CRWR Online Report 05-14 
 
 
GeoSpatial HSPF Model of the 
Sandies and Elm Watershed, Texas 
 
 
by 
Jessica Luttrell Watts, B.S., P.E. 
 
David R. Maidment, Ph.D. 
Lynn E. Katz, Ph.D. 
 
 
May 2006 
 
 
CENTER FOR RESEARCH IN WATER RESOURCES 
The University of Texas at Austin 
J.J. Pickle Research Campus  
Austin, Texas 78712 
 
 
This document is available on the World Wide Web at: 
http://www.crwr.utexas.edu/online.shtml
 ii
 
 
 
 
Acknowledgements 
 
To my husband, Alex, for his love and support, 
To my children, Gabriel and Holly, for their love and laughter, 
To my parents, Henry and Marjorie Luttrell, for their love and support, 
To Dr. David Maidment, who taught me, guided me, and helped me to see the 
vision beyond the work, 
To Dr. Lynn Katz, who shared her love of water chemistry and water quality 
modeling, 
To Nate Johnson, whose research laid the foundation for my own, 
To Carrie Gibson and Becky Teasley and all the students and faculty at CRWR 
and EWRE for their friendship and support, 
I give my heartfelt appreciation and thanks. 
 
 
 
May 2006 
 iii
Abstract 
GeoSpatial HSPF Model of the  
Sandies and Elm Watershed, Texas 
 
