Arcview project and
extension. The scripts are presented in Appendices B and C, and are not considered in the
data dictionary. The following conventions are used:
[pC] Point Coverage
[AC] Arc Coverage
[PC] Polygon Coverage
[Gr] Grid
[I] Image
[Table] Table
[Project] Avenue Project
[Ext] Avenue Extension
All coverages and grids are in State Plane coordinates, unless otherwise specified.
227
Name Feature Class Attribute Value Description
Acv.dbf Annual capture volume table. [Table] This table is an input to the script
Qual.BMPfut (non located BMPs).
Austin.tif 1:24,000 scanned map for
Austin region
[I] This map results from the projection
in state plane coordinates of a
scanned map in geographic
coordinates.
Austn_e 30m DEM for Austin East.
UTM projection
[Gr] elevation Floating point The elevation values in each grid cell
are in units of feet above sea level
Austn_w 30m DEM for Austin East.
UTM projection
[Gr] elevation Floating point The elevation values in each grid cell
are in units of feet above sea level.
Bastrpsw 30m DEM for Bastrop SW.
UTM projection
[Gr] elevation Floating point The elevation values in each grid cell
are in units of feet above sea level.
Beecave 30m DEM for Bee Cave. UTM
projection
[Gr] elevation Floating point The elevation values in each grid cell
are in units of feet above sea level.
Bmpzone.dbf BMP zones table. [Table] This table is an input to the script
Qual.BMPfut (non located BMPs).
Border Border of the study area. [PC] This coverage defines a drainage
area.
Buda 30m DEM for Buda. UTM
projection
[Gr] elevation Floating point The elevation values in each grid cell
are in units of feet above sea level.
Buildup %of zones under construction [Gr] Floating point This grid is used in the construction
load and in the future BMPs
calibration.
Burn_crk Digitized creeks coverage from
COA (creeks) completed with
the EPA Reach Files 3 (RF3)
[AC]
228
Name Feature Class Attribute Value Description
Burn_dem Original DEM raised by
10,000 ft and with the streams
burnt in
[Gr] elevation Floating point Elevation in ft (original elevation +
10,000 ft except in the streams)
Burn_fac Flow accumulation grid [Gr] Floating point The grid code for each cell
corresponds to the number of cells
upstream of this cell.
Burn_fdr Flow direction grid [Gr] integer The grid code shows which of the 8
neighboring cells lies on the path of
steepest descet. The 8 directions are
labelled as 1(E), 2(SE), 4(S), 8(SW),
16(W), 32(NW), 64(N) and 128(NE).
Burn_fil Filled grid [Gr] Floating point
Canyon_pt Barton canyon points [pC]
Canyon_wshd Barton canyon wshd
City1 Current residential BMPs [pC] Current loads
removed
121 BMPs.
Cityf1 Future residential BMPs [pC] Future loads
removed
121 BMPs. This coverage is identical
to city1. Only the attribute table is
different.
Coawshd_cv COA watersheds delineated
from the 30m DEMs.
[PC] name 45 watersheds
Coawshd_gr COA watersheds delineated
from the 30m DEMs
[Gr] integer 45 watersheds
229
Name Feature Class Attribute Value Description
Coawshd_pt COA watersheds outlets [pC] This coverage is use to find the
average characteristics of the
watersheds.
Com1pd27 Commercial BMPs [pC] 229 BMPs. Current and future loads
removed are the same.
Corcoef Flow correction coefficients
used in the calibration process.
[Gr] Floating point
Coupland 30m DEM for Coupland. UTM
projection
[Gr] elevation Floating point The elevation values in each grid cell
are in units of feet above sea level
Creedmor 30m DEM for Creedmoor.
UTM projection
[Gr] elevation Floating point The elevation values in each grid cell
are in units of feet above sea level
Creeks Principal streams of the Austin
area
[AC] Source: COA
Crk100_cv Delineated streams (threshold
100 cells)
[AC]
Crk100_gr Delineated streams (threshold
100 cells)
[Gr]
Crk1k_cv Delineated streams (threshold
1,000 cells)
[AC]
Crk1k_gr Delineated streams (threshold
100 cells)
[Gr]
Crk10k_cv Delineated streams (threshold
10,000 cells)
[AC]
Crk10k_gr Delineated streams (threshold
100 cells)
[Gr]
230
Name Feature Class Attribute Value Description
Crk500_cv Delineated streams (threshold
500 cells)
[AC]
Crk500_gr Delineated streams (threshold
100 cells)
[Gr]
Crk5k_cv Delineated streams (threshold
5,000 cells)
[AC]
Crk5k_gr Delineated streams (threshold
100 cells)
[Gr]
Dbl1 Double line roads for North
Austin
[AC] Source: COA
Dbl2 Double line roads for South
Austin
[AC] Source: COA
Dem_st Merged and projected grid of
the 27 30m DEM?s
[Gr] elevation Floating point The elevation values in each grid-cell
are in units of feet above sea level.
Drift 30m DEM for Driftwood.
UTM projection
[Gr] elevation Floating point The elevation values in each grid cell
are in units of feet above sea level
Dripsprg 30m DEM for Dripping
Spring. UTM projection
[Gr] Elevation Floating point The elevation values in each grid cell
are in units of feet above sea level
Edwards Edwards aquifer recharge and
contributing zones
[PC] Zone_name Artesian
Artesian (non
potable)
Contributing
Excluded
Recharge
Transition
USGS
recharge
Source: Barton Springs Conservation
District
231
Name Feature Class Attribute Value Description
Edw_tnris Edwards aquifer [PC] Source: TNRIS
Eff.dbf Non located BMP efficiency
table.
[Table] This table is an input to the script
Qual.BMPfut (non located BMPs).
EII EII sites [pC]
EII_wshd EII sites watersheds [PC]
Elgin_w 30m DEM for Elgin West.
UTM projection
[Gr] elevation Floating point The elevation values in each grid cell
are in units of feet above sea level
Emcbf.dbf Base flow EMC table. [Table] This table is an input to the script
Qual.load (load computation).
Emcrun.dbf Direct runoff EMC table. [Table] This table is an input to the scripts
Qual.Load (load computation) and
Qual.BMPfut (non located BMPs).
232
Name Feature Class Attribute Value Description
EPA_luse Land use of the Austin region
according to the USGS.
[PC] lucode 0
11
12
13
14
15
16
17
21
22
23
24
31
32
33
41
42
43
51
52
53
54
61
62
71
72
73
74
75
76
77
Unknown
Residential
Commercial services
Industrial
Transportation, communication
Industrial and commercial
Mixed urban or build-up land
Other urban or build-up land
Cropland and pasture
Orchards, groves, vineyards,
nurseries
Confined feeding operations
Other agricultural
Herbaceous rangeland
Shrub and brush rangeland
Mixed rangeland
Desidous forest land
Evergreen forest land
Mixed forest land
Streams and canals
Lakes
Reservoirs
Bays and estuaries
Forestred wetlands
Nonforestred wetlands
Dry salt flat
Beaches
Sandy areas other than beach
Bare exposed rock
Strip mines, quarries and gravel
Pits
Transitional areas
Mixed barren lands
233
Name Feature Class Attribute Value Description
Er_pt Erosion points. [pC]
Fin_luse Current land use based on the
COA land use (land use)
completed with the USGS land
use (EPA_luse).
[PC] Newlanduse
code
100, 113
200
300
400
500, 560
600
700
800, 870
900, 999
940
Single family
Multi-family
Commercial
Office
Industrial
Civic/educational
Park
Transportation
Vacant/undeveloped
Water/lake
Futbmp_cv Non located BMPs zones. [PC]
Futvbmp_gr Non located BMPs zones. [Gr]
Futic Future impervious cover [Gr]
Future1 Retrofit BMPs for future
conditions only
[pC] 11 BMPs.
Hamcross 30m DEM for Hammetts
Crossing. UTM projection
[Gr] elevation Floating point The elevation values in each grid cell
are in units of feet above sea level
Henly 30m DEM for Henly. UTM
projection
[Gr] elevation Floating point The elevation values in each grid cell
are in units of feet above sea level
Inlets Storm sewers inlets. [pC] Source: COA
Jollyvil 30m DEM for Jollyville. UTM
projection
[Gr] elevation Floating point The elevation values in each grid cell
are in units of feet above sea level
Juris Jurisdictions [PC]
Lakes Lakes of the Austin area [PC]
234
Name Feature Class Attribute Value Description
Landuse 1990 landuse of the Austin
region according to COA
[PC] Lucode 100
113
200
300
400
500
560
600
700
800
870
900
940
999
Single family
Mobile home
Multi-family
Commercial
Office
Industrial
Open extraction
Civic/educational
Park
Transportation
Utilities
Vacant/undeveloped
Water/lake
Unknown
Lcorr_rech Cell recharge (cfs). [Gr]
Length Flow length in feet based on
the burnt in creeks.
[Gr]
Load.xls Excel spreadsheet with current
future and construction loads
computed in the study.
[Table]
Lyttsprf 30m DEM for Lytton Springs.
UTM projection
[Gr] elevation Floating point The elevation values in each grid cell
are in units of feet above sea level
Manfiel 30m DEM for Mansfield.
UTM projection
[Gr] elevation Floating point The elevation values in each grid cell
are in units of feet above sea level
Manor 30m DEM for Manor. UTM
projection
[Gr] elevation Floating point The elevation values in each grid cell
are in units of feet above sea level
Monto 30m DEM for Montopolis.
UTM projection
[Gr] elevation Floating point The elevation values in each grid cell
are in units of feet above sea level
235
Name Feature Class Attribute Value Description
Mountcty 30m DEM for Mountain City.
UTM projection
[Gr] elevation Floating point The elevation values in each grid cell
are in units of feet above sea level
Newsites All City of Austin drainage
utility sampling sites (COA).
[pC] Source: COA
Oakhill 30m DEM for Oak Hill. UTM
projection
[Gr] elevation Floating point The elevation values in each grid cell
are in units of feet above sea level
Pflug_e 30m DEM for Pflugerville
East. UTM projection
[Gr] elevation Floating point The elevation values in each grid cell
are in units of feet above sea level
Pflug_w 30m DEM for Pflugerville
West. UTM projection
[Gr] elevation Floating point The elevation values in each grid cell
are in units of feet above sea level
Pt64_cv Upstream limit of the 64 acres
creeks.
[pC]
Qual.apr Non-point source pollution
ArcView project
[Project] This project was used to build the
water quality extension.
Qual.avx Non-point source pollution
extension.
[Ext]
Recharge Recharge zone of the Edwards
aquifer
[PC] zone North
Central
South
This coverage was used in the study.
Rech_fac Recharge flow (in cfs). [Gr]
Roads Principal streets and roads of
the Austin area.
[AC] Source: COA
Roughhol 30m DEM for Rough Holllow.
UTM projection
[Gr] Elevation Floating point The elevation values in each grid cell
are in units of feet above sea level
236
Name Feature Class Attribute Value Description
Runcoef Runoff coefficient grid for the
USGS stations.
[Gr] Used as input of flow.aml for the
calibration.
Shinhhi 30m DEM for Shingle Hills.
UTM projection.
[Gr] elevation Floating point The elevation values in each grid cell
are in units of feet above sea level
Signalhi 30m DEM for Signal Hill.
UTM projection.
[Gr] elevation Floating point The elevation values in each grid cell
are in units of feet above sea level
Stations Sites studied in the project. [pC] This point coverage contains the
points located at the EII sites, at the
USGS stations and at the mouths.
Stormsew Storm sewers. [AC] Source: COA
Texas Texas counties. [PC] name
USGS USGS stations used as
references for model
calibration
[pC] Observed flow
(cfs)
17 stations.
USGS_quad USGS 1:24,000 quadrangles
corresponding to the DEMs
used in the project.
[PC] Name
USGS_wshd USGS stations watersheds [PC]
Utley 30m DEM for Utley. UTM
projection.
[Gr] elevation Floating point The elevation values in each grid cell
are in units of feet above sea level
Water_gr Merged streams and lakes at
their original elevation value.
[Gr] elevation Floating point The elevation values in each grid-cell
are in units of feet above sea level.
Webber 30m DEM for Webberville.
UTM projection.
[Gr] elevation Floating point The elevation values in each grid cell
are in units of feet above sea level
Wqexempt27 Water quality exempt zones. [PC] Source: COA
Wqpza27 Water quality protection zones [PC] Source: COA
237
Name Feature Class Attribute Value Description
Wsheds Watersheds of the Austin area [PC] name Source: COA
Wshd1k_cv Delineated watersheds of the
Austin area (threshold 1,000
cells).
[PC]
Wshd1k_gr Delineated watersheds of the
Austin area (threshold 1,000
cells).
[Gr]
Wshd10k_cv Delineated watersheds of the
Austin area (threshold 10,000
cells).
[PC]
Wshd10k_gr Delineated watersheds of the
Austin area (threshold 10,000
cells).
[Gr]
Wshd500_cv Delineated watersheds of the
Austin area (threshold 500
cells).
[PC]
Wshd500_gr Delineated watersheds of the
Austin area (threshold 500
cells).
[Gr]
Wshd5k_cv Delineated watersheds of the
Austin area (threshold 5,000
cells).
[PC]
Wshd5k_gr Delineated watersheds of the
Austin area (threshold 5,000
cells).
[Gr]
Yeager 30m DEM for Yeager Creek.
UTM projection.
[Gr] elevation Floating point The elevation values in each grid cell
are in units of feet above sea level
238
Name Feature Class Attribute Value Description
Zones Traffic serial zones [PC] integer This coverage is used to determine
future impervious cover and future
land use..
205_st EPA Reach File 3 (RF3)
12090205
[AC] The ID number corresponds to the
Hydrologic Unit Code (HUC).
301_st EPA Reach File 3 (RF3)
12090301
[AC] The ID number corresponds to the
Hydrologic Unit Code (HUC).
64crk Delineated streams (threshold
64 acres)
[AC]
239
239
APPENDIX B
CDROM DOCUMENTATION
240
CDROM Documentation
The CDROM contains the same data as the data dictionary but also the Avenue
scripts. The data are not classified by alphabetical order but by theme.All coverages and
grids are in Texas State Plane coordinates except otherwise specified.
                          COORDINATE SYSTEM DESCRIPTION
Projection           STATEPLANE
Zone                       5376
Datum                     NAD27
Units                      FEET             Spheroid             CLARKE1866
Parameters:
The following listing describes the contents of each section of the CDROM. The
following conventions are used :
[pC] Point Coverage
[AC] Arc Coverage
[PC] Polygon Coverage
[Gr] Grid
[I] Image
[Table] Table
[Script] Avenue Script
[Project] Avenue Project
[Ext] Avenue Extension
The source is given after the definition of the data.
ex : creeks [AC] principal streams in the Austin region (COA).
COA stands for City Of Austin.
Directories
COA_DATA: coverages from external sources.
DEM: DEMs and data derived from it.
MODEL: programs and data used to run the model
241
DIRECTORY COA_DATA
? bmp
? city1 [pC] Current residential BMPs with loads removed (COA).
? cityf1 [pC] Future residential BMPs (same coverage as city1 but different
values for the loads removed) (COA).
? com1pd27 [pC] Commercial BMPs (same values for current and future
conditions).
? future1 [pC] Retrofit BMPs (future conditions only).
? edwards
? edw_tnris [PC] Edwards aquifer (Texas Natural Resources Information
System).
? edwards [PC] Edwards aquifer recharge and contributing zones in Austin
(Barton Springs Conservation District).
? recharge [PC] recharge zone coverage used in the study.
? landuse
? epa_luse [PC] land use coverage used to complete the city coverage (EPA).
? fin_luse [PC] completed current land use used in the study for current
conditions.
? landuse [PC] existing land use of the city (1990 version (COA).
? zones [PC] Traffic serial zones (COA). The future impervious cover and land
use are based on that coverage.
? political
? map
Both of the following files are needed to properly display the map.
c143 austinst.tif [I] USGS 1:24,000 scanned maps of Austin in state plane
coordinates. This map was scanned and the resulting image in
geographic coordinates was projected in state plane coordinates
(Horizons Technologies, Inc.).
c143 austin.tfw displays information such as size, localization
? juris [PC] jurisdiction coverage (COA).
? texas [PC]  Texas counties (TNRIS).
? usgs_quad [PC] USGS quadrangles for the study area.
? wqexempt27 [PC] Water quality exempt zones (COA).
? wqpza27 [PC] Water quality protection zones (COA).
? wsheds [PC] principal watersheds of Austin. They are named under the
attribute Name (COA).
242
? road
? dbl1 & dbl2 [AC]double line street files. dbl1 covers the northern part of the
city and dbl2 the southern part (COA).
? roads [AC] principal streets and roads of Austin (COA).
? sewers
? inlets [pC] storm sewer inlets (COA).
? stormsew [AC] storm sewers (COA).
? stations
? 64acres
c143 64crk [AC] streams (64 acres threshold).
c143 pt64_cv [pC] upstream limit of the 64 acres creeks.
? canyon
c143 canyon_pt [pC] Barton canyon points.
c143 canyon_wshd [PC] Barton canyon watersheds.
? coawshd_pt [pC] City of Austin delineated watersheds (coawshd_cv)
outlets.
? eii
c143 eii [pC] Environmental Integrity Index sites.
c143 eii_wshd [PC] Environmental Integrity Index watersheds.
? er_pt [pC] Erosion points.
? newsites [pC] all City of Austin drainage utility sampling sites (COA).
? stations [pC] sites studied. This point coverage contains the EII sites, the
USGS stations and the creeks mouths where flows and loads have been
determined in the study.
? usgs
c143 usgs [pC] USGS stations in Austin region with a period of record of at
least one year.
c143 usgs_wshd [PC] USGS watersheds.
? streams
? creeks [AC] principal streams in the Austin Region (COA).
? lakes [PC] lakes of Austin (COA).
? rf3
c143 205_st [AC] EPA reach file 3 for HUC (hydrologic unit code) 12090205
(EPA).
c143 301_st [AC] EPA reach file 3 for HUC 12090301 (EPA).
243
DIRECTORY DEM (30M CELL SIZE)
This directory contains the inputs and outputs of the burn-in process and of the
watershed and stream delineation.
? border [PC] border of the Austin region.
? burn_crk [AC] used to build the creeks grid (WATER_GR) used in the burn-in
process. The coverage supplied by the City of Austin has been completed by the EPA
RF3 coverage.
? burn_dem [Gr] : This DEM was built by adding 10,000 ft to DEM_ST and by
merging the resulting grid with the grid water_gr.
? burn_fac [Gr] flow accumulation grid (based on burn_dem).
? burn_fdr [Gr] flow direction grid (based on burn_dem).
? burn_fil [Gr] burn_dem whose sinks have been filled.
? coa_wshd [PC] principal watersheds. It can be compared with the coverage given by
the city.
? coawshd_cv [PC] delineated watersheds.
? coawshd_gr [Gr] delineated watersheds. The grid code represents the
coawshd_cv-id.
? deln_crk
This directory contains grids and coverages which were created by applying the Arc/Info
Grid tools to the 30m Digital Elevation Model covering the Austin area.
? crk100_cv [AC] streams (100 cells threshold).
? crk100_gr [Gr] streams (100 cells threshold).
? crk10k_cv [AC] streams (10,000 cells threshold).
? crk10k_gr [Gr] streams (10,000 cells threshold).
? crk1k_cv [AC] streams (1,000 cells threshold).
? crk1k_gr [Gr] streams (1,000 cells threshold).
? crk500_cv [AC] streams (500 cells threshold).
? crk500_gr [Gr] streams (500 cells threshold).
? crk5k_cv[AC] streams (5,000 cells threshold).
? crk5k_gr [Gr]streams (5,000 cells threshold).
244
? deln_wshd
? wshd10k_cv [PC] watersheds (10,000 cells threshold).
? wshd10k_gr [Gr] watersheds (10,000 cells threshold).
? wshd1k_cv [PC] watersheds (1,000 cells threshold).
? wshd1k_gr [Gr] watersheds (1,000 cells threshold).
? wshd500_cv [PC] watersheds (500 cells threshold).
? wshd500_gr [Gr] watersheds (500 cells threshold).
? wshd5k_cv [PC] watersheds (5,000 cells threshold).
? wshd5k_gr [Gr] watersheds (5,000 cells threshold).
? dem30m
This directory contains the original 30m DEMs (27) received from Vernon F. Meyer
and Associates, Inc which have ben processed towards grids. The DEMs are in the UTM
projection system. The elevation values in each grid-cell are in units of feet above sea
level.
? Austn_e [Gr] Austin East.
? Austn_w [Gr] Austn_w.
? Bastrpsw [Gr] Bastrop SW.
? Beecave [Gr] Beecave.
? Buda [Gr] Buda.
? Coupland [Gr] Coupland.
? Creedmor [Gr] Creedmoor.
? Drift [Gr] Driftwood.
? Dripsprg [Gr] Dripping Springs.
? Elgin_w [Gr] Elgin West.
? Hamcross [Gr] Hammetts Crossing.
? Henly [Gr] Henly.
? Jollyvil [Gr] Jollyville.
? Lyttsprf [Gr] Lytton Spring.
? Manfiel [Gr] Manfiel.
? Manor [Gr] Manor.
? Monto [Gr] Montopolis.
? Mountcty [Gr] Mountain City.
? Oakhill [Gr] Oak Hill.
? Pflug_e [Gr] Pflugerville East.
? Pflug_w [Gr] Pflugerville West.
? Roughol [Gr] Rough Hollow.
? Shinhhi [Gr] Shingle Hills.
? Signalhi [Gr] Signal Hill.
? Utley [Gr] Utley.
? Webber [Gr] Webberville.
? Yeager [Gr] Yeager Creek.
245
? dem_st [Gr] this DEM was created by merging 27 30m Digital Elevation Models and
by projecting the resulting grid in state plane coordinates (Vernon F. Meyer and
Associates, Inc.).
? water_gr [Gr] creeks grid used in the burn-in process.
DIRECTORY MODEL
? buildup [Gr] buildup grid.
? burn_fac [Gr] flowaccumulation grid.
? burn_fdr [Gr] flowdirection grid.
? corcoef [Gr] flow correction grid.
? fin_luse [PC] current land use coverage (COA).
? futic [Gr] future impervious cover.
? Length [Gr] Flow length in feet grid based on the creeks burnt in.
? lcorr_rech [Gr] cell recharge.
? load.xls [Table] Excel spreadsheet containing current, future and construction loads
computed in the study at the locations of the points in the point coverage stations.
? futbmp_gr [Gr] non located BMP zones.
? futbmp_cv [PC] non located BMP zones.
? qual.apr [Project] ArcView project used to create the non-point source pollution
extension.
? qual.avx [Ext] Non-point source pollution extension.
? rech_fac [Gr] recharge flow.
246
? Scripts
? Ext_inst.ave [Script] Extension.Install.
? Ext_make.ave [Script] Extension.Make.
? Ext_uninst.ave [Script] Extension.Uninstall.
? Qual_add.ave [Script] Qual.Addpoint.
? Qual_avg.ave [Script] Qual.Average.
? Qual_bmpeff .ave [Script] Qual.BMPeff.
? Qual_bmpeffc_ave [Script] Qual.BMPeffcpt.
? Qual_bmpfut.ave [Script] Qual.BMPfut.
? Qual_bmpload.ave [Script] Qual.BMPload.
? Qual_creek.ave [Script] Qual.Creek.
? Qual_creeklim.ave [Script] Qual.Creeklim.
? Qual_del.ave [Script] Qual.Delete.
? Qual_flow.ave [Script] Qual.Flow.
? Qual_hydro.ave [Script] Qual.HydroZdlsv.
? Qual_join.ave [Script] Qual.Join.
? Qual_load.ave [Script] Qual.Load.
? Qual_merge.ave [Script] Qual.Mergetheme.
? Qual_pick.ave [Script] Qual.Pick.
? Qual_wshd.ave  [Script] Qual.Wshd.
? Qual_zone.ave [Script] Qual.Zonalmean.
? tables
? acv.dbf [table] annual capture volume table.
? bmpzone [table] BMP zones table.
? eff.dbf [table] non located BMP efficiency table.
? emcbf.dbf [table] base flow EMC table.
? emcrun.dbf [table] direct runoff EMC table.
? wshdzone [Gr] watershed zones grid used to define the nested watersheds.
watersheds)
? zone_gr [Gr] traffic serial zone grid used to locate water land use (grid-code 999).
247
APPENDIX C
AVENUE SCRIPTS
248
SCRIPTS
Script Name Function
Extension.Install Installs the extension.
Extension.Make Creates the extension file qual.avx.
Extension.Uninstall Uninstalls the extension.
Qual.Addpoint Creates or adds a point to a point coverage.
Qual.Average Computes the average based on drainage area.
Qual.BMPeff Computes the load removed by located BMPs defined by
removal efficiency.
Qual.BMPeff_cpt Subroutine to BMP_eff.
Qual.BMPfut Computes the new load after the effect of non located BMPs
defined by removal efficiency.
Qual.BMPload Computes the load removed by located BMPs defined by load
removed.
Qual.Creek Delineates creeks for a flowaccumulation threshold.
Qual.Creeklimit Creates gridpoints representing the upstream limit of the creeks
for a flowaccumulation threshold.
Qual.Delete Deletes several fields in a table.
Qual.Flow Computes the discharge (cfs).
Qual.HydroZdlsv Dangling polygons.
Qual.Join Permanently joins two tables.
Qual.Load Computes the load (kg/yr).
Qual.Mergetheme Merges two themes.
Qual.Pick Retrieves the values of  grids for points in a point coverage.
Qual.Wshd Delineates watersheds for points in a point coverage.
Qual.Zonalmean Computes the averages within a zone.
249
?Script: Extension.Install
?----------------------------
?--- Creation information ---
?----------------------------
?Name: Extension.Uninstall
?Version: 1.0
?Creation date: 11/17/97
?Author: Christine Dartiguenave
?Center for Research in Water Resources
?The University of Texas at Austin
?darti@crwr.utexas.edu
?---------------------------
?--- Purpose/Description ---
?---------------------------
?Uninstall the water quality extension.
?The self object for this script is the extension.
?The first object is the view, then the button and the menu
?Check if there is an active project
  if (av.getproject = nil) then
   return nil
  end
?Add the buttons at the end
thebuttonbar = av.getproject.findgui("View").getbuttonbar
thebutton1 = thebuttonbar.findbyname("Qual.Flow")
  if (thebutton1 = nil) then
    thebuttonbar.add(self.get(0),999)
  end
thebutton2 = thebuttonbar.findbyscript("Qual.Load")
  if (thebutton2 = nil) then
    thebuttonbar.add(self.get(1),999)
  end
thebutton3 = thebuttonbar.findbyscript("Qual.BMPload")
  if (thebutton3 =nil) then
    thebuttonbar.add(self.get(2),999)
  end
thebutton4 = thebuttonbar.findbyscript("Qual.BMPeff")
  if (thebutton4 =nil) then
    thebuttonbar.add(self.get(3),999)
  end
thebutton6 = thebuttonbar.findbyscript("Qual.BMPfut")
  if (thebutton6 =nil) then
    thebuttonbar.add(self.get(4),999)
  end
thebutton7 = thebuttonbar.findbyscript("Qual.Average")
  if (thebutton7 =nil) then
    thebuttonbar.add(self.get(5),999)
  end
thebutton8 = thebuttonbar.findbyscript("Qual.Zonalmean")
  if (thebutton8 =nil) then
    thebuttonbar.add(self.get(6),999)
  end
thebutton9 = thebuttonbar.findbyscript("Qual.Wshd")
  if (thebutton9 =nil) then
    thebuttonbar.add(self.get(7),999)
  end
thebutton10 = thebuttonbar.findbyscript("Qual.Creek")
  if (thebutton10 =nil) then
    thebuttonbar.add(self.get(8),999)
  end
thebutton11 = thebuttonbar.findbyscript("Qual.Creeklimit")
  if (thebutton11 =nil) then
    thebuttonbar.add(self.get(9),999)
  end
thebutton12 = thebuttonbar.findbyscript("Qual.Pick")
  if (thebutton12 =nil) then
    thebuttonbar.add(self.get(10),999)
  end
thebutton13 = thebuttonbar.findbyscript("Qual.Mergetheme")
  if (thebutton13 =nil) then
    thebuttonbar.add(self.get(11),999)
  end
thebutton14 = thebuttonbar.findbyscript("Qual.HydroZdlsv")
  if (thebutton14 =nil) then
    thebuttonbar.add(self.get(12),999)
  end
250
thebuttonbar1 = av.getproject.findgui("Table").getbuttonbar
thebutton15 = thebuttonbar1.findbyscript("Qual.Delete")
  if (thebutton13 =nil) then
    thebuttonbar1.add(self.get(13),999)
  end
thebutton16 = thebuttonbar1.findbyscript("Qual.Join")
  if (thebutton14 =nil) then
    thebuttonbar1.add(self.get(14),999)
  end
?Add the tool
thetoolbar = av.getproject.findgui("view").gettoolbar
thetool = thetoolbar.findbyscript("qual.addpoint")
  if (thetool =nil) then
    thetoolbar.add(self.get(15),999)
  end
?Add the menus
themenubar = av.getproject.findgui("View").getmenubar
themenu1 = themenubar.findbylabel("Qual")
  if (themenu1 =nil) then
    themenubar.add(self.get(16),999)
  end
themenu2 = themenubar.findbylabel("QualTools")
  if (themenu2 =nil) then
    themenubar.add(self.get(17),999)
  end
themenubar2 = av.getproject.findgui("Table").getmenubar
themenu3 = themenubar2.findbylabel("QualTable")
  if (themenu3=nil) then
    themenubar2.add(self.get(18),999)
  end
?Script: Extension.Make
?----------------------------
?--- Creation information ---
?----------------------------
?Name: Extension.make
?Version: 1.0
?Creation date: 11/17/97
?Author: Christine Dartiguenave
?Center for Research in Water Resources
?The University of Texas at Austin
?darti@crwr.utexas.edu
?---------------------------
?--- Purpose/Description ---
?---------------------------
?Create the water quality extension
theproject=av.getproject
?install and uninstall scripts
theinstallscript=theproject.finddoc("Extension.Install").getscript
theuninstallscript=theproject.finddoc("Extension.Uninstall").getscript
?make sure install and unistall script are compiled
if ((theinstallscript = nil ) or ( theuninstallscript = nil )) then
  Msgbox.info("Install or Uninstall script are not compiled","")
  return nil
end
?make the extension, extension files typically have a .avx suffix
myextension = extension.make("c:\temp\qual.avx".asfilename, "Water quality",
theinstallscript, theuninstallscript, {})
?Add the view object called "my view"
?myextension.add(theproject.finddoc("Test"))
?Get the new button items and add them to extension
theviewbuttonbar = theproject.findGui("View").getbuttonbar
thebutton1 = theviewbuttonbar.findbyscript("Qual.Flow")
thebutton2 = theviewbuttonbar.findbyscript("Qual.Load")
thebutton3 = theviewbuttonbar.findbyscript("Qual.BMPload")
thebutton4 = theviewbuttonbar.findbyscript("Qual.BMPeff")
thebutton6 = theviewbuttonbar.findbyscript("Qual.BMPfut")
thebutton7 = theviewbuttonbar.findbyscript("Qual.Average")
thebutton8 = theviewbuttonbar.findbyscript("Qual.Zonalmean")
thebutton9 = theviewbuttonbar.findbyscript("Qual.Wshd")
thebutton10 = theviewbuttonbar.findbyscript("Qual.Creek")
thebutton11 = theviewbuttonbar.findbyscript("Qual.Creeklimit")
251
thebutton12 = theviewbuttonbar.findbyscript("Qual.Pick")
thebutton13 = theviewbuttonbar.findbyscript("Qual.Mergetheme")
thebutton14 = theviewbuttonbar.findbyscript("Qual.HydroZdlsv")
thetablebuttonbar = theproject.findGui("Table").getbuttonbar
thebutton15 = thetablebuttonbar.findbyscript("Qual.Delete")
thebutton16 = thetablebuttonbar.findbyscript("Qual.Join")
myextension.add(thebutton1)
myextension.add(thebutton2)
myextension.add(thebutton3)
myextension.add(thebutton4)
myextension.add(thebutton6)
myextension.add(thebutton7)
myextension.add(thebutton8)
myextension.add(thebutton9)
myextension.add(thebutton10)
myextension.add(thebutton11)
myextension.add(thebutton12)
myextension.add(thebutton13)
myextension.add(thebutton14)
myextension.add(thebutton15)
myextension.add(thebutton16)
?Get the new tool item and add it to the extension
theviewtoolbar = theproject.findgui("View").gettoolbar
thetool = theviewtoolbar.findbyscript("Qual.Addpoint")
myextension.add(thetool)
?Get the new menu items and add them to the extension
theviewmenubar = theproject.findGui("View").getmenubar
themenu1 = theviewmenubar.findbylabel("Qual")
themenu2 = theviewmenubar.findbylabel("QualTools")
thetablemenubar = theproject.findGui("Table").getmenubar
themenu3 = thetablemenubar.findbylabel("QualTable")
? Make it the last items
myextension.add(themenu1)
myextension.add(themenu2)
myextension.add(themenu3)
?add necessary scripts to the extension, assumes all scripts
?are prefixed with "Qual."
for each d in av.getproject.getdocs
  if (d.is(sed) and (d.getname.left("qual".count+1) = "Qual.")) then
   myextension.add(d.getscript)
  end
end
?Add a description to appear in the extension dialog
myextension.setabout("Water Quality extension")
?Commit change to the extension
myextension.commit
?Script: Extension.Uninstall
?----------------------------
?--- Creation information ---
?----------------------------
?Name: Extension.uninstall
?Version: 1.0
?Creation date: 11/17/97
?Author: Christine Dartiguenave
?Center for Research in Water Resources
?The University of Texas at Austin
?darti@crwr.utexas.edu
?---------------------------
?--- Purpose/Description ---
?---------------------------
?Installs the water quality extension.
?The self object for this script is the extension
?Check if there is an active project
  if (av.getproject = nil) then
    return nil
  end
?No need to uninstall if project is closing
  if (av.getproject.isclosing) then
    return nil
  end
252
?Remove the buttons
?V i e w
thebuttonbar=av.getproject.findGUI("View").getbuttonbar
thebuttonbar.remove(self.get(0))
thebuttonbar.remove(self.get(1))
thebuttonbar.remove(self.get(2))
thebuttonbar.remove(self.get(3))
thebuttonbar.remove(self.get(4))
thebuttonbar.remove(self.get(5))
thebuttonbar.remove(self.get(6))
thebuttonbar.remove(self.get(7))
thebuttonbar.remove(self.get(8))
thebuttonbar.remove(self.get(9))
thebuttonbar.remove(self.get(10))
thebuttonbar.remove(self.get(11))
thebuttonbar.remove(self.get(12))
?T a b l e
thebuttonbar=av.getproject.findGUI("Table").getbuttonbar
thebuttonbar.remove(self.get(13))
thebuttonbar.remove(self.get(14))
?Remove the tool
thetoolbar=av.getproject.findgui("view").gettoolbar
thetoolbar.remove(self.get(15))
?Remove the menus
themenubar=av.getproject.findgui("View").getmenubar
themenubar.remove(self.get(16))
themenubar.remove(self.get(17))
themenubar2=av.getproject.findgui("Table").getmenubar
themenubar2.remove(self.get(18))
?Script: Qual.Addpoint
?
?
?----------------------------
?--- Creation information ---
?----------------------------
?
?Name: Qual.Addpoint
?Version: 1.0
?Date: 5/20/97
?Author: Christine Dartiguenave
?        Center for Research in Water Resources
?        The University of Texas at Austin
?        darti@crwr.utexas.edu
?
?---------------------------
?--- Purpose/Description ---
?---------------------------
?
?Create a point coverage in Arcview or add new points to a point coverage.
?The snap command enables to snap the point to a line coverage.
?--------------------
?--- Get the View ---
?--------------------
theview=av.getactivedoc
?-----------------------
?--- Enter the point ---
?-----------------------
?
ThePntV=theView.GetDisplay.ReturnUserPoint
?---------------------------------------------------
?--- Add the point to an existing point coverage ---
?---------------------------------------------------
?
rel = msgbox.yesno("Do you want to create a new point coverage?" , Script.The.GetName
,true)
  if (rel.not) then
    if (theView.GetThemes.Count = 0) then
      msgbox.error("No active themes found", Script.The.GetName)
      exit
    end
    stList=list.Make
      for each thm in TheView.GetThemes
        if(thm.is(Ftheme))then
          if (thm.GetFtab.GetShapeClass.GetClassName="Point")then
            stList.add(thm)
          end
        end
      end
253
    stthm=Msgbox.ChoiceAsString(stList,"Choose a point coverage.",Script.The.GetName)
      if(stthm=nil)then
        exit
      end
    else
?-------------------------------------
?--- Creating a new point coverage ---
?-------------------------------------
outFName = av.GetProject.MakeFileName("Point", "shp")
thefname = FileDialog.Put(outFName, "*.shp", "New Point Coverage")
if (thefName = Nil) then
  exit
end
          theFtab=Ftab.MakeNew(theFName,point)
          PntID=Field.Make("Id",#FIELD_Short,4,0)
          theftab.seteditable(true)
          theFtab.AddFields({PntID})
          stthm=Ftheme.Make(theFtab)
          TheView.AddTheme(stthm)
          stthm.setvisible(true)
       end
 que1 = msgbox.yesno("Snap point to a line coverage?" , Script.The.GetName , true)
?------------
?--- Snap ---
?------------
    if (que1) then
        lList=list.Make
          for each thm in TheView.GetThemes
            if(thm.is(Ftheme))then
              if(thm.GetFtab.GetShapeClass.GetClassName="Polyline")then
                lList.add(thm)
              end
            end
          end
       lthm=Msgbox.ChoiceAsString(lList,"Choose a line coverage.",Script.The.GetName)
       if(lthm=nil)then
         exit
       else
        lthmName=lthm.GetName
       end
     lftab=lThm.GetFtab
     lshp=lftab.FindField("Shape")
     recs=lthm.FindByPoint(ThePntV)
        if(recs.IsEmpty.not)then
          rec=recs.get(0)
          TheShpV=lftab.ReturnValue(lShp,rec)
          theline=theshpv.aspolyline
          m=theline.querypointdistance(thepntv,1000)
          newline=theline.returndensified(10000)
          multi=newline.asmultipoint
          val=thepntv.snap(multi,1000)
            if (val) then
              msgbox.info("Snapped",Script.The.GetName)
            end
         else
            msgbox.info("No line theme found",Script.The.GetName)
            exit
         end
end
theftab = stthm.getftab
theftab.seteditable(true)
therecno = theftab.addrecord
theshapef = theftab.findfield("Shape")
theftab.setvalue(theshapef, therecno, thepntv)
theftab.seteditable(false)
?------------------------------------------
?--- Enter the parameters for the point ---
?------------------------------------------
fieldlist=theftab.getfields
n=theftab.GetNumRecords
m=fieldlist.count
  p=m-1
254
  i=0
  minnum=10.min(p)
  newfieldlist=list.make
  for each i in 1..minnum
    thefield=fieldlist.get(i).asstring
    newfieldlist.add(thefield)
    i=i+1
  end
    q=minnum-1
    defaultlist=list.make
 if (newfieldlist.get(0)="id") then
defaultlist={n.asstring}
    if (q > 1) then
      for each i in 1..q
        defaultlist.add("-")
        i=i+1
      end
    end
  else
     if (p>0) then
       for each i in 1..minnum
         defaultlist.add("-")
         i=i+1
       end
     end
  end
    param = MsgBox.MultiInput( stthm.asstring++"fields", Script.The.GetName, newfieldlist,
defaultlist)
    if (param=nil) then
      exit
    end
theftab.seteditable(true)
i=1
j=1
  for each i in 1..n
    for each j in 1..minnum
       ptfield=fieldlist.get(j)
       theftab.setvalue(ptfield,therecno,param.get(j-1))
       j=j+1
    end
    i=i+1
  end
theftab.seteditable(false)
msgbox.info("End",Script.The.GetName)
?-----------
?--- End ---
?-----------
? Script Qual.Average
?