Jessica Luttrell Watts, M.S.E. 
The University of Texas at Austin, 2006 
 
Co-Supervisors:  David Maidment and Lynn Katz 
 
The Sandies and Elm Creeks were placed on EPA’s 303(d) list in 2000 due to 
depressed dissolved oxygen and elevated bacteria levels.  Given the rural, agricultural 
nature of the watershed, a Total Mass Daily Load (TMDL) study was initiated to 
determine the source or sources of the non-point source pollution.  A model needed to be 
developed that simulated the agricultural runoff from the watershed.  The simulation 
model, Hydrologic Simulation Program – FORTRAN (HSPF) was chosen.  A typical 
HSPF model was conceived, but during the course of the study circumstances forced the 
model to develop in an atypical way.  The classic source of precipitation forcing data, the 
National Climatic Data Center, lacked point precipitation stations with data during the 
calibration timeframe; therefore alternate data sources were reviewed and NEXRAD data 
was chosen as the alternate data source.  But, the use of NEXRAD data required that the 
model be distributed to a greater degree than a classic HSPF model.  This delineation 
pushed the HSPF code to the edge of its design and encouraged examination of the 
weaknesses of both HSPF and hydrologic modeling in general. 
 iv
Table of Contents 
List of Tables ................................................................................................................... viii 
List of Figures......................................................................................................................x 
List of Equations.............................................................................................................. xiii 
Chapter 1 Introduction........................................................................................................1 
1.1 Introduction........................................................................................................1 
1.2 Purpose and Scope .............................................................................................1 
1.3 Document Outline..............................................................................................2 
Chapter 2 Background........................................................................................................4 
2.1 Sandies and Elm Watershed...............................................................................4 
2.1.1 Streams...................................................................................................5 
2.1.1.1 Elm Creek ............................................................................5 
2.1.1.2 Sandies Creek.......................................................................5 
2.1.1.3 Flow Characteristics.............................................................6 
2.1.2 Climate...................................................................................................7 
2.1.3 Land Use / Land Cover..........................................................................8 
2.1.3.1 Ecoregions............................................................................9 
2.1.3.2 Livestock............................................................................11 
2.2 Water Quality Overview..................................................................................14 
2.2.1 TMDL Overview .................................................................................15 
2.3 Sandies and Elm Water Quality Background ..................................................15 
2.3.1 Concern Definitions.............................................................................16 
2.3.2 Impairments .........................................................................................16 
2.3.3 Point Sources .......................................................................................19 
Chapter 3 Hydrologic Simulation Program - FORTRAN................................................21 
3.1 Hydrologic Modeling Overview......................................................................21 
3.1.1 Stochastic or Deterministic..................................................................21 
3.1.2 Lumped or Distributed.........................................................................22 
 v
3.1.3 Steady or Unsteady ..............................................................................22 
3.1.4 Continuous or Event-Based .................................................................22 
3.1.5 HSPF Model Classification..................................................................23 
3.2 History of HSPF...............................................................................................25 
3.3 HSPF Overview ...............................................................................................27 
3.3.1 HSPF Perspective of the Hydrologic Cycle.........................................27 
3.3.2 HSPF Application Modules .................................................................29 
3.3.3 PERLND Module.................................................................................30 
3.3.4 IMPLND Module.................................................................................32 
3.3.5 RCHRES Module.................................................................................33 
3.4 Closing .............................................................................................................34 
Chapter 4 Motivation........................................................................................................36 
4.1 Precipitation Data Sources...............................................................................36 
4.1.1 NCDC ..................................................................................................36 
4.1.1.1 Daily...................................................................................37 
4.1.1.2 Hourly ................................................................................39 
4.1.2 NEXRAD.............................................................................................39 
4.1.3 DAYMET ............................................................................................42 
4.1.4 NARR ..................................................................................................43 
4.2 Precipitation Data Spatial Comparison............................................................44 
4.2.1 Initial Precipitation Data Comparison .................................................44 
4.2.2 Precipitation Spatial Evaluation Results..............................................49 
4.2.3 Precipitation Spatial Evaluation Summary ..........................................62 
4.3 Precipitation Study Results..............................................................................65 
Chapter 5 Model Development.........................................................................................66 
5.1 GIS to HSPF Overview....................................................................................66 
5.2 Data Collection ................................................................................................68 
5.2.1 Precipitation .........................................................................................68 
5.2.2 Evaporation..........................................................................................71 
5.2.3 Land Use / Land Cover........................................................................72 
5.2.4 Streams.................................................................................................73 
 vi
5.2.5 Topography..........................................................................................74 
5.2.6 Geology and Soils................................................................................75 
5.2.7 Stream Flow.........................................................................................77 
5.3 Model Construction .........................................................................................77 