?----------------------------
?--- Creation information ---
?----------------------------
?
?Name: Qual.Average
?Version: 1.0
?Date: 6/26/97
?Author: Christine Dartiguenave
?        Center for Research in Water Resources
?        The University of Texas at Austin
?        darti@crwr.utexas.edu
?
?---------------------------
?--- Purpose/Description ---
?---------------------------
?
?This program computes the average value at any cell, based on its drainage area.
?--------------------
?--- Get the View ---
?--------------------
?
theView=av.GetActiveDoc
?----------------------
?--- Get the themes ---
?----------------------
?
if (theView.GetThemes.Count = 0) then
   msgbox.error("No themes found", "IC")
   exit
end
255
?Choose a theme (grid or polygon coverage)
ThemeList=list.Make
for each thm in TheView.GetThemes
  if(thm.is(Ftheme))then
     if(thm.GetFtab.GetShapeClass.GetClassName="Polygon")then
       ThemeList.add(thm)
     end
  end
  if(thm.is(Gtheme)) then
    ThemeList.add(thm)
   end
end
thethm=Msgbox.ChoiceAsString(ThemeList,"Choose a value theme.",Script.The.GetName)
    if(thethm=nil)then
      exit
    end
?Flow direction grid
gridList=list.Make
 for each thm in TheView.GetThemes
    if(thm.is(Gtheme))then
       gridList.add(thm)
    end
 end
fdrthm=Msgbox.ChoiceAsString(gridList,"Choose a flow direction
grid.",Script.The.GetName)
    if(fdrthm=nil)then
      exit
    end
fdirgrid=fdrthm.getgrid
 ?Flow accumulation grid
 facthm=Msgbox.ChoiceAsString(gridList,"Choose a flow accumulation
grid.",Script.The.GetName)
    if(facthm=nil)then
      exit
    end
facgrid=facthm.getgrid
?Name the new grid
outFname = av.GetProject.MakeFileName("grid", "")
aname = FileDialog.Put(outFName, "", Script.The.GetName)
if (aname = Nil) then
  exit
end
?--------------------------------------
?--- Alternative (grid or coverage) ---
?--------------------------------------
if (thethm.is(Ftheme))then
?---------------------
?--- Get the table ---
?---------------------
?
theFtab=thethm.getFtab
fieldlist=theftab.getfields
thefield = MsgBox.choiceAsString(fieldlist, "Choose a value field" , Script.The.GetName)
if (thefield=nil) then
  MsgBox.Info("No field selected", Script.The.GetName)
  exit
end
?
?-----------------------
?--- Convert to grid ---
?-----------------------
theFtab.seteditable(true)
cellsize=fdirgrid.getcellsize
box=fdirgrid.getextent
aPrj = theView.GetProjection
thegrid = Grid.MakeFromFTab(theFTab, aPrj, theField, {cellSize, box})
 else
   thegrid=thethm.getgrid
 end
?-------------------------
?--- Flow accumulation ---
?-------------------------
256
thefacgrid = (fdirgrid.flowaccumulation(thegrid))
theavg1grid=thefacgrid/facgrid
thelist1=list.make
thelist1.add(thegrid)
theavggrid=theavg1grid.merge(thelist1)
theavggrid.savedataset(aname)
theavgthm = gtheme.make(theavggrid)
theview.addtheme(theavgthm)
theavgthm.setlegendvisible(false)
?final message to user
message = "Average grid created."
msgbox.info(message,Script.The.GetName)
?-----------
?--- End ---
?-----------
?Script Qual.BMPeff
?
?----------------------------
?--- Creation information ---
?----------------------------
?
?Name: Qual.BMPeff
?Version: 1.0
?Date: 5/21/97
?Modified: 10/16/97
?Author: Christine Dartiguenave
?        Center for Research in Water Resources
?        The University of Texas at Austin
?        darti@crwr.utexas.edu
?
?---------------------------
?--- Purpose/Description ---
?---------------------------
?
?This program computes the load after the action of
? located BMPs defined by their efficiency.
?--------------------
?--- Get the View ---
?--------------------
?
theView=av.GetActiveDoc
?Check if there are any theme in the view.
if (theView.GetThemes.Count = 0) then
  msgbox.error("No themes found", Script.The.GetName)
  exit
end
?---------------------------
?--- Set analysis extent ---
?---------------------------
? bring up the AnalysisPropertiesDialog
theAE = AnalysisPropertiesDialog.Show(theView,FALSE,"Analysis Properties")
  if (theAE=nil) then
    exit
  end
theExtent = Rect.Make(0@0,1@1)
theCellSize = 1
if ((theAE.GetExtent(theExtent) <> #ANALYSISENV_VALUE) or
    (theAE.GetCellSize(theCellSize) <> #ANALYSISENV_VALUE)) then
  theCE = AnalysisPropertiesDialog.Show(theView,TRUE,"Analysis Extent")
  ? check for Cancel from dialog
  if (theCE = NIL) then
    return NIL
  end
  theCE.GetCellSize(theCellSize)
  theCE.GetExtent(theExtent)
end
Grid.SetAnalysisCellSize ( #GRID_ENVTYPE_VALUE , theCellSize )
Grid.SetAnalysisExtent ( #GRID_ENVTYPE_VALUE , theextent )
?-----------------------------
?--- Set working directory ---
?-----------------------------
aProject=av.GetProject
257
defaultdir=aProject.GetWorkDir
inputdir=MsgBox.Input("Choose the working
directory.",Script.The.GetName,defaultdir.asstring)
  if (inputdir=nil) then
  else
    aDirName = inputdir.asfilename
    aProject.SetWorkDir (aDirName)
  end
?------------------
?--- Get themes ---
?------------------
?Name the new grid
outFName = av.GetProject.MakeFileName("newload", "")
aname = FileDialog.Put(outFName, "", "New load grid")
if (aname = Nil) then
  exit
end
?List the available grids
ThmList=list.Make
  for each thm in TheView.GetThemes
    if(thm.is(Gtheme))then
      ThmList.add(thm)
    end
  end
?Choose a flow direction grid
    fdirthm=Msgbox.ChoiceAsString(ThmList,"Choose a flow direction
grid",Script.The.GetName)
      if(fdirthm=nil)then
        exit
      end
fdirgrid=fdirthm.getgrid
?Choose a flow accumulation grid
  facthm=Msgbox.ChoiceAsString(ThmList,"Choose a flow accumulation
grid",Script.The.GetName)
    if(facthm=nil)then
      exit
    end
  facgrid=facthm.getgrid
?List the available point coverages
Thm1List=list.Make
  for each thm in TheView.GetThemes
    if(thm.is(Ftheme))then
      if(thm.GetFtab.GetShapeClass.GetClassName="Point")then
        Thm1List.add(thm)
      end
    end
  end
?Choose the BMPs point coverage
Ptthm=Msgbox.ChoiceAsString(Thm1List,"Choose a BMPs point
coverage",Script.The.GetName)
  if(Ptthm=nil)then
    exit
  end
?Get the point attribute table
pttab = Ptthm.getftab
  if (pttab = nil) then
    msgbox.error("Can?t open point theme",Script.The.GetName)
    exit
  end
?Choose the removal efficiency field
ptfieldlist=pttab.getfields
pteff=Msgbox.ChoiceAsString(ptfieldlist,"Choose a BMPs efficiency
field",Script.The.GetName)
if (pteff=nil) then
258
  msgbox.error("Can?t find efficiency field in point theme",Script.The.GetName)
  exit
end
ptshape = pttab.findfield("shape")
  if (ptshape = nil) then
    msgbox.error("Can?t find ?shape? field in point theme",Script.The.GetName)
    exit
  end
?Correct the efficiency field
question=MsgBox.YesNo("Do you want to correct the efficiency field?",
Script.The.GetName , true )
  if (question) then
     bmparea=Msgbox.ChoiceAsString(ptfieldlist,"Choose an observed drainage area field (in
acres).",Script.The.GetName)
    if (bmparea=nil) then
      msgbox.error("Can?t find drainage area field in point theme",Script.The.GetName)
    exit
    end
  end
?Choose the initial load grid
loadthm=Msgbox.ChoiceAsString(thmList,"Choose an initial load grid",Script.The.GetName)
  if(loadthm=nil)then
    exit
  end
load0grid = loadthm.getgrid
?Choose a watershed grid
  wshdthm=Msgbox.ChoiceAsString(ThmList,"Choose a watershed zones
grid",Script.The.GetName)
    if(wshdthm=nil)then
      exit
    end
wshdgrid=wshdthm.getgrid
?Create initial load field
ptload0 =  pttab.findfield("load0")
  if (ptload0=nil) then
    pttab.seteditable(true)
    ptload0 = field.make("load0", #FIELD_DECIMAL, 16, 3)
  else
    pttab.seteditable(true)
    ptload0=field.make("load0xxx",#FIELD_DECIMAL, 16, 3)
  end
pttab.addfields({ptload0})
pttab.seteditable(false)
?Write the initial load to the field
pttab.seteditable(true)
  for each rec in pttab
    shapev = pttab.returnvalue(ptshape,rec)
    val = load0grid.cellvalue(shapeV,Prj.MakeNull)
    pttab.setvalue(ptload0,rec,val)
  end
pttab.seteditable(false)
?-----------------------------
?--- Efficiency correction ---
?-----------------------------
if (question) then
?Create a fac field to store the flow accumulation
  ptfac = pttab.findfield("fac")
    if (ptfac = nil) then
      pttab.seteditable(true)
      ptfac = field.make("fac", #FIELD_DECIMAL, 16, 0)
      pttab.addfields({ptfac})
      pttab.seteditable(false)
    end
?Pick flowaccumulation for all points
  pttab.seteditable(true)
    for each rec in pttab
      shapev = pttab.returnvalue(ptshape,rec)
      facval = facgrid.cellvalue(shapeV,Prj.MakeNull)
      pttab.setvalue(ptfac,rec,facval)
    end
  pttab.seteditable(false)
259
?Compute computed drainage area (in acre) from the fac value for a 100 ft cellsize
  bmpeff = pttab.findfield("effcorr")
    if (bmpeff = nil ) then
      pttab.seteditable(true)
      bmpeff = field.make("effcorr", #FIELD_DECIMAL, 5, 3)
      pttab.addfields({bmpeff})
      pttab.seteditable(false)
    end
  pttab.seteditable(true)
    for each rec in pttab
      facval = pttab.returnvalue(ptfac,rec)
      areaobsval = pttab.returnvalue(bmparea,rec)
      eff = pttab.returnvalue(pteff,rec)
      areacompval = facval * 10000 / 43650
      corrarea= areaobsval / areacompval
      effcorr = corrarea * eff
      pttab.setvalue(bmpeff, rec,effcorr)
    end
  pttab.seteditable(false)
else
bmpeff=pteff
end
?------------------------------------------------------------
?--- Write the new load at the BMP?s to the field removed ---
?------------------------------------------------------------
?
?Check the existence of the field where the removed and the remaining loads will be writen to
ptremoved = pttab.findfield("removed")
  if (ptremoved = nil) then
    pttab.seteditable(true)
    ptremoved = field.make("removed", #FIELD_DECIMAL, 16, 3)
    pttab.addfields({ptremoved})
    pttab.seteditable(false)
  else
  end
ptremain = pttab.findfield("remain")
  if (ptremain = nil) then
    pttab.seteditable(true)
    ptremain = field.make("remain", #FIELD_DECIMAL, 16, 3)
    pttab.addfields({ptremain})
    pttab.seteditable(false)
  else
  end
?Check the efficiency: percentage or decimal fraction
            effmax=0
            effmin=0
              for each rec in pttab
                effval = pttab.returnvalue(pteff,rec)
                effmax = effmax.max(effval)
                effmin = effmin.min(effval)
              end
              if (effmax > 1) then
                percval = 100
              elseif (effmin < -1) then
                percval = 100
              else
                percval = 1
              end
?Compute the removed and remaining loads and write them in the table
pttab.seteditable(true)
  for each rec in pttab
    bmpval=pttab.returnvalue(bmpeff,rec)
    load0val=pttab.returnvalue(ptload0,rec)
    removedloadval = load0val*bmpval/percval
    remainloadval = load0val - removedloadval
    pttab.setvalue(ptremoved,rec,removedloadval)
    pttab.setvalue(ptremain,rec,remainloadval)
  end
pttab.seteditable(false)
?----------------------------------------
?--- Check if the stations are nested ---
?----------------------------------------
?Compute the flow accumulation: removed load value at the BMP?s, 0 everywhere else
?if the flowaccumulation value is 0 at the BMP?s, non nested
260
?Create grids with the removed and remaining load value at the BMP?s
aPrj = theView.GetProjection
ptremoved = pttab.findfield("removed")
removedgrid = Grid.MakeFromFTab(pttab, aPrj, ptremoved, {thecellSize, theextent})
ptremain = pttab.findfield("remain")
remaingrid = Grid.MakeFromFTab(pttab, aPrj, ptremain, {thecellSize, theextent})
?Compute the weighted flowaccumulation
rmloadgrid = (fdirgrid.flowaccumulation(removedgrid))
?Check the existence of a field for the weighted flowaccumulation
ptrmfac = pttab.findfield("rmfac")
  if (ptrmfac = nil) then
    pttab.seteditable(true)
    ptrmfac = field.make("rmfac", #FIELD_DECIMAL, 16, 0)
    pttab.addfields({ptrmfac})
    pttab.seteditable(false)
  else
  end
?Pick the flow accumulation value at the BMP?s
n=0
pttab.seteditable(true)
for each rec in pttab
  shapev = pttab.returnvalue(ptshape,rec)
  val = rmloadgrid.cellvalue(shapeV,Prj.MakeNull)
  pttab.setvalue(ptrmfac,rec,val)
  n=n.max(val)
end
pttab.seteditable(false)
?Check if there are some nested BMP?s and compute the new load
if (n=0) then ?no nested BMP?s
  tmploadgrid= (load0grid - rmloadgrid )
  listgrid=list.make
  listgrid.add(tmploadgrid)
  newloadgrid=remaingrid.merge(listgrid)
  newloadgrid.savedataset(aname)
  newloadthm=Gtheme.Make(newloadgrid)
  theview.addtheme(newloadthm)
?Remove the fields
fieldlist= {ptload0,ptremoved,ptremain,ptrmfac}
  if (question) then
    fieldlist.add(ptfac)
    fieldlist.add(bmpeff)
  end
pttab.seteditable(true)
ptTab.RemoveFields (fieldlist)
pttab.seteditable(false)
  msgbox.info("The new load has been calculated.",Script.The.GetName)
  exit
else ?order the BMP?s (0 if non nested, 1, 2 for different flow accumulation runs)
?Create a field wshd based on the watersheds
ptwshd = pttab.findfield("wshd")
  if (ptwshd = nil) then
    pttab.seteditable(true)
    ptwshd = field.make("wshd", #FIELD_DECIMAL, 4, 0)
    pttab.addfields({ptwshd})
    pttab.seteditable(false)
  else
  end
?Take the id-number associated with each watershed
pttab.seteditable(true)
  for each rec in pttab
    shapev = pttab.returnvalue(ptshape,rec)
    val = wshdgrid.cellvalue(shapeV,Prj.MakeNull)
    pttab.setvalue(ptwshd,rec,val)
  end
pttab.seteditable(false)
?Create a new field maxnum for the maximum number of nested BMP?s in each watershed
261
pttab.seteditable(true)
ptmaxnum=pttab.findfield("maxnum")
  if (ptmaxnum=nil) then
    pttab.seteditable(true)
    ptmaxnum = field.make("maxnum", #FIELD_DECIMAL, 4, 0)
    pttab.addfields({ptmaxnum})
  else
  end
?for each rec in pttab
 ? pttab.setvalue(ptmaxnum, rec, 0)
?e n d
?Select the watersheds in which there are nested BMP?s
wshdlist=list.make
for each rec in pttab
  rmfacval=pttab.returnvalue(ptrmfac,rec)
    if (rmfacval > 0) then ?it is a nested BMP
      wshdval=pttab.returnvalue(ptwshd,rec)
      wshdlist.add(wshdval)
    end
end
?Assign the number of BMP?s per watersheds in a new field maxnum (0 for the normal ones)
maxnumber=0
for each rec in pttab
  rmfacval=pttab.returnvalue(ptrmfac,rec)
    if (rmfacval > 0) then ?it is a nested BMP
      wshdval=pttab.returnvalue(ptwshd,rec)
      i=0
        for each rec in wshdlist
          if (wshdval=rec) then
            i=i+1
          else
          end
        end
      pttab.setvalue(ptmaxnum, rec, i)
      maxnumber=maxnumber.max(i)
    end
end
?msgbox.info("max= "++maxnumber.asstring,"")
?If the maximum number of nested BMP?s in any watershed is 1
if (maxnumber=1) then
?Create two new efficiency fields (2 runs)
  ptneweff0 =  pttab.findfield("neweff0")
    if (ptneweff0=nil) then
      pttab.seteditable(true)
      ptneweff0 = field.make("neweff0", #FIELD_DECIMAL, 3, 2)
      pttab.addfields({ptneweff0})
      pttab.seteditable(false)
    end
  ptneweff1 =  pttab.findfield("neweff1")
    if (ptneweff1=nil) then
      pttab.seteditable(true)
      ptneweff1 = field.make("neweff1", #FIELD_DECIMAL, 3, 2)
      pttab.addfields({ptneweff1})
      pttab.seteditable(false)
    end
?Write the efficiency values
  pttab.seteditable(true)
    for each rec in pttab
      effval=pttab.returnvalue(bmpeff,rec)
      rmfacval=pttab.returnvalue(ptrmfac,rec)
        if (rmfacval > 0) then?nested BMPs
          pttab.setvalue(ptneweff1,rec,effval)
        else
          pttab.setvalue(ptneweff0,rec,effval)
        end
    end
?Compute the new load
  load1grid=av.run("Qual.bmpeff_cpt",{load0grid,fdirgrid,pttab,ptneweff0,percval})
  newloadgrid=av.run("Qual.bmpeff_cpt",{load1grid,fdirgrid,pttab,ptneweff1,percval})
  newloadgrid.savedataset(aname)
  newloadthm=Gtheme.Make(newloadgrid)
  theView.AddTheme(newloadthm)
  newloadthm.setlegendvisible(false)
262
?Remove the fields
fieldlist= {ptload0,ptremoved,ptremain,ptmaxnum,ptneweff0,ptneweff1,ptrmfac,ptwshd}
  if (question) then
    fieldlist.add(ptfac)
    fieldlist.add(bmpeff)
  end
pttab.seteditable(true)
ptTab.RemoveFields (fieldlist)
pttab.seteditable(false)
  msgbox.info("The new load has been calculated.","")
  exit
else ?if there are more than 1 nested BMP in each watershed, sort by flowacumulation.
if (question=false) then
?Create a fac field to store the flow accumulation
  ptfac = pttab.findfield("fac")
    if (ptfac = nil) then
      pttab.seteditable(true)
      ptfac = field.make("fac", #FIELD_DECIMAL, 16, 0)
      pttab.addfields({ptfac})
      pttab.seteditable(false)
    end
?Pick flowaccumulation for all points
  pttab.seteditable(true)
    for each rec in pttab
      shapev = pttab.returnvalue(ptshape,rec)
      facval = facgrid.cellvalue(shapeV,Prj.MakeNull)
      pttab.setvalue(ptfac,rec,facval)
    end
  pttab.seteditable(false)
end
?Check the existence of a field order to sort the BMP?s
  ptorder=pttab.findfield("order")
    if (ptorder = nil) then
        pttab.seteditable(true)
        ptorder = field.make("order", #FIELD_DECIMAL, 4, 0)
        pttab.addfields({ptorder})
        pttab.seteditable(false)
    end
?Create list of BMP?s in the same watershed
  minimum=1000000000
  wshdlist.removeduplicates
  idlist=list.make
    for each wshd in wshdlist
      i=0
        for each rec in pttab
          rmfacval=pttab.returnvalue(ptrmfac,rec)
            if (rmfacval > 0) then ?it is a nested bmp
              wshdval=pttab.returnvalue(ptwshd,rec)
                if (wshdval=wshd) then
                  idlist.add(i)
                end
            else
              pttab.seteditable(true)
              pttab.setvalue(ptorder,rec,0)
            end
          i=i+1
         end
?Compute the minimum for the list
    faclist=list.make
      for each rec in idlist
        facval=pttab.returnvalue(ptfac,rec)
        faclist.add(facval)
        ?msgbox.info("facval"+facval.asstring,"")
        minimum=minimum.min(facval)
      end
    ?msgbox.info("the min1 is "++minimum.asstring,"")
263
?Order the nested bmp in a selected watershed according to their
?flowaccumulation value
    pttab.seteditable(true)
    n=idlist.count
    i=1
      for each i in 1..n
        idlist1=list.make
          for each rec in idlist
            facval=pttab.returnvalue(ptfac,rec)
              if(facval=minimum) then
                pttab.seteditable(true)
                pttab.setvalue(ptorder,rec,i)
                pttab.seteditable(false)
              else
                idlist1.add(rec)
              end
          end
        i=i+1
        minimum=100000000
          for each rec in idlist1
            facval=pttab.returnvalue(ptfac,rec)
            minimum=minimum.min(facval)
          end
        idlist=idlist1
      end
  end
?Create as many neweff fields as necessary
  i=0
    for each i in 0..maxnumber
      ptneweff =  pttab.findfield("neweff")
        if (ptneweff=nil) then
          pttab.seteditable(true)
          ptneweff = field.make("neweff", #FIELD_DECIMAL, 3, 2)
          pttab.addfields({ptneweff})
          pttab.seteditable(false)
        end
      pttab.seteditable(true)
        for each rec in pttab
          orderval=pttab.returnvalue(ptorder,rec)
            if (orderval=i) then
              bmpeffval=pttab.returnvalue(bmpeff,rec)
              pttab.setvalue(ptneweff,rec,bmpeffval)
            else
              pttab.setvalue(ptneweff,rec,0)
            end
        end
?Compute the new loads
      load0grid=av.run("Qual.bmpeff_cpt",{load0grid,fdirgrid,pttab,ptneweff,percval})
      i=i+1
    end
?Save the load grid
  load0grid.savedataset(aname)
  newloadthm=Gtheme.Make(load0grid)
  theview.addtheme(newloadthm)
  newloadthm.setlegendvisible(false)
?Remove the fields
fieldlist= {ptload0,ptremoved,ptremain,ptmaxnum,ptfac,ptneweff,ptrmfac,ptwshd,ptorder}
  if (question) then
    fieldlist.add(ptfac)
    fieldlist.add(bmpeff)
  end
pttab.seteditable(true)
ptTab.RemoveFields (fieldlist)
pttab.seteditable(false)
  msgbox.info("The new load has been calculated.","")
  exit
end
end
?-----------
?--- End ---
?-----------
264
?Script Qual.BMPeff_cpt
?
?----------------------------
?--- Creation information ---
?----------------------------
?
?Name: Qual.BMPeff_cpt
?Version: 1.0
?Date: 05/23/97
?Author: Christine Dartiguenave
?        Center for Research in Water Resources
?        The University of Texas at Austin
?        darti@crwr.utexas.edu
?
?---------------------------
?--- Purpose/Description ---
?---------------------------
?
?This program takes a load grid and a point coverage
?and computes the new load for non nested BMP?s.
?It is used as a subroutine of Qual.BMPeff.
theview=av.getactivedoc
if (self.count=5) then
  load0grid=self.get(0)
  fdirgrid=self.get(1)
  pttab=self.get(2)
  bmpeff=self.get(3)
  percval=self.get(4)
  else
exit
end
ptshape = pttab.findfield("shape")
  if (ptshape = nil) then
    msgbox.error("Can?t find ?shape? field in point theme",Script.The.GetName)
    exit
  end
?-------------------------------------------------
?--- Write the initial load to the field load0 ---
?-------------------------------------------------
?Check the existence of the initial load field load0
ptload0 =  pttab.findfield("load0")
if (ptload0=nil) then
  pttab.seteditable(true)
  ptload0 = field.make("load0", #FIELD_DECIMAL, 16, 0)
  pttab.addfields({ptload0})
  pttab.seteditable(false)
end
?Write the initial load to the field load0
pttab.seteditable(true)
  for each rec in pttab
    shapev = pttab.returnvalue(ptshape,rec)
    val = load0grid.cellvalue(shapeV,Prj.MakeNull)
    pttab.setvalue(ptload0,rec,val)
  end
pttab.seteditable(false)
?------------------------------------------------------------
?--- Write the new load at the BMP?s to the field removed ---
?------------------------------------------------------------
?
ptremoved=pttab.findfield("removed")
ptremain=pttab.findfield("remain")
?Compute the removed and remaining loads and write them in the table
pttab.seteditable(true)
for each rec in pttab
    bmpval=pttab.returnvalue(bmpeff,rec)
    load0val=pttab.returnvalue(ptload0,rec)
    removedloadval = load0val*bmpval/percval
    remainloadval = load0val-removedloadval
    pttab.setvalue(ptremoved,rec,removedloadval)
    pttab.setvalue(ptremain,rec,remainloadval)
    if (bmpval = 0) then
        pttab.setvalue(ptremain,rec,0)
265
    end
end
pttab.seteditable(false)
?Create a grid with the remaining value just at the station with non negative neweff
?Create grids with the removed and remaining load value at the BMP?s
cellsize=load0grid.getcellsize
box=load0grid.getextent
aPrj = theView.GetProjection
ptremain=pttab.findfield("remain")
remain1grid = Grid.MakeFromFTab(pttab, aPrj, ptremain, {cellSize, box})
remaingrid=(remain1grid = 0.asgrid).setnull(remain1grid)
ptremoved = pttab.findfield("removed")
removedgrid = Grid.MakeFromFTab(pttab, aPrj, ptremoved, {cellSize, box})
?Compute the weighted flowaccumulation
rmloadgrid = (fdirgrid.flowaccumulation(removedgrid))
?Compute the new load
tmploadgrid=load0grid-rmloadgrid
listgrid=list.make
listgrid.add(tmploadgrid)
newloadgrid = remaingrid.merge( listgrid )
return newloadgrid
?Script: Qual.BMPfut
?
?----------------------------
?--- Creation information ---
?----------------------------
?
?Name: Qual.BMPfut
?Version: 1.0
?Date: 10/17/97
?Author: Christine Dartiguenave
?        Center for Research in Water Resources
?        The University of Texas at Austin
?        darti@crwr.utexas.edu
?
?---------------------------
?--- Purpose/Description ---
?---------------------------
?
?This program compute the new load after implementation of the future BMPs (areal
representation).
?--------------------
?--- Get the View ---
?--------------------
?
theView=av.GetActiveDoc
aPrj = theView.GetProjection
?Check if there are any theme in the view.
  if (theView.GetThemes.Count = 0) then
    msgbox.error("No themes found", Script.The.GetName)
    exit
  end
?---------------------------
?--- Set analysis extent ---
?---------------------------
? bring up the AnalysisPropertiesDialog
theAE = AnalysisPropertiesDialog.Show(theView,FALSE,"Analysis Properties")
  if (theAE=nil) then
    exit
  end
theExtent = Rect.Make(0@0,1@1)
theCellSize = 1
if ((theAE.GetExtent(theExtent) <> #ANALYSISENV_VALUE) or
    (theAE.GetCellSize(theCellSize) <> #ANALYSISENV_VALUE)) then
  theCE = AnalysisPropertiesDialog.Show(theView,TRUE,"Analysis Extent")
  ? check for Cancel from dialog
  if (theCE = NIL) then
    return NIL
  end
  theCE.GetCellSize(theCellSize)
  theCE.GetExtent(theExtent)
end
Grid.SetAnalysisCellSize ( #GRID_ENVTYPE_VALUE , theCellSize )
Grid.SetAnalysisExtent ( #GRID_ENVTYPE_VALUE , theextent )
266
?-----------------------------
?--- Set working directory ---
?-----------------------------
aProject=av.GetProject
defaultdir=aProject.GetWorkDir
inputdir=MsgBox.Input("Choose the working
directory.",Script.The.GetName,defaultdir.asstring)
  if (inputdir=nil) then
  else
    aDirName = inputdir.asfilename
    aProject.SetWorkDir (aDirName)
  end
recharge=msgbox.yesno("Do you want to consider a recharge
zone",Script.The.GetName,true)
?----------------------------------------
?--- Choose the constituents to model ---
?----------------------------------------
?----------------------
?--- Get the tables ---
?----------------------
doculist = av.GetProject.Getdocs
tablelist=List.Make
  for each d in doculist
    if(d.Is(Table))then
      TableList.add(d)
    end
  end
?Annual capture volume tables
acvtable=Msgbox.ChoiceAsString(tableList,"Choose a capture volume
table.",Script.The.GetName)
  if(acvtable=nil)then
    msgbox.error("No ACV table selected",Script.The.GetName)
    exit
  end
acvtab=acvtable.getvtab
acvlist=acvtab.getfields
?BMPs zones tables
bmptable=Msgbox.ChoiceAsString(tableList,"Choose a BMPs zones
table.",Script.The.GetName)
  if(bmptable=nil)then
    msgbox.error("No BMPs zones table selected",Script.The.GetName)
    exit
  end
bmptab=bmptable.getvtab
bmplist=bmptab.getfields
?Efficiency
efftable=Msgbox.ChoiceAsString(tableList,"Choose an efficiency
table.",Script.The.GetName)
  if(efftable=nil)then
    msgbox.error("No efficiency table selected",Script.The.GetName)
    exit
  end
efftab=efftable.getvtab
efflist=efftab.getfields
?Direct runoff EMC table
emcruntable=Msgbox.ChoiceAsString(tableList,"Choose a direct runoff EMCs
table",Script.The.GetName)
    if(emcruntable=nil)then
      msgbox.error("No direct runoff EMCs table selected",Script.The.GetName)
      exit
    end
emcruntab=emcruntable.getvtab
emcrunlist=emcruntab.getfields
runcons=emcrunlist.get(0)
?List the available grids
gridList=list.Make
  for each thm in TheView.GetThemes
    if(thm.is(Gtheme))then
      gridList.add(thm)
    end
  end
267
?Choose the constituents to model
?Number of constituents
i=0
  for each rec in efftab
    i=i+1
  end
r=i
s=r-1
constfield=efflist.get(0)
conslist=list.make
  for each k in 2..s
    constituent=efftab.returnvaluestring(constfield,k)
    conslist.add(constituent)
  end
choices = MsgBox.MultiListAsString( conslist, "Choose the constituent(s) to model",
Script.The.GetName )
  if (choices = nil) then
    msgbox.info("No constituent selected.", Script.The.GetName)
    exit
  else
    namelist=list.make
    loadlist=list.make
      for each cons in choices
        outFName = av.GetProject.MakeFileName(cons, "")
        aName = FileDialog.Put(outFName, "", cons)
          if (aName = Nil) then
            exit
          end
        namelist.add(aname)
        ?Choose an original load grid
        loadthm=Msgbox.ChoiceAsString(gridList,"Choose an initial load grid
for"++cons.asstring,Script.The.GetName)
          if(loadthm=nil)then
            exit
          end
        loadlist.add(loadthm)
    end
  end
?Choose an impervious cover theme
icList=list.Make
  for each thm in TheView.GetThemes
    if(thm.is(Ftheme))then
      if(thm.GetFtab.GetShapeClass.GetClassName="polygon")then
       icList.add(thm)
      end
    else
      if (thm.is(Gtheme)) then
       iclist.add(thm)
      end
   end
  end
icthm=Msgbox.ChoiceAsString(icList,"Choose an impervious cover
theme.",Script.The.GetName)
    if(icthm=nil)then
      exit
    end
if (icthm.is(ftheme)) then
  anftab=icthm.getftab
  fieldlist=anftab.getfields
  icfield=Msgbox.ChoiceAsString(fieldlist,"Choose the ic field.",Script.The.GetName)
  if(icfield=nil)then
    exit
  end
end
?Choose a flow direction grid
fdirthm=Msgbox.ChoiceAsString(gridList,"Choose a flow direction
grid.",Script.The.GetName)
  if(fdirthm=nil)then
    exit
  end
fdirgrid=fdirthm.getgrid
?Choose a bmp zone grid
bmpzonethm=Msgbox.ChoiceAsString(gridList,"Choose a BMPs zones
grid.",Script.The.GetName)
  if(bmpzonethm=nil)then
268
    exit
  end
bmpzone=bmpzonethm.getgrid
?Choose a corrected cell runoff grid
runcellthm=Msgbox.ChoiceAsString(gridList,"Choose a corrected cell runoff
grid.",Script.The.GetName)
      if(runcellthm=nil)then
        exit
      end
runcell=runcellthm.getgrid
?Choose a buildup grid
buildupthm=Msgbox.ChoiceAsString(gridList,"Choose a buildup grid.",Script.The.GetName)
      if(buildupthm=nil)then
        exit
      end
buildup=buildupthm.getgrid
?Choose a water land use zone
zonethm=Msgbox.ChoiceAsString(gridList,"Choose a water landuse theme
(zone_gr).",Script.The.GetName)
    if(zonethm=nil)then
      exit
    end
zone=zonethm.getgrid
if (recharge) then
?Choose a total flow grid with recharge
tflowthm=Msgbox.ChoiceAsString(gridList,"Choose a predicted flow grid (with recharge,
flow1).",Script.The.GetName)
      if(tflowthm=nil)then
        exit
      end
tflow=tflowthm.getgrid
?Choose a total flow grid without recharge
tflow0thm=Msgbox.ChoiceAsString(gridList,"Choose a total flow grid (without recharge,
tflow01).",Script.The.GetName)
      if(tflow0thm=nil)then
        exit
      end
totalflow0=tflow0thm.getgrid
?Choose a cell correction recharge
lcorrrechthm=Msgbox.ChoiceAsString(gridList,"Choose a cell correction recharge
grid.",Script.The.GetName)
      if(lcorrrechthm=nil)then
        exit
      end
lcorr_rech=lcorrrechthm.getgrid
end
if (icthm.is(gTheme)) then
  icgrid=icthm.getgrid
else
  anftab=icthm.getftab
  icgrid = Grid.MakeFromFTab(anFTab, aPrj, icfield, {thecellSize, theextent})
end
?----------------------
?--- Capture volumes ---
?----------------------
?number of acv
p=acvlist.count
q=p-1
for each i in 0..q
  thefield=acvlist.get(i)
  a=acvtab.returnvalue(thefield,0)
  b=acvtab.returnvalue(thefield,1)
269
  acvgrid=a.asgrid*icgrid+b.asgrid
  acvname = av.getproject.makefilename("acv", "")
  acvgrid.savedataset(acvname)
  acvgthm=Gtheme.Make(acvgrid)
  theview.addtheme(acvgthm)
  acvgthm.setlegendvisible(false)
  i=i+1
end
?------------------
?--- Efficiency ---
?------------------
i=0
  for each rec in bmptab
    i=i+1
  end
n=i
?n is the number of bmp zones
?q total number of bmps
p=bmplist.count
q=p-1
?for each constituent
?number of constituents to model
z=choices.count
if (recharge=true) then
?-------------------------------
?--- Flow removal efficiency ---
?-------------------------------
?Check if there are non discharge BMPs
theval=0
  for each i in 1..q
    thefield2=efflist.get(i)
    effval=efftab.returnvalue(thefield2,1)
    theval=theval.max(effval)
    i=i+1
  end
  if (theval<>0) then
    floweffgrid=0.asgrid
      ?for each zone
       for each i in 1..n
         floweff=0.asgrid
          for each j in 1..q
            ?get the percentage of the bmp
            thefield1=bmplist.get(j)
            bmpval=bmptab.returnvalue(thefield1,i-1)
            ?msgbox.info(bmpval.asstring,"bmp%")
            ?get the efficiency
            thefield2=efflist.get(j)
            effval=efftab.returnvalue(thefield2,1)
            acvval=efftab.returnvalue(thefield2,0)
            theacvname="acv"+acvval.asstring
            ?msgbox.info(theacvname, "acv")
            ?msgbox.info(effval.asstring,"removal eff")
            acvthm=theview.findtheme(theacvname)
            theacvgrid=acvthm.getgrid
            floweff=floweff+(bmpval.asgrid*effval.asgrid*theacvgrid)
            j=j+1
          end
        floweffgrid=(bmpzone=i.asgrid).con(floweff,floweffgrid)
        i=i+1
      end
?thename = av.getproject.makefilename("floweff","")
?floweffgrid.savedataset(thename)
?floweffg=Gtheme.Make(floweffgrid)
?theview.addtheme(floweffg)
?floweffg.setlegendvisible(false)
?e x i t
rmruncell = runcell * floweffgrid * buildup
rmflow = (fdirgrid.flowaccumulation(rmruncell))
totalflow1 = totalflow0 - rmflow
newflow1 = tflow - rmflow
thename = av.getproject.makefilename("newflow","")
newflow1.savedataset(thename)
newflow1gthm=Gtheme.Make(newflow1)
theview.addtheme(newflow1gthm)
newflow1gthm.setlegendvisible(false)
270
  else
    totalflow1=totalflow0
  end
  end
?-------------------------
?--- Direct Runoff EMC ---
?-------------------------
for each l in 1..z
  theeffgrid=0.asgrid
  cons=choices.get(l-1)
?Check storm runoff field
if (icthm.is(ftheme)) then
      anftab.seteditable(true)
      consfield = anftab.findfield(cons+"_[mg/l]")
        if (consfield = nil) then
          consfield = field.make(cons+"_[mg/l]", #FIELD_DECIMAL, 6, 3)
          anftab.addfields({consfield})
        end
end
?Get the parameters a and b (emc=a+b*ic,0<ic<1)
            i=0
            for each rec in emcruntab
              runconsname=emcruntab.returnvaluestring(runcons,rec)
                if (runconsname=cons) then
                  p=i
                else
                  i=i+1
                end
            end
            afield=emcrunlist.get(1)
            bfield=emcrunlist.get(2)
            a=emcruntab.returnvalue(afield,p)
            b=emcruntab.returnvalue(bfield,p)
            if (icthm.is(Ftheme)) then
              icmax=0
              for each rec in anFTab
                ic1 = anFtab.returnvalue(icfield,rec)
                icmax=icmax.max(ic1)
              end
            if (icmax>1)then
             icperc = true
           else
             icperc = false
           end
              for each rec in anFtab
                ic1 = anFtab.returnvalue(icfield, rec)
                  if (icperc=true) then
                    ic1=ic1/100
                  end
                emcrun=b*ic1+a
                anftab.setvalue(consfield , rec , emcrun )
              end
            else
            aprj=theview.getprojection
            icint=icgrid.int
            icvtab=icint.getvtab
            icfield=icvtab.findfield("value")
              icmax=0
              for each rec in icvtab
                icvalue=icvtab.returnvalue(icfield,rec)
                icmax=icmax.max(icvalue)
              end
                if (icmax<=1) then
                  emc_gr0 = icgrid*b + a.asgrid
                else
                  emc_gr0 = icgrid*b*0.01 + a.asgrid
                end
            end
aPrj=theview.getprojection
  if (icthm.is(Ftheme)) then
    emc_gr0 = Grid.MakeFromFTab(anFTab, aPrj, consfield, {thecellSize, theextent})
  end
?Set the EMC for water to zero.