5.3.1 Watershed Delineation.........................................................................79 
5.3.2 River Reaches ......................................................................................79 
5.3.3 Subbasins .............................................................................................80 
5.3.4 Land Use / Land Cover........................................................................82 
5.3.5 Cross-Section and Outflow..................................................................85 
5.3.6 Physical Parameter Definition .............................................................90 
5.3.7 Length of Overland Flow Plane (LSUR).............................................91 
5.3.8 Slope of Overland Flow Path (SLSUR)...............................................92 
5.3.9 Manning’s n for Overland Flow Plane (NSUR) ..................................92 
5.3.10 Lower Zone Evapotranspiration (LZETP)...........................................93 
5.3.11 Lower Zone Nominal Soil Moisture Storage (LZSN) .........................94 
5.3.12 Index to Mean Soil Infiltration Rate (INFILT)....................................94 
5.3.13 Rainfall Vegetation Interception (CEPSC)..........................................95 
5.3.14 Nominal Upper Zone Soil Moisture Storage (UZSN) .........................95 
Chapter 6 Model Calibration ............................................................................................96 
6.1 Parameter Estimation.......................................................................................96 
6.2 HSPF Standard Calibration..............................................................................98 
6.2.1 Annual Water Balance .........................................................................98 
6.2.2 Seasonal and Monthly Distribution .....................................................99 
6.2.3 Storm Event Calibration ....................................................................100 
6.2.4 Specific Calibration Rules and Procedures........................................101 
6.2.5 Calibration Targets.............................................................................101 
6.3 Sandies and Elm Calibration..........................................................................102 
6.3.1 Calibration Period ..............................................................................103 
Chapter 7 Conclusions and Recommendations ..............................................................110 
7.1 Spatial Precipitation Data Findings ...............................................................110 
7.2 HSPF..............................................................................................................111 
 vii
7.3 HSPF Future...................................................................................................112 
7.4 A Word of Caution.........................................................................................114 
Appendix A:  Convective Set Spatial Interpretation of Precipitation..............................116 
Appendix B:  Frontal Storm Set Spatial Interpretation of Precipitation..........................140 
Appendix C ......................................................................................................................168 
Appendix D......................................................................................................................172 
Appendix E:  Model Parameters......................................................................................178 
Abbreviations...................................................................................................................195 
References ........................................................................................................................198 
Vita  ........................................................................................................................203 
 viii
List of Tables 
Table 2.1: Livestock Counts for County Areas in Watershed and Watershed Total .... 13 
Table 2.2: Sandies and Elm Impairment/Concerns (GBRA & UGRA, 2005).............. 18 
Table 2.3: Sandies and Elm Point Source Discharges .................................................. 19 
Table 3.1: Modules and Associated Uses (Bicknell et al., 2001) ................................. 30 
Table 4.1: Selected Convective and Frontal Storms ..................................................... 49 
Table 4.2: NCDC Data for February 21, 2003 Storm................................................... 56 
Table 4.3: Spatial Analysis of Precipitation Methods over Sandies & Elm Watershed 57 
Table 4.4: NCDC Data for March 14, 2000 Storm....................................................... 59 
Table 4.5: Spatial Analysis of Precipitation Methods over Sandies & Elm Watershed 61 
Table 4.6: Convective Storm Set Spatial Analysis over the Sandies & Elm Watershed
..................................................................................................................... 63 
Table 4.7: Frontal Storm Set Spatial Analysis over the Sandies & Elm Watershed..... 64 
Table 5.1: Overview of ArcGIS, HSPF, and Timeseries Preprocessing Methodologies 
(Johnson, 2005)............................................................................................ 67 
Table 5.2: Hydrologic Soil Groups ............................................................................... 76 
Table 5.3: Land Use Breakdown................................................................................... 83 
Table 5.4: Section Side Slope ....................................................................................... 90 
Table 5.5: HSPF Physical Parameters........................................................................... 91 
Table 5.6: Drainage Density Statistics (kilometer/square kilometer) ........................... 92 
Table 5.7: Sandies & Elm NSUR Parameters............................................................... 93 
Table 5.8: LZETP Monthly Values per Land Use ........................................................ 93 
Table 5.9: SCS Hydrologic Soil Group Characteristics................................................ 94 
Table 5.10: Monthly Interception Rates (Inches) ........................................................... 95 
 ix
Table 6.1: HSPF PWATER Parameters (US EPA, 2000) ............................................ 97 
Table 6.2: Annual Water Balance Calibration Parameters ........................................... 99 
Table 6.3: Seasonal and Monthly Distribution Parameters......................................... 100 
Table 6.4: Seasonal and Monthly Distribution Parameters......................................... 100 
Table 6.5: HSPF Calibration Criteria (adapted from Donigian et al., 1984) .............. 102 
Table 6.6: HSPF Calibration Criteria Results - Full Calibration Period..................... 104 
Table 6.7: HSPF Calibration Criteria Results – Shortened Calibration Period .......... 105 
 x
List of Figures 
Figure 2.1: Sandies and Elm Watershed Study Area ....................................................... 4 
Figure 2.2: Sandies and Elm Creeks................................................................................. 6 
Figure 2.3: Annual Mean Flow (USGS: NWIS, 2005) .................................................... 7 
Figure 2.4: PRISM Average Annual Precipitation (inches)............................................. 8 
Figure 2.5: Sandies and Elm Land Use / Land Cover Breakdown................................... 9 
Figure 2.6: Sandies and Elm EcoRegions (US EPA, 2004)........................................... 10 
Figure 2.7: Counties with Significant Poultry Activity.................................................. 12 
Figure 2.8: Usage Impairments and Concerns for the Sandies and Elm Creeks............ 17 
Figure 2.9: Sandies and Elm Point Sources (US EPA, 2004) ........................................ 20 
Figure 3.2: Stanford Watershed Model (AquaTerra, 2005) ........................................... 25 