emc_gr=(zone=999).con(0.asgrid,emc_gr0)
271
?for each zone
for each i in 1..n
      eff=0.asgrid
?for each BMP
   for each j in 1..q
    ?get the percentage of the bmp
    thefield1=bmplist.get(j)
    bmpval=bmptab.returnvalue(thefield1,i-1)
    ?msgbox.info(bmpval.asstring,"bmp%")
    ?get the efficiency
    thefield2=efflist.get(j)
    effval=efftab.returnvalue(thefield2,l+1)
    ?msgbox.info(effval.asstring,"eff")
    acvval=efftab.returnvalue(thefield2,0)
    theacvname="acv"+acvval.asstring
    ?msgbox.info(theacvname,"acv")
    acvthm=theview.findtheme(theacvname)
    theacvgrid=acvthm.getgrid
    ?1=bod in that case
     eff=eff+ (theacvgrid*bmpval.asgrid*effval.asgrid)
    j=j+1
  end
  theeffgrid=(bmpzone=i.asgrid).con(eff,theeffgrid)
  i=i+1
end
 ? theeffgrid.savedataset(aname)
 ? effthm=Gtheme.Make(theeffgrid)
 ? theview.addtheme(effthm)
 ? effthm.setlegendvisible(false)
?Check if effgrid contains negative values
effgrid1 = theeffgrid*10000
effgridint = effgrid1.int
  effgridtab=effgridint.getvtab
  effgridfield=effgridtab.findfield("value")
  themax=0
  themin=0
    for each rec in effgridtab
      theval=effgridtab.returnvalue(effgridfield,rec)
      themax=themax.max(theval)
      themin=themin.min(theval)
    end
  if (themin<0) then
    if (themax=0) then
     effgrid = - theeffgrid
     rmloadcell=runcell*emc_gr*effgrid*buildup*3.048*3.048*3.048*365*86400/1000000
     rmload0=-(fdirgrid.flowaccumulation(rmloadcell))
    else
      neggrid=(theeffgrid<0).setnull(-theeffgrid)
      posgrid=(theeffgrid>=0).setnull(theeffgrid)
      negloadcell = runcell
*emc_gr*neggrid*buildup*3.048*3.048*3.048*365*86400/1000000
      posloadcell = runcell *emc_gr*posgrid*buildup*3.048*3.048*3.048*365*86400/1000000
      negload0 = (fdirgrid.flowaccumulation(negloadcell))
      posload0 = (fdirgrid.flowaccumulation(posloadcell))
      rmload0 = posload0 - negload0
   end
  else
   rmloadcell=runcell*emc_gr*theeffgrid*buildup*3.048*3.048*3.048*365*86400/1000000
   rmload0=(fdirgrid.flowaccumulation(rmloadcell))
  end
?----------------------------------
?--- Compute the corrected load ---
?----------------------------------
loadthm=loadlist.get(l-1)
load=loadthm.getgrid
if (recharge=false) then
?Without recharge
  newload=load-rmload0
  aname=namelist.get(l-1)
  newload.savedataset(aname)
  newloadgthm=Gtheme.Make(newload)
  theview.addtheme(newloadgthm)
  newloadgthm.setlegendvisible(false)
else
?With recharge
  co=load/tflow
  load01 = co * totalflow0 - rmload0
  co1 = load01 / totalflow1
  loadrech = lcorr_rech * co1
  rechload=(fdirgrid.flowaccumulation(loadrech))
  newload=load01-rechload
  aname=namelist.get(l-1)
  newload.savedataset(aname)
  newloadgthm=Gtheme.Make(newload)
272
  theview.addtheme(newloadgthm)
  newloadgthm.setlegendvisible(false)
end
l=l+1
end
p=acvlist.count
  i=1
  for each i in 1..p
    theacvname="acv"+i.asstring
    thename=theacvname.asfilename
    acvthm=theview.findtheme(theacvname)
    theview.deletetheme(acvthm)
    grid.deletedataset(thename)
    i=i+1
  end
msgbox.info("Corrected load(s) calculated.",Script.The.GetName)
?Script Qual.BMPload
?
----------------------------
?--- Creation information ---
?----------------------------
?
?Name: Qual.BMPload
?Version: 1.0
?Date: 5/21/97
?Modified: 10/16/97
?Author: Christine Dartiguenave
?        Center for Research in Water Resources
?        The University of Texas at Austin
?        darti@crwr.utexas.edu
?
?---------------------------
?--- Purpose/Description ---
?---------------------------
?
?This program computes the newload after removing
?the mass given in a bmp table corresponding to a bmp coverage.
?--------------------
?--- Get the View ---
?--------------------
theView=av.GetActiveDoc
?Check if there are some themes in the view.
if (theView.GetThemes.Count = 0) then
  msgbox.error("No themes found", Script.The.GetName)
  exit
end
?-----------------------------
?--- Set working directory ---
?-----------------------------
aProject=av.GetProject
defaultdir=aProject.GetWorkDir
inputdir=MsgBox.Input("Choose the working
directory.",Script.The.GetName,defaultdir.asstring)
  if (inputdir=nil) then
  else
    aDirName = inputdir.asfilename
    aProject.SetWorkDir (aDirName)
  end
?Name the new grid
outFName = av.GetProject.MakeFileName("remload", "")
aname = FileDialog.Put(outFName, "", "Load removed")
if (aname = Nil) then
  exit
end
?------------------
?--- Get themes ---
?------------------
?List the available grids
273
ThmList=list.Make
  for each thm in TheView.GetThemes
    if(thm.is(Gtheme))then
      ThmList.add(thm)
    end
  end
?Choose a flow direction grid
    fdirthm=Msgbox.ChoiceAsString(ThmList,"Choose a flow direction
grid",Script.The.GetName)
      if(fdirthm=nil)then
        exit
      end
fdirgrid=fdirthm.getgrid
?List the available point coverages
Thm1List=list.Make
  for each thm in TheView.GetThemes
    if(thm.is(Ftheme))then
      if(thm.GetFtab.GetShapeClass.GetClassName="Point")then
        Thm1List.add(thm)
      end
    end
  end
?Choose the BMPs point coverage
Ptthm=Msgbox.ChoiceAsString(Thm1List,"Choose a BMPs point
coverage",Script.The.GetName)
  if(Ptthm=nil)then
    exit
  end
?Get the point attribute table
pttab = Ptthm.getftab
  if (pttab = nil) then
    msgbox.error("Can?t open point theme",Script.The.GetName)
    exit
  end
?Choose the removed load field
ptfieldlist=pttab.getfields
bmpload=Msgbox.ChoiceAsString(ptfieldlist,"Choose the removed load
field",Script.The.GetName)
if (bmpload=nil) then
  msgbox.error("Can?t find removed load field in point theme",Script.The.GetName)
  exit
end
ptshape = pttab.findfield("shape")
  if (ptshape = nil) then
    msgbox.error("Can?t find ?shape? field in point theme",Script.The.GetName)
    exit
  end
?Create a grid with the removed value at the BMPs (positive values)
cellsize=fdirgrid.getcellsize
box=fdirgrid.getextent
aPrj = theView.GetProjection
removedgrid = Grid.MakeFromFTab(pttab, aPrj, bmpload, {cellSize, box})
themax=0
themin=0
  for each rec in pttab
    theval=pttab.returnvalue(bmpload,rec)
    themax=themax.max(theval)
    themin=themin.min(theval)
  end
  if (themin<0) then
    if (themax=0) then
      removed1grid=-removedgrid
      rmloadgrid =- (fdirgrid.flowaccumulation(removed1grid))
    else
      neggrid=(removedgrid>=0).setnull(-removedgrid)
      posgrid=(removedgrid<0).setnull(removedgrid)
      negrmload = (fdirgrid.flowaccumulation(neggrid))
      posrmload = (fdirgrid.flowaccumulation(posgrid))
      rmloadgrid=posrmload - negrmload
    end
   else
     rmloadgrid = (fdirgrid.flowaccumulation(removedgrid))
  end
listgrid=list.make
274
zerogrid=rmloadgrid*0.asgrid
listgrid.add(zerogrid)
newremgrid = removedgrid.merge(listgrid)
rmgrid= rmloadgrid+newremgrid
rmgrid.savedataset(aname)
rmthm=Gtheme.Make(rmgrid)
theview.addtheme(rmthm)
rmthm.setlegendvisible(false)
Msgbox.info("The load removed by the BMPs has been calculated.",Script.The.GetName)
?-----------
?--- End ---
?-----------
?Script: Qual.Creek
?----------------------------
?--- Creation information ---
?----------------------------
?
?Name: Qual.Creek
?Version: 1.0
?Date: 11/17/97
?Author: Christine Dartiguenave
?        Center for Research in Water Resources
?        The University of Texas at Austin
?        darti@crwr.utexas.edu
?
?---------------------------
?--- Purpose/Description ---
?---------------------------
?
?This program creates a grid creek network corresponding
? to a given thresold.
?--------------------
?--- Get the View ---
?--------------------
?
theView=av.GetActiveDoc
?----------------------
?--- Get the themes ---
?----------------------
gridList=list.Make
  for each thm in TheView.GetThemes
    if(thm.is(Gtheme))then
       gridList.add(thm)
     end
 end
fdrthm=Msgbox.ChoiceAsString(gridList,"Choose a flow direction
grid.",Script.The.GetName)
    if(fdrthm=nil)then
      exit
    end
fdrgrid=fdrthm.getgrid
facthm=Msgbox.ChoiceAsString(gridList,"Choose a flow accumulation
grid.",Script.The.GetName)
    if(facthm=nil)then
      exit
    end
facgrid=facthm.getgrid
? Define the creek threshold
thethreshold=msgbox.input("Enter a threshold value to define the creeks (number of
cells).",Script.The.GetName,"100")
?Name the creeks grid and coverage
outname1=av.getproject.makefilename("crk_gr","")
aname1=filedialog.put(outname1,"","Creek grid")
outname2=av.getproject.makefilename("crk_cv","shp")
aname2=filedialog.put(outname2,"shp","Creek coverage")
?Define the creeks
streamgrid = (facgrid < thethreshold.asnumber.asgrid).setnull(1.asgrid)
streamgrid.savedataset(aname1)
streamtheme = gtheme.make(streamgrid)
theview.addtheme(streamtheme)
streamtheme.setlegendvisible(false)
275
TheFtab=streamgrid.StreamToPolyLineFtab(aname2,fdrgrid,False,prj.MakeNull)
TheFThm=FTheme.Make(TheFtab)
TheView.AddTheme(TheFThm)
TheFThm.setlegendvisible(false)
?-----------
?--- END ---
?-----------
?Script: Qual.Creeklimit
?
?----------------------------
?--- Creation information ---
?----------------------------
?
?Name: Qual.Creeklimit
?Version: 1.0
?Date: 11/17/97
?Author: Christine Dartiguenave
?        Center for Research in Water Resources
?        The University of Texas at Austin
?        darti@crwr.utexas.edu
?
?---------------------------
?--- Purpose/Description ---
?---------------------------
?
?This program creates a grid representing the limit
?of the creeks associated to a certain threshold.
?--------------------
?--- Get the View ---
?--------------------
?
theView=av.GetActiveDoc
?----------------------
?--- Get the themes ---
?----------------------
gridList=list.Make
  for each thm in TheView.GetThemes
    if(thm.is(Gtheme))then
       gridList.add(thm)
     end
 end
fdrthm=Msgbox.ChoiceAsString(gridList,"Choose a flow direction
grid.",Script.The.GetName)
    if(fdrthm=nil)then
      exit
    end
fdrgrid=fdrthm.getgrid
facthm=Msgbox.ChoiceAsString(gridList,"Choose a flow accumulation
grid.",Script.The.GetName)
    if(facthm=nil)then
      exit
    end
facgrid=facthm.getgrid
?Define the creek threshold
thethreshold=msgbox.input("Enter a threshold value to define the creeks (number of
cells).",Script.The.GetName,"100")
?Name the point grid
outname1=av.getproject.makefilename("crklim","")
aname1=filedialog.put(outname1,"","Creek upstream limit")
?Define the creek limit
streamgrid = (facgrid < thethreshold.asnumber.asgrid).setnull(1.asgrid)
faclimgrid = fdrgrid.flowaccumulation (streamgrid)
?Take the intersection between the cells located in the newly defined
?creeks and the cells whose new flowaccumulation value is 0.
pointlimgrid = (streamgrid = 1.asgrid and  faclimgrid > 0.asgrid).setnull(streamgrid)
pointlimgrid.savedataset(aname1)
pointlimtheme = gtheme.make(pointlimgrid)
theview.addtheme(pointlimtheme)
pointlimtheme.setlegendvisible(false)
?-----------
?--- END ---
?-----------
276
? Script Qual.Delete
?----------------------------
?--- Creation information ---
?----------------------------
?Name: Qual.Delete
?Version: 1.0
?Date: 10/03/1997
?Author: Christine Dartiguenave
?Center for Research in Water Resources
?The University of Texas at Austin
?darti@crwr.utexas.edu
?---------------------------
?--- Purpose/Description ---
?---------------------------
?Delete several fields in a table
?------------------------
?--- Choose the table ---
?------------------------
doculist = av.GetProject.GetDocs
tablelist=List.Make
      for each d in doculist
        if(d.Is(Table))then
          TableList.add(d)
        end
      end
name=MsgBox.choiceasstring(tablelist, "Choose a table", Script.The.GetName)
if (name = nil)
  then MsgBox.info("No table selected", Script.The.GetName)
  exit
end
?-------------------------------------
?---   Choose the fields to delete ---
?-------------------------------------
table1=name.getvtab
fieldlist = table1.GetFields
fieldname = MsgBox.MultiListAsString(fieldlist, "Choose the field(s) to delete" ,
Script.The.GetName)
if (fieldname = nil)
  then MsgBox.info("No field(s) selected" , Script.The.GetName)
  exit
end
?-------------------------
?--- Delete the fields ---
?-------------------------
Answer = MsgBox.YesNo("Do you really want to delete these fields?",Script.The.GetName ,
true )
if (answer) then
  table1.seteditable(true)
  table1.removefields(fieldname)
  table1.seteditable(false)
end
?-----------
?--- END ---
?-----------
?Script: Qual.Flow
?----------------------------
?--- Creation information ---
?----------------------------
?Name: Qual.Flow
?Version: 1.0
?Creation date: 06/26/97
?Modified 09/16/97
?Modified 10/20/97
?Author: Christine Dartiguenave
?Center for Research in Water Resources
?The University of Texas at Austin
?darti@crwr.utexas.edu
?---------------------------
?--- Purpose/Description ---
?---------------------------
?Compute the base flow, the stormflow and the total flow.in cfs,
?and the grids necessary to the load computation.
?--------------------
?--- Get the view ---
?--------------------
277
theView=av.GetActiveDoc
 if (theView.GetThemes.Count = 0) then
    msgbox.error("No themes found", Script.The.GetName)
    exit
  end
?---------------------------
?--- Set analysis extent ---
?---------------------------
? bring up the AnalysisPropertiesDialog
theAE = AnalysisPropertiesDialog.Show(theView,FALSE,"Analysis Properties")
  if (theAE=nil) then
    exit
  end
theExtent = Rect.Make(0@0,1@1)
theCellSize = 1
if ((theAE.GetExtent(theExtent) <> #ANALYSISENV_VALUE) or
    (theAE.GetCellSize(theCellSize) <> #ANALYSISENV_VALUE)) then
  theCE = AnalysisPropertiesDialog.Show(theView,TRUE,"Analysis Extent")
  ? check for Cancel from dialog
  if (theCE = NIL) then
    return NIL
  end
  theCE.GetCellSize(theCellSize)
  theCE.GetExtent(theExtent)
end
Grid.SetAnalysisCellSize ( #GRID_ENVTYPE_VALUE , theCellSize )
Grid.SetAnalysisExtent ( #GRID_ENVTYPE_VALUE , theextent )
?-----------------------------
?--- Set working directory ---
?-----------------------------
aProject=av.GetProject
defaultdir=aProject.GetWorkDir
inputdir=MsgBox.Input("Choose the working
directory.",Script.The.GetName,defaultdir.asstring)
  if (inputdir=nil) then
  else
    aDirName = inputdir.asfilename
    aProject.SetWorkDir (aDirName)
  end
?----------------------
?--- Get the themes ---
?----------------------
?------------------------
?--- Impervious cover ---
?------------------------
icList=list.Make
  for each thm in TheView.GetThemes
    if(thm.is(Ftheme))then
      if(thm.GetFtab.GetShapeClass.GetClassName="Polygon")then
        icList.add(thm)
      end
    else
      if(thm.is(Gtheme))then
        iclist.add(thm)
      end
     end
  end
icthm=Msgbox.ChoiceAsString(icList,"Choose an impervious cover
theme.",Script.The.GetName)
  if(icthm=nil)then
    exit
  end
?------------------------
?--- Examine IC theme ---
?------------------------
  if (icthm.is(Gtheme)) then
    ic_gr=icthm.getgrid
  else
    theFtab=icthm.getFtab
    theFtab.seteditable(true)
    fieldlist=theftab.getfields
    impc = MsgBox.ChoiceAsString(fieldList,"Choose an IC field.",Script.The.GetName)
      if (impc = nil) then
        Msgbox.info("Can?t find IC field in polygon theme",Script.The.GetName)
        exit
     end
  end
  ?---------------------------
?--- Flow direction grid ---
?---------------------------
278
gridList=list.Make
  for each thm in TheView.GetThemes
    if(thm.is(Gtheme))then
      gridList.add(thm)
    end
  end
fdrthm=Msgbox.ChoiceAsString(gridList,"Choose a flow direction
grid.",Script.The.GetName)
  if(fdrthm=nil)then
    exit
  end
fdirgrid=fdrthm.getgrid
?-----------------------
?--- Correction grid ---
?-----------------------
corrcoefthm=Msgbox.ChoiceAsString(gridList,"Choose a correction
grid.",Script.The.GetName)
  if(corrcoefthm=nil)then
    exit
  end
thethm=corrcoefthm
corrcoef=thethm.getgrid
?----------------
?--- Recharge ---
?----------------
recharge=msgbox.yesno("Do you want to consider a recharge
zone?",Script.The.GetName,true)
  if (recharge=true) then
?Recharge flow
      rechfacthm=Msgbox.ChoiceAsString(gridList,"Choose a recharge grid
(rech_fac).",Script.The.GetName)
        if(rechfacthm=nil)then
          exit
        end
      rechfac=rechfacthm.getgrid
?Recharge cell
      cellrech=Msgbox.ChoiceAsString(gridList,"Choose a cell recharge grid
(lcorr_rech).",Script.The.GetName)
        if(cellrech=nil)then
          exit
        end
      lcorr_rech=cellrech.getgrid
  end
?---------------------------
?--- Precipitation value ---
?---------------------------
?Rainfall amount in in/yr
prec=31.08
preccoef=prec/31.08
?----------------------
?--- Name the grids ---
?----------------------
outname1=av.getproject.makefilename("runoff","")
aname1=filedialog.put(outname1,"","Direct Runoff")
outname2=av.getproject.makefilename("baseflow","")
aname2=filedialog.put(outname2,"","Baseflow")
outname3=av.getproject.makefilename("flow","")
aname3=filedialog.put(outname3,"","Total flow")
?-------------------------------------
?--- Calculate runoff coefficients ---
?-------------------------------------
  if(icthm.is(ftheme)) then
    rel=msgbox.yesno("Do you want to recompute the runoff coefficients?",
Script.The.GetName, true )
  else
    rel=true
  end
  if (rel) then
?Create the direct runoff coefficient field
      if (icthm.is(ftheme)) then
279
        runco = theFtab.findfield("runcoef")
          if (runco = nil) then
            theFtab.seteditable(true)
            runco = field.make("runcoef", #FIELD_DECIMAL, 6, 3)
            theFtab.addfields({runco})
            theFtab.seteditable(false)
          else
            question=Msgbox.yesno("The field runcoef already exists. Do you want to overwrite
it?",Script.The.GetName,true)
              if (question=false) then
                runcofield = Msgbox.input("Name of the direct runoff coefficients
field:",Script.The.GetName,"runcoef1")
                  if (runcofield=nil) then
                    exit
                  end
                theFtab.seteditable(true)
                runco = field.make(runcofield.asstring, #FIELD_DECIMAL, 6, 3)
                theFtab.addfields({runco})
                theFtab.seteditable(false)
              end
          end
?Create the base flow runoff coefficient field
        runco_bf = theFtab.findfield("runcoef_bf")
          if (runco_bf = nil) then
            theFtab.seteditable(true)
            runco_bf = field.make("runcoef_bf", #FIELD_DECIMAL, 6, 3)
            theFtab.addfields({runco_bf})
            theFtab.seteditable(false)
          else
            question=Msgbox.yesno("The field runcoef_bf already exists. Do you want to
overwrite it?",Script.The.GetName,true)
              if (question=false) then
                runcobffield= Msgbox.input("Name of the base flow runoff coefficients
field:",Script.The.GetName,"runcoef_bf1")
                  if (runcobffield=nil) then
                    exit
                  end
                theFtab.seteditable(true)
                runco_bf = field.make(runcobffield.asstring, #FIELD_DECIMAL, 6, 3)
                theFtab.addfields({runco})
                theFtab.seteditable(false)
              end
           end
      end
?Calculate runoff coefficient for direct runoff
    rel1 = msgbox.yesno("The ic/runoff coefficient relationship for direct runoff is: runcoef =
0.3428*IC^2 + 0.5677*IC + 0.0125 (0<IC<1) Do you want to change it?" , "Runoff
coefficient " , true)
      if (rel1) then
        labels={"a","b","c"}
        defaults={"0.3428","0.5677","0.0125"}
        coeflist=MsgBox.MultiInput ("runcoef = a*IC^2 + b*IC + c and 0<IC<1", "Direct runoff
coefficients",labels, defaults)
        a1=coeflist.get(0)
        b1=coeflist.get(1)
        c1=coeflist.get(2)
        a=a1.asnumber
        b=b1.asnumber
        c=c1.asnumber
          if (icthm.is(Ftheme)) then
            theFtab.seteditable(true)
            icmax=0
              for each rec in theFTab
                ic1 = theFtab.returnvalue(impc,rec)
                icmax=icmax.max(ic1)
              end
              if (icmax > 1) then
                icperc=true
              else
                icperc=false
              end
              for each rec in theFtab
                ic1 = theFtab.returnvalue(impc, rec)
                  if (icperc=true) then
                    ic1=ic1/100
                  end
                runco1 = (a*ic1*ic1)+(b*ic1)+c
                theFtab.setvalue(runco , rec , runco1 )
              end
            theFtab.seteditable(false)
          else
            aprj=theview.getprojection
            icint=ic_gr.int
            icvtab=icint.getvtab
            icfield=icvtab.findfield("value")
              icmax=0
              for each rec in icvtab
                icvalue=icvtab.returnvalue(icfield,rec)
                icmax=icmax.max(icvalue)
              end
              if (icmax<=1) then
280
                runcoef = (a.asgrid*ic_gr*ic_gr)+(b.asgrid*ic_gr)+c.asgrid
              else
                runcoef = (0.0001.asgrid*a.asgrid*ic_gr*ic_gr) + ( 0.01.asgrid * b.asgrid *ic_gr) +
c.asgrid
              end
          end
    else
    ?default value
       if (icthm.is(Ftheme)) then
         theFtab.seteditable(true)
           icmax=0
           for each rec in theFTab
             ic1 = theFtab.returnvalue(impc,rec)
             icmax=icmax.max(ic1)
           end
           if (icmax>1)then
             icperc = true
           else
             icperc = false
           end
           for each rec in theFtab
             ic1 = theFtab.returnvalue(impc, rec)
               if (icperc=true) then
                 ic1=ic1/100
               end
              runco1 = (0.3428*ic1*ic1)+(0.5677*ic1)+0.0125
              theFtab.setvalue(runco , rec , runco1 )
           end
        theFtab.seteditable(false)
       else
         aprj=theview.getprojection
          icint=ic_gr.int
          icvtab=icint.getvtab
          icfield=icvtab.findfield("value")
          icmax=0
            for each rec in icvtab
              icvalue=icvtab.returnvalue(icfield,rec)
              icmax=icmax.max(icvalue)
            end
              if (icmax<=1) then
                runcoef=(0.3428.asgrid*ic_gr*ic_gr)+(0.5677.asgrid*ic_gr)+0.0125.asgrid
              else
runcoef=(0.0001.asgrid*0.3428.asgrid*ic_gr*ic_gr)+(0.01.asgrid*0.5677.asgrid*ic_gr)+0.012
5.asgrid
           end
       end
    end
?Calculate runoff coefficient for baseflow
rel2 = msgbox.yesno("The ic/runoff coefficient relationship for base flow is: runcoef_bf = -
0.36*IC + 0.1904 if IC < 52% and 0 otherwise (0<IC<1) Do you want to change it?" , "Base
flow runoff coefficients" , true)
  if (rel2) then
    labels={"a","b"}
    defaults={"-0.36","0.1904"}
    bfcoeflist=MsgBox.MultiInput("runcoef_bf = a*IC + b and 0<IC<1","Base flow runoff
coefficients",labels,defaults)
    a1=bfcoeflist.get(0)
    b1=bfcoeflist.get(1)
    a=a1.asnumber
    b=b1.asnumber
      if (icthm.is(Ftheme)) then
        theftab.seteditable(true)
          for each rec in theFtab
            if (icperc=true) then
              ic1=ic1/100
            end
            ic1 = theFtab.returnvalue(impc, rec)
            runco2 = (a*ic1)+b
              if (runco2<0) then
                runco2 = 0
              end
            theFtab.setvalue(runco_bf , rec , runco2 )
          end
        theftab.seteditable(false)
       else
         if (icmax=1 <=1) then
           runcoef1_bf = (a.asgrid*ic_gr)+b.asgrid
         else
            runcoef1_bf = (0.01.asgrid*a.asgrid*ic_gr)+b.asgrid
          end
         runcoef_bf=(runcoef1_bf>0.asgrid).con(runcoef1_bf, 0.asgrid)
       end
   else
     if (icthm.is(ftheme)) then
       theftab.seteditable(true)
         for each rec in theFtab
            ic1 = theFtab.returnvalue(impc, rec)
              if (icperc=true)
                then ic1=ic1/100
              end
            runco2 = -0.36*ic1+0.1904
              if (runco2<0) then
281
                runco2 = 0
              end
            theFtab.setvalue(runco_bf , rec , runco2 )
          end
         theftab.seteditable(false)
      else
        if (icmax<=1) then
          runcoef1_bf = (-0.36.asgrid*ic_gr)+0.1904.asgrid
        else
          runcoef1_bf = (-0.0036.asgrid*ic_gr)+0.1904.asgrid
        end
        runcoef_bf=(runcoef1_bf>0.asgrid).con(runcoef1_bf, 0.asgrid)
      end
    end
  end
?-----------------------------------------------------
?--- Create the runoff coefficient grids if needed ---
?-----------------------------------------------------
aPrj=theView.GetProjection
  if (icthm.is(ftheme)) then
    anFtab=icthm.getftab
    aField1 = anFtab.findfield("runcoef")
    runcoef = Grid.MakeFromFTab(anFTab, aPrj, aField1, {thecellSize, theextent})
    aField2 = anFtab.findfield("runcoef_bf")
    runcoef_bf = Grid.MakeFromFTab(anFTab, aPrj, aField2, {thecellSize, theextent})
  end
?---------------------------
?--- Corrected cell flow ---
?---------------------------
?Corrected direct cell runoff
runcoefname = av.getproject.makefilename("runcoef","")
runcoef.savedataset(runcoefname)
runoff = runcoef * corrcoef * 31.08.asgrid * 5.asgrid / 189216.asgrid*preccoef.asgrid
runoffname = av.getproject.makefilename("runcel","")
runoff.savedataset(runoffname)
grid.deletedataset(runcoefname)
runoffgtheme = gtheme.make(runoff)
theview.addtheme(runoffgtheme)
runoffgtheme.setlegendvisible(false)
?Corrected base flow cell runoff (cfs)
if (icthm.is(gtheme)) then
  bfcoef1name = av.getproject.makefilename("bf1coef","")
  runcoef1_bf.savedataset(bfcoef1name)
end
bfcoefname = av.getproject.makefilename("bfcoef","")
runcoef_bf.savedataset(bfcoefname)
baseflow = runcoef_bf * corrcoef * 31.08.asgrid * 5.asgrid / 189216.asgrid * preccoef.asgrid
bflowname = av.getproject.makefilename("bflowcell","")
baseflow.savedataset(bflowname)
grid.deletedataset(bfcoefname)
if (icthm.is(gtheme)) then
  grid.deletedataset(bfcoef1name)
end
bflowgtheme = gtheme.make(baseflow)
theview.addtheme(bflowgtheme)
bflowgtheme.setlegendvisible(false)
?----------------------
?--- Corrected flow ---
?----------------------
?Flowaccumulation
runoff_flow0 = (fdirgrid.flowaccumulation(runoff))
baseflow_gr0 = (fdirgrid.flowaccumulation(baseflow))
totalflow0 = baseflow_gr0 + runoff_flow0
  if (recharge=false) then
    runoff_flow0.savedataset(aname1)
    runoffgtheme = gtheme.make(runoff_flow0)
    theview.addtheme(runoffgtheme)
    runoffgtheme.setlegendvisible(false)
    baseflow_gr0.savedataset(aname2)
    baseflowgtheme = gtheme.make(baseflow_gr0)
    theview.addtheme(baseflowgtheme)
    baseflowgtheme.setlegendvisible(false)
    totalflow0.savedataset(aname3)
    tflow0gtheme = gtheme.make(totalflow0)
    theview.addtheme(tflow0gtheme)
    tflow0gtheme.setlegendvisible(false)
  else
282
    runoff0name = av.getproject.makefilename("rnoff0","")
    runoff_flow0.savedataset(runoff0name)
    bflow0name = av.getproject.makefilename("bflow0","")
    baseflow_gr0.savedataset(bflow0name)
    tflow0name = av.getproject.makefilename("tflow0","")
    totalflow0.savedataset(tflow0name)
    tflow0gtheme = gtheme.make(totalflow0)
    theview.addtheme(tflow0gtheme)
    tflow0gtheme.setlegendvisible(false)
?-----------------------------------------
?--- Corrected flow with recharge zone ---
?-----------------------------------------
?Predicted flow
totalflow = totalflow0 - rechfac
totalflow.savedataset(aname3)
totalflowgtheme = gtheme.make(totalflow)
theview.addtheme(totalflowgtheme)
totalflowgtheme.setlegendvisible(false)
?Part of base flow
partbase = baseflow_gr0 / totalflow0
?partbasename = av.getproject.makefilename("partbf","")
?partbase.savedataset(partbasename)
?partbasegtheme = gtheme.make(partbase)
?theview.addtheme(partbasegtheme)
?partbasegtheme.setlegendvisible(false)
?Direct runoff
runcell_rech = lcorr_rech * (1.asgrid - partbase)
runoff_rech = (fdirgrid.flowaccumulation(runcell_rech))
runcrechname = av.getproject.makefilename("rcrech","")
runcell_rech.savedataset(runcrechname)
runoff_flow = runoff_flow0 - runoff_rech
grid.deletedataset(runcrechname)
runoff_flow.savedataset(aname1)
runoffgtheme = gtheme.make(runoff_flow)
theview.addtheme(runoffgtheme)
runoffgtheme.setlegendvisible(false)
grid.deletedataset(runoff0name)
?Base flow
bf_rech = rechfac - runoff_rech
baseflow_gr = baseflow_gr0 - bf_rech
baseflow_gr.savedataset(aname2)
baseflowgtheme = gtheme.make(baseflow_gr)
theview.addtheme(baseflowgtheme)
baseflowgtheme.setlegendvisible(false)
grid.deletedataset(bflow0name)
end
?Message to user
msgbox.info("Flow grids calculated",Script.The.GetName)
?-----------
?--- END ---
?-----------
?Script: Qual.HydroZdlsv
?**********************************************
? this program assigns to single-cell poly the
? grid-code of its adjcent polygon
?**********************************************
TheProject=av.GetProject
TheView=av.getactiveDoc
ThemeList=TheView.Getthemes
 LineList=list.make
 PolyList=list.make
 for each thm in Themelist
  if(Thm.Is(FTheme))then
   if(thm.getFtab.FindField("Shape").getType=#FIELD_SHAPELINE)then
     LineList.add(thm)
   end
   if(thm.getFtab.FindField("Shape").getType=#FIELD_SHAPEPOLY)then
     Polylist.add(thm)
   end
  end  ?if(Thm.Is(Ftheme))then
 end  ?for each thm in Themelist
PTheme=msgbox.choiceAsString(Polylist,"Pick a Basin polygon
theme",Polylist.get(0).getFtab.GetName)
  if (Ptheme=nil) then
  exit
  end
LTheme=msgbox.choiceasString(LineList,"Pick a Basin boundary
theme",Linelist.get(0).getFtab.GetName)
  if (Ptheme=nil) then
283
  exit
  end
 if (LTheme.Is(FTHEME).not) then
  msgbox.error(LTheme.Getname++"IsNotFtheme","")
  exit
 end
 if (Ptheme.Is(FTHEME).not) then
  msgbox.error(Ptheme.Getname++"IsNotFtheme","")
  exit
 end
PFtab=PTheme.GetFtab
LFtab=LTheme.GetFtab
 if(PFtab.CanEdit)then
  PFtab.SetEditable(true)
 else
  msgbox.info("PFTAB.CAN?TEDIT",Script.The.GetName++"001")
  exit
 end
LLPoly=LFtab.FindField("LPOLY#")
LRPoly=LFtab.FindField("RPOLY#")
if(LLPoly=nil)then
 LLpoly=LFtab.FindField("LPOLY_")
 LRpoly=LFtab.FindField("RPOLY_")
end
PArea=PFtab.FindField("AREA")
PGCODE=PFtab.FindField("Grid-Code")
  if(PGCODE=nil)then
    PGCODE=PFtab.FindField("Grid_Code")
  end
PCovNo=PFtab.FindField(PTheme.GetName+"_")
  if(PCovNo=nil)then
    PCovNo=PFtab.FindField(PTheme.GetName+"#")
   end
if(PcovNo=nil)then
  Pflds=PFtab.GetFields
  PcovNo=msgbox.choiceasString(PFlds,"Select a field as Cov_ or
Cov#",Script.The.GetName)
  if(PcovNo=nil)then
    exit
  end
end
doneDict=dictionary.make(PFtab.GetNumRecords)  ?counting for the polys that has been
chked
tmplist=list.make
for each rec in PFtab
 doneDict.add(rec.AsString.AsNumber,0)
 tmplist.add(rec.AsString.AsNumber)
end
?  chk=msgbox.choiceAsString(tmplist,"dcnt="+tmplist.count.asString,"OKHERE")
?  if (chk=nil)then
?   e x i t
?  e n d
ddlist=list.make   ?holding poly?s recnum
kn=0
tnn=PFtab.getNumRecords
for each rec in PFtab
av.ShowMsg(rec.AsString+"of"+tnn.AsString+"looped"+kn.AsString+"RecsAddedToDDlist"
)
 av.SetStatus(rec/(Tnn-1)*100)
  if(doneDict.get(rec)=1)then      ?if the record (poly) has been chked, skip
   continue
  end
 GridV=PFtab.ReturnValue(PGCode,rec)
 PFound=False                      ?PFound is set to True in the following loop is another
                                   ?poly with the same grid-code is found
 tmplist.empty                     ?tmplist holds the polys with the same grid-code
 maxarea=0.0
 for each prec in PFtab
   if(doneDict.get(prec)=1)then    ?if the Poly has been chked, skip
    continue
   end
   if(Prec=rec)then                ?if the Poly is the current Poly, skip
    continue
   end
   GridC=PFtab.ReturnValue(PGCode,prec)   ?gets the GCode of the current poly
    if(GridC=GridV)then                   ?The current GCode=TheGCode of the poly on the outer
loop
      PFound=true
      if(tmplist.count=0)then             ?Put the Poly on the outer loop into the tmplist
        doneDict.set(rec.Asstring.AsNumber,1)
        kn=kn+1
        tmprec=rec.AsString
        maxrec=tmprec.AsNumber
        tmplist.add(tmprec.Asnumber)
        maxarea=PFtab.ReturnValue(Parea,rec)
      end
     tmparea=PFtab.ReturnValue(Parea,prec)
      if(tmparea>maxarea)then
        maxarea=tmparea
        maxrec=prec.Asstring.AsNumber     ?Keep track of Max Area Poly
      end
     tmplist.add(prec.AsString.AsNumber)  ?Put the current Poly on the inner loop into the list
     doneDict.set(prec.AsString.AsNumber,1)
     kn=kn+1
    end  ?endif(gridC=gridV)
 end  ?endfor each prec in PFtab
284
   if(PFound=true)then                    ?Whenever PFound=Ture, keep the poly with MaxArea, the
rest goes to ddlist
     for each ii in tmplist
       if(ii=maxrec)then
        continue
       else
        ddlist.add(ii.AsString.AsNumber)
       end
     end  ?end for ii in tmplist
   end ?endif(PFound=true)
end ?for each rec in PFtab
?*******************************************
? assign new grid-code to polygons in the
? dlist
?*******************************************
dcnt=ddlist.count
  chk=msgbox.choiceAsString(ddlist,"dcnt="+dcnt.asString,"OKHERE")
  if (chk=nil)then
   exit
  end
dcrt=0
 if(dcnt=0)then
  msgbox.error("dlistHasZeroMembers",Script.The.GetName++"EXIT-002")
  exit
 end
for each drec in ddlist          ?For now,after running this program,one needs to use
ARC/INFO?s Dissolve function to dissolve the polys in the ddlinst
 av.setstatus(dcrt/dcnt*100)
 av.showMsg((dcrt+1).Asstring+" of "+dcnt.AsString+" corrected")
 Pcov=PFtab.ReturnValue(PcovNo,drec)
 PFound=False
 nextFound=False
 for each lrec in lFtab
  LpolyV=LFtab.ReturnValue(LLpoly,lrec)
  RpolyV=LFtab.ReturnValue(LRpoly,lrec)
   if(LpolyV=Pcov)then
    PFound=True
    for each prec in PFtab
     PcovC=PFtab.ReturnValue(PCovNo,prec)
      if(PcovC=RpolyV)then
       nextFound=true
       PFtab.SetValue(PGCode,drec,PFtab.ReturnValue(PGCode,prec))
       dcrt=dcrt+1
       break
      end
    end  ?for each prec in PFtab
   end   ?if(LpolyV=Pcov)then
 if((PFound=True) and (NextFound=true))then
  break
 elseif((PFound=true) and (nextFound=False))then
  chk=msgbox.input("pfound=true,nextFound=False","Pcov="+Pcov.AsString,"EXITLpoly")
  if(chk=nil)then
  exit
  end
  PFound=False
 else
  PFound=False
  NextFound=False
 end
   if(RpolyV=Pcov)then
    PFound=True
    for each prec in PFtab
     PcovC=PFtab.ReturnValue(PCovNo,prec)
      if(PcovC=LpolyV)then
       nextFound=true
       PFtab.SetValue(PGCode,drec,PFtab.ReturnValue(PGCode,prec))
       dcrt=dcrt+1
       break
      end
    end  ?for each prec in PFtab
   end   ?if(RpolyV=Pcov)then
 if((PFound=True) and (NextFound=true))then
  break
 elseif((PFound=true) and (nextFound=False))then
  chk=msgbox.input("pfound=true,nextFound=False","Pcov"+Pcov.AsString,"EXITRpoly")
  if(chk=nil)then
  exit
  end
  PFound=False
 else
  PFound=False
  NextFound=False
 end
end ?end for each lrec in LFtab
 if(PFound=False)then
  chk=msgbox.input("pfound=False","Pcov="+Pcov.AsString,"EXITforeachLFtab")
  if(chk=nil)then
   exit
  end
 end
end ?end for each drec in ddlist
av.SetStatus(100)
PFtab.SetEditable(false)
??/export/home1/ye/dissolve.822 of 55 lines,
??Written on Wed Sep  6 13:42:55 CDT 1995 by ye
??/export/home1/ye/dissolve.822 of 182 lines,
??Written on Thu Sep  7 15:20:08 CDT 1995 by ye
??/home/ye/sos/dissolve.utl of 182 lines,
??Written on 1996:06:13-09:20:33 by yeZ.