Figure 3.3: Hydrologic Cycle......................................................................................... 28 
Figure 3.4: PERLND Structure Chart (AquaTerra, 2005) ............................................. 31 
Figure 3.5: IMPLND Structure Chart (AquaTerra, 2005).............................................. 32 
Figure 3.6: RCHRES Structure Chart (AquaTerra, 2005) ............................................. 33 
Figure 4.1: Available NCDC Daily Precipitation Stations (NOAA: NCDC, 2006b) .... 38 
Figure 4.2: Available NCDC Daily Precipitation Stations for years 2000 thru 2004 .... 38 
Figure 4.3: Available NCDC Hourly Precipitation Stations (NOAA: NCDC, 2006b).. 39 
Figure 4.4: National Doppler RADAR Coverage (NOAA: NWS, 2006d) .................... 40 
Figure 4.5: National Doppler RADAR Sites (NOAA, NWS, 2006a)............................ 41 
Figure 4.6: National 18-Year Mean Monthly Total Precipitation for August (DAYMET, 
2006b) .......................................................................................................... 43 
Figure 4.7: NCDC Gauge Spline Interpolation, August 27, 2000.................................. 45 
 xi
Figure 4.8: Storm Color Scale (hundredth inch) ............................................................ 45 
Figure 4.9: NCDC Gauge IDW Interpolation, August 27, 2000.................................... 46 
Figure 4.10: NEXRAD Image, August 27, 2000 ............................................................. 47 
Figure 4.11: Storm Color Scale (hundredth inch) ............................................................ 50 
Figure 4.12: NEXRAD May 13, 2004.............................................................................. 51 
Figure 4.13: NCDC Gauge IDW Interpolation May 13, 2004......................................... 51 
Figure 4.14: NEXRAD November 17, 2003.................................................................... 52 
Figure 4.15: NCDC Gauge IDW Interpolation November 17, 2003 ............................... 52 
Figure 4.16: NEXRAD October 25, 2003........................................................................ 53 
Figure 4.17: NEXRAD February 21, 2003 ...................................................................... 54 
Figure 4.18: NCDC Gauge IDW Interpolation February 21, 2003.................................. 55 
Figure 4.19: NEXRAD 2/19/2003 thru 2/22/2003........................................................... 56 
Figure 4.20: NCDC Gauge IDW Interpolation 2/19/2003 thru 2/22/2003 ...................... 57 
Figure 4.21: NEXRAD March 14, 2000 .......................................................................... 58 
Figure 4.22: NCDC Gauge IDW Interpolation March 14, 2000...................................... 59 
Figure 4.23: NEXRAD 3/14/2000 thru 3/15/2000........................................................... 60 
Figure 4.24: NCDC Gauge IDW Interpolation 3/14/2000 thru 3/15/2000 ...................... 60 
Figure 4.25: NEXRAD June 30, 2002.............................................................................. 61 
Figure 4.26: NCDC Gauge IDW Interpolation June 30, 2002......................................... 62 
Figure 5.1: NEXRAD Cell Coverage of the Sandies & Elm Watershed ....................... 69 
Figure 5.2: West Gulf River Forecast Center Area of Interest (NOAA: NWS, 2005b). 70 
Figure 5.3: Schematic Overview of ArcGIS Timeseries Preprocessing Methodology 
(Johnson, 2005)............................................................................................ 71 
Figure 5.4: NCDC Evaporation Stations........................................................................ 72 
 xii
Figure 5.5: Land Use / Land Cover Data (USGS: Seamless, 2006a)............................. 73 
Figure 5.6: NHD High-Resolution Flowlines for the Sandies and Elm Watershed....... 74 
Figure 5.7: 1/3 Arc Second National Elevation Data (USGS: Seamless, 2005) ............ 75 
Figure 5.8: STATSGO Hydrologic Soil Groups ............................................................ 76 
Figure 5.9: Sandies Creek USGS Gage Flow 1999 thru 2004 ....................................... 77 
Figure 5.10: Sandies and Elm Drainage Lines ................................................................. 80 
Figure 5.11: Sandies and Elm Watershed Delineation..................................................... 81 
Figure 5.12: Reclassification of Land Uses for HSPF Model.......................................... 84 
Figure 5.13: Land Use / Subbasin Intersection Illustration.............................................. 84 
Figure 5.14: HSPF Land Uses and Subbasins.................................................................. 85 
Figure 5.15: USGS Gaging Station 08175000 Historical Width versus Flow................. 86 
Figure 5.16: USGS Gaging Station 08175000 Historical Width versus Low Flow......... 87 
Figure 5.17: USGS Gaging Station 08175000 Historical Depth versus Flow ................. 88 
Figure 5.18: Historical Cross-Section at USGS Gauge 08175000................................... 88 
Figure 6.1: Daily Flow ................................................................................................. 106 
Figure 6.2: Daily Flow Calibration Period................................................................... 107 
Figure 6.3: Monthly Cumulative Flow - Calibration Period ........................................ 108 
Figure 6.4: Daily Flow Duration Curve - Calibration Period....................................... 109 
 xiii
List of Equations 
Equation 2.1:  TMDL Components .................................................................................. 15 
Equation 5.1:  Main Channel Flow................................................................................... 89 
Equation 5.2:  Lower Floodplain Flow............................................................................. 89 
Equation 5.3:  Upper Floodplain Flow ............................................................................. 89 
Equation 5.4:  Bottom Width............................................................................................ 89 
Equation 5.5:  Manning’s Equation .................................................................................. 89 
Equation 5.6:  Top Width.................................................................................................. 90 
Equation 5.7:  Overland Flow (LSUR)............................................................................. 91 
Equation 6.1:  Annual Water Balance............................................................................... 98 
 1
Chapter 1 Introduction 
1.1 INTRODUCTION 
The Sandies and Elm Creeks were placed on EPA’s 303(d) list in 2000 due to 
depressed dissolved oxygen and elevated bacteria levels.  Given the rural, agricultural 
nature of the watershed, a Total Mass Daily Load (TMDL) study was initiated to 
determine the source or sources of the non-point source pollution.  A model needed to be 
developed that simulated the agricultural runoff from the watershed.  The computer 
model, Hydrologic Simulation Program – FORTRAN (HSPF) was chosen for two 
reasons.  First, it is recommended by the EPA for use in non-point source .pollution 
watershed modeling and second, the model has the ability to simulate continuously on a 
given time step. 
A typical HSPF model was conceived, but during the course of the study 
circumstances encouraged the model to develop in an atypical way.  The classic source of 
precipitation forcing data, the National Climatic Data Center, lacked point precipitation 
stations with data during the calibration timeframe; therefore alternate data sources were 
reviewed and NEXRAD data was chosen as the alternate data source.  But, the use of 
NEXRAD data required that the model be distributed to a greater degree than a classic 
HSPF model.  This delineation pushed the HSPF code to the edge of its design and 
supported examination of the weaknesses of both HSPF and hydrologic modeling in 
general. 
1.2 PURPOSE AND SCOPE 
The purpose of this study is to examine various aspects of the application of the 
HSPF model to the Sandies and Elm watershed, Texas.  Initially prompted by the need to 
develop a continuous hydrologic simulation model for a TMDL study in this watershed, 
 2
the scope was later broadened to include an examination of the effect of various sources 
of rainfall input on the HSPF simulated flow. 
A hydrologic and water quality model for the Sandies and Elm watershed was 
developed using the Hydrologic Simulation Program – FORTRAN (HSPF) simulation 
model.  The model incorporates basin specific information, in a timeseries format, which 
includes measured stream flow, as well as precipitation and evaporation forcing data.  
Additionally, the model also includes characteristics of the topography, soils, land use / 
land cover, and vegetation.  The model was calibrated with measured stream flow data 
and where available and to the degree possible, the model parameters were physically 
based. 
1.3 DOCUMENT OUTLINE 
This thesis is divided into seven chapters.  The first is the introduction which 
gives an overview of the thesis as well as the objective and scope of the study 
undertaken.  Chapter two presents an overview of the Sandies and Elm watershed as well 
as a brief explanation of the Total Mass Daily Load (TMDL) study process and a water 
quality history of the watershed.  Chapter three provides an overview of hydrologic 
modeling in general and HSPF specifically.  It describes the model structure as well as 
the history of the model’s development.  A discussion of different aspects in the model 
development is included in Chapter four through six.  Chapter four describes the 
motivation behind the atypical development of the HSPF model and includes a discussion 
of differences between NEXRAD and NCDC gage interpolation methods.  It lays out an 
explanation of the different precipitation sources and compares select storms for 
evaluation of NEXRAD and NCDC data.  Chapter five describes the process and data 
used in the HSPF model development.  It begins with a very brief overview of the 
ArcGIS to HSPF preprocessing methodology used in initially creating the HSPF model, 
 3
and then a discussion of data collection methods is presented.  Definitions of those HSPF 
features that could be defined through known information of the physical watershed are 
also provided.  Chapter six continues with the model development, but concentrates on 
the calibration and parameterization of watershed features that cannot be defined through 
known physical characteristics.  Chapter six covers both the standard HSPF calibration 
methods as well as those specific to this study.  The chapter concludes with the results of 
the model.  Chapter seven contains the conclusions of the study and somewhat more 
importantly the recommendations for future development in water quality modeling.  It 
describes a vision for the future of hydrological water quality modeling.
 4
Chapter 2 Background 
2.1 SANDIES AND ELM WATERSHED 
The Sandies and Elm watershed is part of the Guadalupe River Basin in South 
Central Texas.  The watershed is located 34 miles East-Southeast of San Antonio, and is 
situated between the Medina and Guadalupe Rivers.  The watershed covers an area of 
712 square miles and extends into portions of five counties: DeWitt, Gonzales, 
Guadalupe, Karnes, and Wilson.  Figure 2.1 identifies the geographic location of the 
watershed study area.  The watershed terrain varies from level to rolling land, and 
elevation ranges from 130 to 745 feet.  There is only one major town in the watershed, 
Nixon, which has a population of 2,186 people.  (US Census Bureau, 2000) 
Figure 2.1: Sandies and Elm Watershed Study Area 
Sandies Creek
Elm Creek
 5
Seventy-five (75) types of soils overlying 19 different geologic formations have 
been classified in Gonzales County, in which most of the Sandies and Elm watershed is 
contained.  This area has the most diversified soil variety of any county in the state.  Dark 
Red sandstone is abundant in the northeast part of the watershed.  Sandy loam soil is 
plentiful in the northwest portion of the watershed.  The soils contained in Wilson and 
Karnes Counties have light to dark, loamy surfaces over reddish, clayey subsoils with 
limestone within forty inches of the surface, and gray to black, cracking.  The Salt Creek 
Flats can be found in the southern portion of Gonzales County.  The Flats furnished the 
early settlers with enough salt to satisfy their needs, but salt was never produced 
commercially there.  (Handbook of Texas Online, 2006a; 2006b; 2006c) 
2.1.1 Streams 
2.1.1.1 Elm Creek 
Elm Creek (Segment 1803A) originates west of Nixon in the eastern part of 
Wilson County.  The stream flows eastward for approximately 24 miles.  It converges 
with Sandies Creek just west of the Sandies crossing with FM 1116.  (See Figure 2.2)  
The stream traverses flat to rolling terrain of clay and sandy loam.  The riparian 
vegetation consists of water-tolerant hardwoods and grasses.  
2.1.1.2 Sandies Creek 
Sandies Creek (Segment 1803B), formerly known as Castleman Creek, originates 
in southwestern Guadalupe County.  The stream flows southeastward for approximately 
65 miles until it joins with the Guadalupe River northwest of Cuero in DeWitt County.   
(See Figure 2.2)  The creek traverses flat to rolling terrain with a surface of sand that 
gives the creek its name.  The riparian vegetation consists of hardwoods, pines, mesquite, 
and a variety of grasses. 
 6
Figure 2.2: Sandies and Elm Creeks 
2.1.1.3 Flow Characteristics 
The drainage area associated with the USGS gauging station on Sandies Creek at 
Westhoff, Texas is 549 square miles and the annual average discharge is 145 CFS.  But, 
as can be seen from Figure 2.3, the annual mean flow varies significantly from year to 
year.  The annual average discharge ranges from 5.81 CFS in 1988 to 545 CFS in 1992. 
 7
Figure 2.3: Annual Mean Flow (USGS: NWIS, 2005) 
2.1.2 Climate 
The climate in which the Sandies and Elm watershed is located is subtropical/sub-
humid, with mild winters and hot summers.  Temperatures in January range from an 
average low of 40° to an average high of 65° F and in July range from an average low of 
74° to an average high of 96° F.  The average annual precipitation across the watershed, 
as shown in Figure 2.4 below, ranges from 31 inches along the southwestern edge to 35 
inches in most of the eastern portion of the watershed.  There is no significant snowfall.  
The growing season averages 280 days per year, with the last freeze in February and the 
first freeze in early December.  (Handbook of Texas Online, 2006a) 
Annual Mean Flow
1
10
100
1000
1960 1965 1970 1975 1980 1985 1990 1995 2000
Year
Flo
w (CFS
)
 8
Figure 2.4: PRISM Average Annual Precipitation (inches) 
2.1.3 Land Use / Land Cover 
The watershed lies along the border of the Upper Coastal and Gulf Coast Plain in 
Southeast Texas.  Vegetation consists primarily of grasslands, mesquite, blackjack, post 
oak, live oak, pecan, and some brush, thorny shrubs, and cacti in drier areas of the 
watershed, while water-tolerant hardwoods and conifers flourish near creeks.  The natural 
vegetation of the watershed is examined more closely in the next section on Ecoregions. 
According to USGS: Seamless (2006a) 1992 Land Use / Land Cover data, ninety-
five percent of the land cover in the watershed is contained within four land use / land 
cover types:  pasture, grassland, shrubland, and forest as shown in Figure 2.5.  Although 
 9
the majority of the watershed is agricultural, only five percent of the land in the county is 
considered farmland.  The crops include peanuts, pecans, oats, wheat, sorghum, corn, 
vegetables, watermelons, and peaches.  The largest industry in the watershed is livestock 
production; this topic is more closely examined in section 2.1.3.2 below. 
Sandies and Elm Land Use / Land Cover
Pasture 
25%
Deciduous
Forest
20%
Shrubland
21%
Grassland
24%
Evergreen Forest 5.4%
Row Crops 3.5%
Open Water
Small Grains
Commercial/Industrial
Bare Rock/Sand/Clay
Herbaceous Wetland
Woody Wetlands
Quarries/Strip Mines
Light Residential
Heavy Residential
Recreational Grasses
Mixed Forest
1.1%
 