??/home/ye/soflow/dosave/SFdslv.pre of 184 lines,
285
??Written on 1992:10:19-10:33:53 by YEZ.
??/appdev/approg/ye/ngflow/dosave/SFdslv.utl of 187 lines,
??Written on 1996:11:05-08:56:24 by YEZ.
?Script Qual.Join
?----------------------------
?--- Creation information ---
?----------------------------
?Name: Qual.Join
?Version: 1.0
?Date: 10/3/97
?Author: Christine Dartiguenave
?        Center for Research in Water Resources
?        The University of Texas at Austin
?        darti@crwr.utexas.edu
?---------------------------
?--- Purpose/Description ---
?---------------------------
?Join two tables and keep them joined.
?----------------------
?--- Get the tables ---
?----------------------
doculist = av.GetProject.Getdocs
tablelist=List.Make
      for each d in doculist
        if(d.Is(Table))then
          TableList.add(d)
        end
      end
?-------------------------
?--- Destination table ---
?-------------------------
tab1 = Msgbox.ChoiceAsString(tableList,"Destination table",Script.The.GetName)
if (tab1=nil)
  then msgbox.info("No destination table selected", Script.The.GetName)
  exit
end
vtab1 = tab1.GetVTab
fieldlist1 = vtab1.getfields
field1 = MsgBox.choiceAsString(fieldlist1, "Common field for destination table" ,
Script.The.GetName)
if (field1=nil) then
  MsgBox.Info("No field selected", Script.The.GetName)
  exit
end
n=fieldlist1.count
?--------------------
?--- Source table ---
?--------------------
tab2 = Msgbox.ChoiceAsString(TableList,"Source table",Script.The.GetName)
if (tab2=nil) then
  MsgBox.Info("No source table selected", Script.The.GetName)
  exit
end
vtab2 = tab2.GetVtab
fieldlist2 = vtab2.getFields
field2 = MsgBox.choiceAsString(fieldlist2, "Common field for source table" ,
Script.The.GetName)
if (field2=nil) then
  MsgBox.info("No field selected", Script.The.GetName)
  exit
end
?-------------------------
?--- Join the tables ---
?-------------------------
vtab1.Join( field1, vtab2, field2)
?----------------------
?--- Add new fields ---
?----------------------
fieldlist3=vtab1.getfields
p=fieldlist3.count
q=p-1
vtab1.seteditable(true)
i=n
for each i in n.. q
  oldfield=fieldlist3.get(i)
  newfield=oldfield.clone
286
  newfieldlist=list.make
  newfieldlist.add(newfield)
  vtab1.addfields(newfieldlist)
    for each rec in vtab1
      val=vtab1.returnvalue(oldfield,rec)
      vtab1.SetValue (newfield, rec, val)
    end
i=i+1
end
vtab1.seteditable(false)
?------------------------
?--- Remove all joins ---
?------------------------
vTab1.UnjoinAll
msgbox.info("Tables joined",Script.The.GetName)
?-----------
?--- End ---
?-----------
?Script Qual.load
?
?----------------------------
?--- Creation information ---
?----------------------------
?
?Name: Qual.Load
?Version: 1.0
?Date: 05/28/97
?Modified: 10/21/97
?Author: Christine Dartiguenave
?        Center for Research in Water Resources
?        The University of Texas at Austin
?        darti@crwr.utexas.edu
?
?---------------------------
?--- Purpose/Description ---
?---------------------------
?This program computes the loads.
?--------------------
?--- Get the View ---
?--------------------
theView=av.GetActiveDoc
if (theView.GetThemes.Count = 0) then
   msgbox.error("No Themes found", Script.The.GetName)
   exit
end
?---------------------------
?--- Set analysis extent ---
?---------------------------
? bring up the AnalysisPropertiesDialog
theAE = AnalysisPropertiesDialog.Show(theView,FALSE,"Analysis Properties")
  if (theAE=nil) then
    exit
  end
theExtent = Rect.Make(0@0,1@1)
theCellSize = 1
if ((theAE.GetExtent(theExtent) <> #ANALYSISENV_VALUE) or
    (theAE.GetCellSize(theCellSize) <> #ANALYSISENV_VALUE)) then
  theCE = AnalysisPropertiesDialog.Show(theView,TRUE,"Analysis Extent")
  ? check for Cancel from dialog
  if (theCE = NIL) then
    return NIL
  end
  theCE.GetCellSize(theCellSize)
  theCE.GetExtent(theExtent)
end
Grid.SetAnalysisCellSize ( #GRID_ENVTYPE_VALUE , theCellSize )
Grid.SetAnalysisExtent ( #GRID_ENVTYPE_VALUE , theextent )
?-----------------------------
?--- Set working directory ---
?-----------------------------
aProject=av.GetProject
defaultdir=aProject.GetWorkDir
287
inputdir=MsgBox.Input("Choose the working
directory.",Script.The.GetName,defaultdir.asstring)
  if (inputdir=nil) then
  else
    aDirName = inputdir.asfilename
    aProject.SetWorkDir (aDirName)
  end
?----------------------
?--- Get the tables ---
?----------------------
doculist = av.GetProject.Getdocs
tablelist=List.Make
      for each d in doculist
        if(d.Is(Table))then
          TableList.add(d)
        end
      end
?Direct runoff
emcruntable=Msgbox.ChoiceAsString(tableList,"Choose a direct runoff EMCs
table",Script.The.GetName)
    if(emcruntable=nil)then
      msgbox.error("No direct runoff EMCs table selected",Script.The.GetName)
      exit
    end
emcruntab=emcruntable.getvtab
emcrunlist=emcruntab.getfields
?Base flow
emcbftable=Msgbox.ChoiceAsString(tableList,"Choose a base flow EMCs
table",Script.The.GetName)
    if(emcbftable=nil)then
      msgbox.error("No base flow EMCs table selected",Script.The.GetName)
      exit
    end
emcbftab=emcbftable.getvtab
emcbflist=emcbftab.getfields
?Check that the tables correspond
i=0
  for each rec in emcruntab
    i=i+1
  end
m=i
i=0
  for each rec in emcbftab
    i=i+1
  end
n=i
  if (m=n) then
    p=n-1
    conslist=list.make
    for each i in 0..p
      runcons=emcrunlist.get(0)
      bfcons=emcbflist.get(0)
      runconsname=emcruntab.returnvaluestring(runcons,i)
      bfconsname=emcbftab.returnvaluestring(bfcons,i)
        if (runconsname=bfconsname) then
          i=i+1
          conslist.add(runconsname)
        else
          msgbox.error("The constituents in the two EMCs tables do not
correspond.",Script.The.GetName)
          exit
        end
    end
  else
    msgbox.error("The number of constituents in the two EMC tables is
different.",Script.The.GetName)
    exit
  end
?Choose the constituents to model
choices = MsgBox.MultiListAsString( conslist, "Choose the constituent(s) to model",
Script.The.GetName )
  if (choices = nil) then
    msgbox.info("No constituent selected.", Script.The.GetName)
    exit
  else
    namelist=list.make
    for each cons in choices
        outFName = av.GetProject.MakeFileName(cons, "")
        aName = FileDialog.Put(outFName, "", cons)
          if (aName = Nil) then
            exit
          end
288
        namelist.add(aname)
    end
  end
?----------------------
?--- Get the themes ---
?----------------------
undev=0.15
icList=list.Make
  for each thm in TheView.GetThemes
    if(thm.is(Ftheme))then
      if(thm.GetFtab.GetShapeClass.GetClassName="polygon")then
       icList.add(thm)
      end
    else
      if (thm.is(Gtheme)) then
       iclist.add(thm)
      end
   end
  end
icthm=Msgbox.ChoiceAsString(icList,"Choose an impervious cover
theme.",Script.The.GetName)
    if(icthm=nil)then
      exit
    end
gridList=list.Make
  for each thm in TheView.GetThemes
    if(thm.is(Gtheme))then
       gridList.add(thm)
     end
  end
fdrthm=Msgbox.ChoiceAsString(gridList,"Choose a flow direction
grid.",Script.The.GetName)
    if(fdrthm=nil)then
      exit
    end
fdirgrid=fdrthm.getgrid
zonethm=Msgbox.ChoiceAsString(gridList,"Choose a water landuse theme
(zone_gr).",Script.The.GetName)
    if(zonethm=nil)then
      exit
    end
zone=zonethm.getgrid
runoffthm=Msgbox.ChoiceAsString(gridList,"Choose a corrected runoff cell grid
(runcel1).",Script.The.GetName)
    if(runoffthm=nil)then
      exit
    end
runoff=runoffthm.getgrid
baseflowthm=Msgbox.ChoiceAsString(gridList,"Choose a corrected baseflow cell grid
(bflowc1).",Script.The.GetName)
    if(baseflowthm=nil)then
      exit
    end
baseflow=baseflowthm.getgrid
?Recharge zone
recharge=msgbox.yesno("Do you want to consider a recharge
zone?",Script.The.GetName,true)
  if (recharge=true) then
    lcellrechthm=Msgbox.ChoiceAsString(gridList,"Choose a cell recharge grid
(lcorr_rech).",Script.The.GetName)
      if(lcellrechthm=nil)then
        exit
      end
    lcellrech=lcellrechthm.getgrid
    totalflowthm=Msgbox.ChoiceAsString(gridList,"Choose a total flow grid (without
recharge, tflow01).",Script.The.GetName)
    if(totalflowthm=nil)then
      exit
    end
totalflow=totalflowthm.getgrid
289
  end
  if (icthm.is(Gtheme)) then
    ic_gr=icthm.getgrid
  else
?Coverage
?---------------------
?--- Get the table ---
?---------------------
    theFtab=icthm.getFtab
    fieldlist=theftab.getfields
    impc = MsgBox.choiceasstring( fieldlist,"Name of IC field", Script.The.GetName)
      if (impc = nil) then
        addfield1 = msgbox.yesno("Can not find ?IC? field in polygon theme.  Add
it?",Script.The.GetName, true)
        exit
      end
  end
?---------------------------
?--- Calculate EMC values---
?---------------------------
  k=0
  for each cons in choices
    if (icthm.is(Ftheme)) then
      theftab.seteditable(true)
?Check storm runoff field
      consfield = theFtab.findfield(cons+"_[mg/l]")
        if (consfield = nil) then
          consfield = field.make(cons+"_[mg/l]", #FIELD_DECIMAL, 6, 3)
          theFtab.addfields({consfield})
        end
?Check base flow field
      consfieldbf = theFtab.findfield(cons+"_bf_[mg/l]")
        if (consfieldbf = nil) then
          consfieldbf = field.make(cons+"_bf_[mg/l]", #FIELD_DECIMAL, 6, 3)
          theFtab.addfields({consfieldbf})
        end
   end
?Calculate EMC
?Direct runoff
?Get the parameters a and b (emc=a+b*ic,0<ic<1)
            i=0
            for each rec in emcruntab
              runconsname=emcruntab.returnvaluestring(runcons,rec)
                if (runconsname=cons) then
                  p=i
                else
                  i=i+1
                end
            end
            afield=emcrunlist.get(1)
            bfield=emcrunlist.get(2)
            a=emcruntab.returnvalue(afield,p)
            b=emcruntab.returnvalue(bfield,p)
            if (icthm.is(Ftheme)) then
              icmax=0
              for each rec in theFTab
                ic1 = theFtab.returnvalue(impc,rec)
                icmax=icmax.max(ic1)
              end
            if (icmax>1)then
             icperc = true
           else
             icperc = false
           end
              for each rec in theFtab
                ic1 = theFtab.returnvalue(impc, rec)
                  if (icperc=true) then
                    ic1=ic1/100
                  end
                emcrun=b*ic1+a
                theFtab.setvalue(consfield , rec , emcrun )
              end
            else
290
            aprj=theview.getprojection
            icint=ic_gr.int
            icvtab=icint.getvtab
            icfield=icvtab.findfield("value")
              icmax=0
              for each rec in icvtab
                icvalue=icvtab.returnvalue(icfield,rec)
                icmax=icmax.max(icvalue)
              end
              if (icmax<=1) then
                emc_gr = ic_gr*b + a.asgrid
              else
                emc_gr = ic_gr*b*0.01 + a.asgrid
              end
            end
?Base flow
                  afield=emcbflist.get(1)
                  bfield=emcbflist.get(2)
                  a=emcbftab.returnvalue(afield,p)
                  b=emcbftab.returnvalue(bfield,p)
                if (icthm.is(Ftheme)) then
                    for each rec in theFtab
                      ic1=theftab.returnvalue(impc,rec)
                        if (icperc=true) then
                          ic1=ic1/100
                      end
                        if (ic1 <= undev) then
                          emcbf=a
                        else
                          emcbf=b
                        end
                      theFtab.setvalue(consfieldbf , rec , emcbf )
                     end
                 else
                   if (icmax<=1) then
                     emcbf_gr =(ic_gr>undev.asgrid).con(b.asgrid , a.asgrid)
                   else
                     undev=undev/100
                     emcbf_gr = (ic_gr>undev.asgrid).con(b.asgrid,a.asgrid)
                   end
                 end
?-------------------------
?--- Compute the loads ---
?-------------------------
if(icthm.is(ftheme)) then
  anftab=theftab
  aPrj = theView.GetProjection
end
  if(icthm.is(ftheme)) then
?direct runoff emc
    emc_gr = Grid.MakeFromFTab(anFTab, aPrj, consfield, {thecellSize, theextent})
?baseflow emc
    emcbf_gr = Grid.MakeFromFTab(anFTab, aPrj, consfieldbf, {thecellSize, theextent})
  end
loadcell = runoff *  emc_gr * 3.048.asgrid * 3.048.asgrid * 3.048.asgrid * 86400.asgrid *
365.asgrid / 1000000.asgrid
loadcellbf = baseflow *  emcbf_gr * 3.048.asgrid * 3.048.asgrid * 3.048.asgrid * 86400.asgrid
* 365.asgrid / 1000000.asgrid
?T o t a l
tcellload0 = loadcell+loadcellbf
tcellload=(zone=999).con(0.asgrid,tcellload0)
?Flowaccumulation
load0= (fdirgrid.flowaccumulation(tcellload))
  if (recharge=true) then
    co = load0/totalflow
?Recharge zone
    cellrech = lcellrech * co
    loadrech = (fdirgrid.flowaccumulation(cellrech))
?Total load
291
    load = load0-loadrech
  else
    load = load0
  end
aname=namelist.get(k)
load.savedataset(aname)
loadgtheme = gtheme.make(load)
theview.addtheme(loadgtheme)
loadgtheme.setlegendvisible(false)
k=k+1
end
msgbox.info("Load grid(s) calculated",Script.The.GetName)
?-----------
?--- END ---
?-----------
?Script Qual.Mergetheme
? Name:  View.MergeThemes
? Author: Zichuan Ye
? Title:  Merges two feature themes
?