Figure 2.5: Sandies and Elm Land Use / Land Cover Breakdown 
2.1.3.1 Ecoregions 
As shown in Figure 2.6, the watershed lies within the following two Ecoregions:  
East Central Texas Plains and Texas Blackland Prairies. 
 10
Figure 2.6: Sandies and Elm Ecoregions (US EPA, 2004) 
The Texas Blackland Prairie Ecoregion is part of a tallgrass prairie continuum that 
stretches from Manitoba to the Texas Coast.  The lower portion of the Sandies and Elm 
watershed is within the Southern Blackland Prairie, a separated subset of the Texas 
Blackland Prairies.  (Griffith et al., 2004)  The Blackland Prairie has a large degree of 
plant community diversity.  This diversity is attributable to the ecoregion’s variety of 
soil.  These different soils have a variety of textures and a range of pH values.  (Diamond 
et al., 1987; Diamond and Smeins 1985)  The natural vegetation of the region was once 
dominated by tallgrass prairie on uplands with deciduous bottomland forest along the 
creeks.  (Diamond and Smeins 1993; World Wildlife, 2006b)  The dominant grasses 
 11
include:  little bluestem, big bluestem, yellow indiangrass, and switchgrass.  (Griffith et 
al., 2004) 
The Southern Post Oak Savanna is a subset of the East Central Texas Plains 
Ecoregion.  This is sometimes referred to as the East Central Texas Forests (ECTF) and is 
located entirely within the state of Texas.  It comprises one of the smallest ecoregions 
within the Temperate Broadleaf and Mixed forests biome.  (World Wildlife, 2006a)  The 
natural vegetation is a post oak savanna, currently the land cover is a mix of post oak 
woods with improved pasture and rangeland.  Mesquite has been established as an 
invasive species in the southern portion of this area.  A thick under story of yaupon and 
eastern red cedar are also prominent in some parts.  (Griffith et al., 2004)  This ecoregion 
is distinguished from the adjacent prairie units and coastal plain grasslands by a higher 
degree of tree density.  (World Wildlife, 2006a) 
2.1.3.2 Livestock 
Livestock production accounts for a majority of the agricultural industry in the 
watershed.  Livestock includes beef cattle, dairy cattle, poultry, and hogs.   
According to the Texas Commission on Environmental Quality (TCEQ), poultry 
production, which is a possible source of non-point source pollution, is a significant 
industry in two of the five counties of the Sandies and Elm watershed.  The area of 
significant poultry production is 572.8 square miles, which is 80% of the watershed.  (See 
Figure 2.7)  Gonzales County, which makes up 58.2% of the watershed, is the number 
three producer of broilers, the number one producer of layers, and the number four 
producer of turkeys in the state of Texas.  (USDA: NASS, 2005)  Yet, according to a 
Clean River Program report, “Poultry Operations Study Guadalupe River Basin,” 
(GBRA-PBS&J, 1998) there was no detectable difference between this watershed and 
other nearby streams without poultry operations. 
 12
Table 2.1 shows the county breakdown of total livestock in the watershed.  The 
livestock listed per county are the top five types of livestock according to the NASS 2002 
Agricultural Census.  The livestock type, Quail, was removed from Gonzales and Wilson 
Counties’ lists because numbers were unknown.  (USDA:  NASS, 2005) 
Overall, the largest livestock population in the watershed is chickens, with 
approximately five million broilers and two million layers.  Coming in a distant third and 
fourth are cattle with approximately 130,000 head and turkeys with 107,000. 
 
Figure 2.7: Counties with Significant Poultry Activity 
 13
Table 2.1: Livestock Counts for County Areas in Watershed and Watershed Total 
DeWitt 
  1999 2000 2001 2002 2003 2004 
Cattle 21,090 20,424 20,646 19,536 25,974 25,086
Layers 15,009 14,303 14,590 17,918 17,505 17,692
Hogs 639 559 440 500 799 819
Horses 260 260 260 260 260 260
Goats 163 163 163 163 163 163
Gonzales 
  1999 2000 2001 2002 2003 2004 
Broilers 5,069,367 5,184,807 5,189,484 5,397,112 5,468,084 5,723,365
Layers 1,946,647 1,855,148 1,892,350 2,323,996 2,270,382 2,294,727
Turkeys 107,378 107,378 107,378 107,378 107,378 107,378
Cattle 88,464 94,284 92,538 89,628 94,284 97,776
Guadalupe 
  1999 2000 2001 2002 2003 2004 
Broilers 4,311 4,409 4,413 4,590 4,650 4,867
Layers 3,627 3,456 3,525 4,330 4,230 4,275
Cattle 2,548 2,499 2,450 2,450 2,940 2,744
Goats 172 250 348 245 279 260
Sheep 180 180 180 180 180 180
Karnes 
  1999 2000 2001 2002 2003 2004 
Cattle 4,968 4,680 4,680 4,608 5,400 5,328
Layers 3,587 3,418 3,487 4,282 4,183 4,228
Goats 115 108 144 122 166 151
Horses 70 70 70 70 70 70
Sheep 24 24 24 24 24 24
Wilson 
  1999 2000 2001 2002 2003 2004 
Cattle 6,450 6,900 6,675 6,225 7,275 7,050
Goats 105 105 128 113 165 150
Horses 156 156 156 156 156 156
Layers 107 102 104 127 125 126
Sandies and Elm Watershed 
  1999 2000 2001 2002 2003 2004 
Broiler 5,073,678 5,189,216 5,193,897 5,401,702 5,472,734 5,728,233
Layer 1,968,976 1,876,427 1,914,056 2,350,653 2,296,424 2,321,048
Cattle 123,520 128,787 126,989 122,447 135,873 137,984
Turkeys 107,378 107,378 107,378 107,378 107,378 107,378
Hogs 1,412 1,235 970 1,103 1,764 1,809
Goats 392 463 619 643 610 1,318
Horses 486 486 486 486 486 486
Sheep 88 74 64 49 880 1,117
 14
2.2 WATER QUALITY OVERVIEW 
Under Section 305(b) of the Clean Water Act (CWA) each state is required to 
assess the water quality in the water bodies within their borders on a periodic basis.  This 
assessment is called the Water Quality Inventory.  The Texas Clean Rivers Program 
(CRP), which is managed by the TCEQ, was created to oversee and improve the quality 
of surface water resources within the different river basins of Texas.  The Guadalupe-
Blanco River Authority (GBRA) and the Upper Guadalupe River Authority (UGRA) 
work in conjunction with the TCEQ to administer the CRP for the Guadalupe River 
Basin, in which the Sandies and Elm watershed is located, and Lavaca-Guadalupe 
Coastal Basin.  The two river authorities carry out the water quality management efforts 
in these basins under contract with the TCEQ. 
Each major river and lake within the state is classified by their designated uses by 
the state’s water quality authority, in this case, the TCEQ.  Each designated usage has a 
range of water quality criteria associated with it.  The Water Quality Inventory 
assessment is based on a comparison between monitored field data and the range of 
criteria and screening levels associated with the designated uses.  Streams that have an 
impairment for one or more constituents are placed on the TCEQ’s CWA Section 303(d) 
list.  Once a stream is placed on the list, a sequence of actions may be taken by the 
TCEQ, including, but not limited to:  
1. Denial of increases in wastewater permit effluent limits 
2. Total Maximum Daily Load (TMDL) study to allocate pollutant loads 
3. Instituting a strategy for reducing loads from all sources. 
The Sandies and Elm watershed is currently the subject of a TCEQ TMDL study 
due to the high amounts of bacteria and low dissolved oxygen content. 
 15
2.2.1 TMDL Overview 
A TMDL is a tool for implementing state water quality standards.  It is based on the 
relationship between sources of pollutants and in-stream water quality conditions.  The 
TMDL establishes the allowable loadings for specific pollutants that a waterbody can 
receive without exceeding water quality standards, thereby providing the basis for states 
to establish water quality-based pollution controls.  The TMDL can be generally 
described by the following equation: 
Equation 2.1:  TMDL Components 
TMDL = LC = WLA + LA + MOS   
where: LC = loading capacity, 
 WLA = wasteload allocation, 
 LA = load allocation, and 
 MOS = margin of safety 
The loading capacity is the largest pollutant loading a waterbody can receive 
without exceeding water quality standards for the designated usage.  The wasteload 
allocation is the portion of the TMDL allocated for existing and future point sources.  The 
load allocation is the portion of the TMDL allocated to existing and future non-point 
sources and natural background levels.  The margin of safety accounts for uncertainty in 
the relationship between pollutant loads and receiving water quality. The margin of safety 
can be provided implicitly through analytical assumptions or explicitly by reserving a 
portion of loading capacity. (US EPA, 2001) 
2.3 SANDIES AND ELM WATER QUALITY BACKGROUND 
The Sandies and Elm Creeks have four designated uses.  They are: 
1. Aquatic Life 
a. Subcategory – High 
 16
b. Has NO known Federally Endangered or Threatened Aquatic Species 
2. Contact Recreation 
3. General 
4. Fish Consumption 
The “High” aquatic life subcategory designation represents a highly diverse habitat, with 
regionally expected species and some sensitive species present. 
2.3.1 Concern Definitions 
The term impairment is assigned by TCEQ to a water body when specific water 
quality constituents reach threshold concentrations, as specified in the Texas Surface 
Water Quality Standards, a number of times over a five years period. 
Some water bodies are identified with the designation, “concerns for use 
attainment.”  This designation is used for indicators that are directly linked to the support 
of designated uses, such as dissolved oxygen for aquatic life use. 
There are two classifications under Use Concerns, Use Concerns and Use 
Concerns – Limited Data.  Use Concerns are identified for indicators that support the 
designated use as determined by sampling greater than ten, but with few reported 
exceedances of the water quality criteria.  Use Concerns – Limited Data is the same as 
Use Concern, except it is used when there are fewer than ten samples taken. 
Secondary Concerns are identified for indicators such as nutrients that are not 
directly linked to the support of a designated use with quantitative criterion. 
2.3.2 Impairments 
Sandies Creek is impaired for aquatic life use due to depressed dissolved oxygen 
and contact recreation uses due to bacteria.  It has use concerns for aquatic life use due to 
depressed dissolved oxygen and concerns for nutrient enrichment due to ammonia levels.  
Elm Creek is listed as impaired for aquatic life use due to depressed dissolved oxygen 
 17
and contact recreation use due to bacteria.  Figure 2.8 displays the segments and Table 
2.2 lists each of the water segments with the designated use, concern classification, and 
parameter. 
 