? Topics:  GeoData
? Description:  Merges the selected themes into a single theme.  A new
? shapefile is created which combines the shapes and attributes of the
? active themes.  The themes to be merged should have the same set of
? attributes (fields).  Only the fields from the first active theme are
? preserved in the output theme.
? Requires:  At least two themes of the same feature type must be in the
? active view.
? S e l f :
? R e t u r n s :
theView   = av.GetActiveDoc
theThemes = theView.GetThemes
if (theThemes.Count < 2) then
  MsgBox.Error( "Must have at least two themes in a view to merge.","")
  exit
end
? Allow the user to choose themes from the view to be merged...
themesToMerge = List.Make
while (true)
  t = MsgBox.Choice( theThemes, "Choose themes in view to merge:"+NL+
    "(Click Cancel to end):", "Merge Themes" )
  if (t <> Nil) then
    themesToMerge.Add(t)
  else
    break
  end
end
if ((themesToMerge = Nil) or (themesToMerge.Count < 2)) then
  MsgBox.Error("Not enough themes to merge.", "")
  exit
end
? Themes must have matching shape types for merging.  Using the first
? active theme verify that this is the case...
checkType  = themesToMerge.Get(0).GetFtab.FindField("Shape").GetType
for each i in 1 .. (themesToMerge.Count - 1)
  t = themesToMerge.Get(i)
  if (checkType <> t.GetFTab.FindField("Shape").GetType) then
    MsgBox.Error("Theme feature type mismatch - Unable to merge.","")
    exit
  end
end
? Specify the output shapefile...
outFName = av.GetProject.MakeFileName("theme", "shp")
outFName = FileDialog.Put(outFName, "*.shp", "Output Merged Shapefile")
if (outFName = Nil) then
  exit
end
  ? Create the list of fields used for the output theme.  The fields
? are taken from the first active theme only, it is assumed that
? other themes have an identical set of fields.  If this is not the
? case the themes will still be merged, however fields not found in
? other themes will be empty...
fieldList = List.Make
for each f in themesToMerge.Get(0).GetFTab.GetFields
  if (f.GetName = "Shape") then
    continue
  else
292
    fCopy = f.Clone
    fieldList.Add(fCopy)
  end
end
? Get the class of new FTab to create, create the new FTab and
? add fields that we?ve gathered from the input themes....
shapeType = themesToMerge.Get(0).GetFTab.FindField("Shape").GetType
if (shapeType = #FIELD_SHAPELINE) then
  outClass = POLYLINE
elseif (shapeType = #FIELD_SHAPEMULTIPOINT) then
  outClass = MULTIPOINT
elseif (shapeType = #FIELD_SHAPEPOINT) then
  outClass = POINT
elseif (shapeType = #FIELD_SHAPEPOLY) then
  outClass = POLYGON
else
  MsgBox.Error("Invalid shape field type.", "Merge Themes")
  exit
end
mergeFTab = FTab.MakeNew( outFName, outClass )
if (fieldList.Count > 0) then
  mergeFTab.AddFields( fieldList )
end
? Populate the new FTab from the FTabs of the input themes...
for each t in themesToMerge
  av.ShowMsg( "Merging"++t.GetName )
  inFTab  = t.GetFTab
  if (inFTab.GetSelection.Count = 0) then
    theRecordsToMerge = inFTab
    numRecs = inFTab.GetNumRecords
  else
    theRecordsToMerge = inFTab.GetSelection
    numRecs = theRecordsToMerge.Count
  end
  for each rec in theRecordsToMerge
    av.SetStatus( (rec / numRecs) * 100 )
    newRec   = mergeFTab.AddRecord
    inField  = inFTab.FindField( "Shape" )
    outField = mergeFTab.FindField( "Shape" )
    mergeFTab.SetValue( outField, newrec, inFTab.ReturnValue( inField, rec ))
    if (fieldList.Count > 0) then
      for each f in fieldList
        fName    = f.GetName
        inField  = inFTab.FindField( fName )
        ? Skip field if not found in inFTab...
        if ( inField <> Nil ) then
          outField = mergeFTab.FindField( fName )
          aValue    = inFTab.ReturnValue( inField, rec )
          mergeFTab.SetValue( outField, newRec, aValue )
        end
      end   ? for each f
    end   ? if count
  end   ? for each rec
end   ? for each t
av.ClearMsg
av.ClearStatus
if (MsgBox.YesNo("Add shapefile as theme to a view?",
  "Merge Themes", true).Not) then
  exit
end
? Create a list of views and allow the user to choose which view to
? add the new theme to...
viewList = {}
for each d in av.GetProject.GetDocs
  if (d.Is(View)) then
    viewList.Add( d )
  end
end
? Include a choice for a new view...
viewList.Add("")
addToView = MsgBox.ListAsString( viewList,"Add Theme to:", "Merge Themes" )
? Get the specified view, make the theme, and add it...
if (addToView <> nil) then
  if (addToView = "") then
    addToView = View.Make
    addToView.GetWin.Open
  end
  mergeTheme = FTheme.Make( mergeFTab )
  addToView.AddTheme( mergeTheme )
  ? Bring the View to the front...
  addToView.GetWin.Activate
end
293
?Script Qual.Pick
?
?----------------------------
?--- Creation information ---
?----------------------------
?
?Name: pick several.ave
?Version: 1.0
?Date: 08/15/97
?Author: Christine Dartiguenave
?        Center for Research in Water Resources
?        The University of Texas at Austin
?        darti@crwr.utexas.edu
?
?---------------------------
?--- Purpose/Description ---
?---------------------------
?
?This program picks up the value in several grids corresponding to a point coverage and write
them to the selected
?fields of the attribute table of the coverage.
?
?----------------
?--- Get view ---
?----------------
theView = av.GetActiveDoc
?------------------
?--- Get themes ---
?------------------
if (theView.GetThemes.Count = 0) then
  msgbox.error("No themes found", "Pick")
  exit
end
ThmList=list.Make
for each thm in TheView.GetThemes
  if(thm.is(Gtheme))then
    ThmList.add(thm)
  end
end
Flowthm=Msgbox.multilistasstring(ThmList,"Choose the grid(s)",Script.The.GetName)
    if(Flowthm=nil)then
      exit
    else
      FlowthmName=Flowthm.GetName
    end
Thm1List=list.Make
for each thm in TheView.GetThemes
  if(thm.is(Ftheme))then
   if(thm.GetFtab.GetShapeClass.GetClassName="Point")then
   Thm1List.add(thm)
   end
  end
end
Ptthm=Msgbox.ChoiceAsString(Thm1List,"Choose a point coverage",Script.The.GetName)
    if(Ptthm=nil)then
      exit
     end
pttab = Ptthm.getftab
if (pttab = nil) then
    msgbox.error("Can?t open point theme",Script.The.GetName)
    exit
end
?create a field for each grid with the grid name if it does not exist yet.
?If it exists ask to overwrite or to give another name.
for each thm in flowthm
    thmname = thm.getname
    ptvalue = pttab.findfield(thmname)
      if (ptvalue = nil) then
         pttab.seteditable(true)
         ptvalue = field.make(thmname, #FIELD_DECIMAL, 16, 4)
         pttab.addfields({ptvalue})
         pttab.seteditable(false)
       else
         addfield = msgbox.yesno("The field"++thmname.asstring++" already exists. Do you
want to overwrite it?",Script.The.GetName, true)
          if (addfield=false) then
            newname = msgbox.input("Enter the new field name", "Field name" , thmname )
            pttab.seteditable(true)
            ptvalue = field.make(newname.asstring, #FIELD_DECIMAL, 16, 4)
            pttab.addfields({ptvalue})
            pttab.seteditable(false)
           end
        end
294
  grid1 = thm.getgrid
  ptshape = pttab.findfield("shape")
    if (ptshape = nil) then
      msgbox.error("Can?t find ?shape? field in point theme",Script.The.GetName)
    exit
    end
pttab.seteditable(true)
for each rec in pttab
  shapev = pttab.returnvalue(ptshape,rec)
  val = grid1.cellvalue(shapeV,Prj.MakeNull)
  pttab.setvalue(ptvalue,rec,val)
end
pttab.seteditable(false)
end
?
?final message to user
?
message = "Grid values picked"
msgbox.info(message,Script.The.GetName)
?-----------
?--- End ---
?-----------
?Script Qual.Wshd
?
?----------------------------
?--- Creation information ---
?----------------------------
?
?Name: Qual.Wshd
?Version: 1.0
?Date: 6/26/97
?Author: Christine Dartiguenave
?        Center for Research in Water Resources
?        The University of Texas at Austin
?        darti@crwr.utexas.edu
?
?---------------------------
?--- Purpose/Description ---
?---------------------------
?
?This program enable to delineate a watershed based on a point coverage.
?--------------------
?--- Get the View ---
?--------------------
?
theView=av.GetActiveDoc
?----------------------
?--- Get the themes ---
?----------------------
if (theView.GetThemes.Count = 0) then
   msgbox.error("No themes found", Script.The.GetName)
   exit
end
?Name the new grids
outFName = av.GetProject.MakeFileName("wshdgr", "")
aname1 = FileDialog.Put(outFName, "", "Watershed grid")
if (aname1 = Nil) then
  exit
end
outFName = av.GetProject.MakeFileName("wshdcv", "shp")
aname2 = FileDialog.Put(outFName, "*.shp", "Watershed coverage")
if (aname2 = Nil) then
  exit
end
ptList=list.Make
  for each thm in TheView.GetThemes
    if(thm.is(Ftheme))then
      if(thm.GetFtab.GetShapeClass.GetClassName="Point")then
   ptList.add(thm)
   end
  end
end
ptthm=Msgbox.ChoiceAsString(ptList,"Pick a point coverage",Script.The.GetName)
    if(ptthm=nil)then
      exit
    else
      ptthmName=ptthm.GetName
    end
295
gridList=list.Make
  for each thm in TheView.GetThemes
    if(thm.is(Gtheme))then
       gridList.add(thm)
     end
 end
fdrthm=Msgbox.ChoiceAsString(gridList,"Pick a flow direction grid.",Script.The.GetName)
    if(fdrthm=nil)then
      exit
    end
fdirgrid=fdrthm.getgrid
?-----------------------------------------------------
?--- Convert the point coverage to a grid coverage ---
?-----------------------------------------------------
theftab=ptthm.getftab
cellsize=fdirgrid.getcellsize
box=fdirgrid.getextent
aprj=theview.getprojection
fieldlist=theftab.getfields
afield = Msgbox.ChoiceAsString(fieldList,"Choose a grid-code field.",Script.The.GetName)
    if(afield=nil)then
      exit
    end
ptgrid  = grid.makefromftab(theftab,aprj,afield, {cellsize,box})
?--------------------------------
?--- Delineate the watersheds ---
?--------------------------------
wshdgrid=fdirgrid.Watershed (ptgrid)
wshdgrid.savedataset(aname1)
wshdgtheme = gtheme.make(wshdgrid)
theview.addtheme(wshdgtheme)
wshdgtheme.setlegendvisible(false)
?----------------------------
?--- Convert to shapefile ---
?----------------------------
anFTab = wshdgrid.AsPolygonFtab(aname2,true,prj.makenull)
fthm = FTheme.Make(anFTab)
theView.AddTheme(fthm)
fthm.setlegendvisible(false)
?-----------
?--- END ---
?-----------
? Script Qual.Zonalmean
?
?----------------------------
?--- Creation information ---
?----------------------------
?
?Name: Qual.Zonalmean
?Version: 1.0
?Date: 10/15/97
?Author: Christine Dartiguenave
?        Center for Research in Water Resources
?        The University of Texas at Austin
?        darti@crwr.utexas.edu
?
?---------------------------
?--- Purpose/Description ---
?---------------------------
?
?This program compute a zonalmean.
?--------------------
?--- Get the View ---
?--------------------
?
theView=av.GetActiveDoc
?
?------------------
?--- Get themes ---
?------------------
?
?Check if there are a theme in the view.
if (theView.GetThemes.Count = 0) then
  msgbox.error("No themes found", "BMP")
  exit
296
end
outFname = av.GetProject.MakeFileName("grid", "")
gridname = FileDialog.Put(outFName, "", Script.The.GetName)
if (gridname = Nil) then
  exit
end
thmList=list.Make
  for each thm in TheView.GetThemes
    if(thm.is(Gtheme))then
       thmList.add(thm)
    else
      if (thm.is(Ftheme)) then
        if (thm.GetFtab.GetShapeClass.GetClassName="Polygon")then
          thmlist.add(thm)
         end
      end
     end
 end
zoneList=list.Make
  for each thm in TheView.GetThemes
    if(thm.is(Ftheme))then
      if (thm.GetFtab.GetShapeClass.GetClassName="Polygon")then
        zonelist.add(thm)
       end
    end
  end
  gridList=list.Make
  for each thm in TheView.GetThemes
    if(thm.is(Gtheme))then
           gridlist.add(thm)
       end
     end
zonethm= Msgbox.ChoiceAsString(zoneList,"Choose a zone
coverage.",Script.The.GetName)
  if(zonethm=nil) then
    exit
   end
zonetab=zonethm.getftab
fieldlist=zonetab.getfields
fieldname=Msgbox.ChoiceAsString(fieldList,"Choose a field to identify the
zones.",Script.The.GetName)
zonefield=zonetab.findfield(fieldname.asstring)
valuethm=Msgbox.ChoiceAsString(thmList,"Choose a value theme",Script.The.GetName)
    if(valuethm=nil)then
      exit
    end
if (valuethm.is(Gtheme)) then
  valuegrid=valuethm.getgrid
else
  anftab=valuethm.getftab
  fieldlist1=anftab.getfields
  aprj=theview.getprojection
  fdrthm=Msgbox.ChoiceAsString(gridList,"Choose a flow direction grid (cellsize and
extent)",Script.The.GetName)
  afield=Msgbox.ChoiceAsString(fieldList1,"Choose a value field ",Script.The.GetName)
  fdirgrid=fdrthm.getgrid
  cellsize=fdirgrid.getcellsize
  box=fdirgrid.getextent
  valuegrid = Grid.MakeFromFTab(anFTab, aPrj, aField, {cellSize, box})
end
?------------------------
?--- Compute the mean ---
?------------------------
aPrj = theView.GetProjection
meanGrid =
valueGrid.ZonalStats(#GRID_STATYPE_MEAN,zonetab,aPrj,zoneField,FALSE)
meangrid.savedataset(gridname)
meanthm = GTheme.Make(meangrid)
? check for error during operation
if (meanGrid.HasError) then
  return NIL
end
297
theView.AddTheme(meanthm)
msgbox.info("New grid computed",Script.The.GetName)
?-----------
?--- END ---
?-----------
298
Glossary
ACV Annual Capture Volume
AERE Average Event Removal Efficiency
BMP Best Management Practices
BOD  Biological Oxygen Demand
COA City of Austin
COD Chemical Oxygen Demand
COMP City of Austin?s Composite Ordinance
CRWR Center for Research in Water Resources
Cu Copper
CLL City Limit Line
DEM Digital Elevation Model
DP Dissolved Phosphorus
EMC Event Mean Concentration
EPA Environmental Protection Agency
EII Environmental Integrity Index
ETJs Extra Territorial Jurisdictions
GIS Geographic Information System
NCDC National Climatic Data Center
NH
3
Ammonia
NO
3
Nitrate
Pb Lead
SOS City of Austin?s Save Our Spring Ordinance
TKN Total Kjeldahl Nitrogen
TN Total Nitrogen
TNRIS Texas Natural Resources Information System
TNRCC Texas Natural Resource Conservation Commission
TOC Total Organic Compounds
TP Total Phosphorus
TSS Total Suspended Solids
TSZ Traffic Serial Zones
USGS United States Geological Survey
Zn Zinc
299
Bibliography/References
Barrett, M., 1997. Water Quality and Quantity Inputs for the Urban Creeks Future Needs
Assessment, Draft Report to the City of Austin, CRWR, University of Texas at
Austin.
City of Austin Drainage Utility Department, Environmental Resources Management
Division, 1997. Environmental Integrity Index Water Quality Technical
Assessment Methodology, COA-ERM/WRE 1997-03
Chow, V.T., D.R. Maidment, and L. Mays. 1988. Applied Hydrology. McGraw Hill,
New York, New York.
Environmental Systems Research Institute, Inc., http://www.esri.com.
Horizons Technology, Inc., http://www.horizons.com.
Maidment, D.R., (ed.), 1993.  Handbook of Hydrology, McGraw-Hill, New York.
Migalewicz, P.J., and D.R. Maidment, 1996. Modeling Agrichemical Transport in
Midwest Rivers using Geographic Information Systems. Ph.D. Dissertation,
University of Texas at Austin, Department of Civil Engineering, Austin, Texas,
CRWR Online Report 96-6 (http://www.ce.utexas.edu/prof/maidment/pub.html).
National Climatic Data Center, http://www.ncdc.noaa.gov.
Olivera, F., D.R. Maidment, and R.J. Charbeneau, 1996. Spatially Distributed Modeling
of Storm Runoff and Non-Point Source Pollution Using Geographic Information
System, Ph.D. Dissertation, University of Texas at Austin, Department of Civil
Engineering, Austin, Texas, CRWR Online Report 96-4
(http://www.ce.utexas.edu/prof/maidment/pub.html).
Olivera, F., 1996. Spatial Hydrology of the Urubamba River System in Peru using GIS,
http://www.ce.utexas.edu/prof/olivera/peru/peru.htm
Saunders, W.K, and D.R. Maidment, 1996. A GIS Assesnent of Non-point Source
Pollution in the San Antonio-Nueces Coastal Basin. Masters Report, University
of Texas at Austin, Department of Civil Engineering, Austin, Texas , CRWR
Online Report 96-1 (http://www.ce.utexas.edu/prof/maidment/pub.html).
Texas Natural Resources Information System,  http://www.tnris.state.tx.us/ftparea.html.
USGS, Daily-Value Data for Texas, http://txwww.cr.usgs.gov/cgi-bin/txnwis.
300
Vita
Christine Dartiguenave was born in Schiltigheim, France on March 14,
1975, the daughter to Mich?le Andr?e Dartiguenave and Yves Louis Edouard
Dartiguenave. After completing her work in 1992 at the Lyc?e Bellevue,
Toulouse, France, she entered the Lyc?e Pierre de Fermat in Toulouse, France,
where she prepared for two years for the national engineering exams, option
Mathematics. In 1994, she entered the Ecole Centrale de Lille, Lille, France.
During her pursuit of a degree in General Engineering at the Ecole Centrale de
Lille, she held an engineer intern position for Thomson-CSF in Toulouse, France
in January 1995, and for Elf Aquitaine in Lacq, France, during the 1996 summer.
In August 1996, she entered The Graduate School at the University of Texas at
Austin. She graduated from the Ecole Centrale de Lille in October 1997, receiving
the degree of Ing?nieur ECLille.
Permanent address: 15 rue de la Fontaine des Cerdans
31520 Ramonville Saint Agne
France
This thesis was typed by the author.