Figure 2.8: Usage Impairments and Concerns for the Sandies and Elm Creeks 
Both the Sandies and Elm are small creeks and do not have water quality criteria 
developed for their unique hydrologic conditions.  They are evaluated using the standards 
pertaining to the nearest downstream designated segment, in this case the Guadalupe 
River.  But, the Guadalupe River has significantly different characteristics and dynamics 
than the Sandies and Elm Creeks. 
Elm Creek 
Impaired: 
 Aquatic Life Use / DO 
 Contact Recreation Use / Bacteria 
Upper Sandies Creek
Impaired: 
 Contact Recreation Use / Bacteria 
Use Concern: 
 Aquatic Life Use / DO 
Concern: 
 Nutrient Enrichment / Ammonia 
Lower Sandies Creek 
Impaired: 
 Aquatic Life Use / DO 
Use Concern: 
 Contact Recreation Use / Bacteria 
Concern: 
 Nutrient Enrichment / Ammonia 
 18
Table 2.2: Sandies and Elm Impairment/Concerns (GBRA & UGRA, 2005) 
Water 
Body ID 
Water 
Body Name 
Location 
Use/Water 
Quality Concern 
Impairment 
or Concern 
Parameter 
1803A Elm Creek Entire Water Body Aquatic Life Use Impaired Depressed DO 
1803A Elm Creek Entire Water Body 
Contact 
Recreation Use 
Impaired Bacteria 
1803A Elm Creek Entire Water Body 
Narrative Criteria 
Concern 
Concern Depressed DO 
1803B 
Sandies 
Creek 
From the confluence 
with Elm Creek to the 
upper end of the water 
body 
Aquatic Life Use Impaired Depressed DO 
1803B 
Sandies 
Creek 
From the confluence 
with Elm Creek to the 
upper end of the water 
body 
Contact 
Recreation Use 
Impaired Bacteria 
1803B 
Sandies 
Creek 
From the confluence 
with Elm Creek to the 
upper end of the water 
body 
Aquatic Life Use Use Concern Depressed DO 
1803B 
Sandies 
Creek 
From the confluence 
with Elm Creek to the 
upper end of the water 
body 
Nutrient 
Enrichment 
Concern 
Concern Ammonia 
1803B 
Sandies 
Creek 
From the confluence 
with Elm Creek to the 
upper end of the water 
body 
Contact 
Recreation Use 
Impaired Bacteria 
1803B 
Sandies 
Creek 
From the confluence 
with the Guadalupe 
River to the confluence 
with Elm Creek 
Contact 
Recreation Use 
Impaired Bacteria 
1803B 
Sandies 
Creek 
From the confluence 
with the Guadalupe 
River to the confluence 
with Elm Creek 
Contact 
Recreation Use 
Use Concern Bacteria 
1803B 
Sandies 
Creek 
From the confluence 
with the Guadalupe 
River to the confluence 
with Elm Creek 
Aquatic Life Use Use Concern Depressed DO 
1803B 
Sandies 
Creek 
From the confluence 
with the Guadalupe 
River to the confluence 
with Elm Creek 
Nutrient 
Enrichment 
Concern 
Concern Ammonia 
A Texas Clean Rivers Program study was undertaken by the Guadalupe Blanco 
River Authority in coordination with the engineering company PBS&J, to evaluate water 
quality non compliance of small streams.  The report, “Unique Challenges Posed by 
 19
Small Streams in Determining DO and Bacteria Water Quality Criteria Compliance” 
(PBS&J, 2001), explained that the smaller the stream, the more non-attainment was 
observed.  This is not unexpected since the criteria for the streams in Texas were 
developed for larger rivers, not for lower flow creeks a few inches deep.  Several physical 
conditions exist in smaller streams that exacerbate an already problematic situation.  The 
shallow water, which has less dissolved oxygen content than larger streams, also allows 
for less dilution when it is inundated with high bacteria runoff from a storm event.  The 
percentage of shaded area is greater in smaller creeks than large rivers.  This creates a 
higher temperature differential along the stream.  The report concludes that an effort is 
needed to account for stream size and conditions and develop criteria appropriate to the 
higher natural variation and physical conditions of smaller streams. 
2.3.3 Point Sources 
According to the US EPA BASINS data for HUC 12100202, there are four 
permitted discharges into the Sandies and Elm Creeks, two domestic waste sources and 
two industrial waste sources.  (US EPA, 2004)  Figure 2.9 shows the locations for 
sources.  The facility name and permitted flow are listed below in Table 2.3. 
Table 2.3:  Sandies and Elm Point Source Discharges 
Map 
Label 
Permit 
Number 
Facility Name 
Permitted 
Flow (MGD) 
Remark 
1 02013-000 Holmes Foods Nixon Proc. Plant  
TX Land 
App. Permit 
2 10234-001 City of Nixon WWTP 0.45  
3 10574-002 Smiley WWTP 0.042  
4 14458-001 Schertz Seguin Local Gov. WTP 0.75  
 20
 
Figure 2.9: Sandies and Elm Point Sources (US EPA, 2004) 
To assess the magnitude of both point and non-point sources of pollution on the 
streams in the Sandies and Elm watershed a TMDL study was initiated.  For this study a 
watershed model that could accurately model the runoff from agricultural practices was 
needed.  Hydrological Simulation Program – FORTRAN (HSPF) was chosen for this 
purpose.  The next chapter discusses hydrologic modeling in general, and the history and 
structure of HSPF specifically.
 21
Chapter 3 Hydrologic Simulation Program - FORTRAN 
3.1 HYDROLOGIC MODELING OVERVIEW 
There are two main purposes of hydrologic modeling.  The first is to characterize 
current situations or predict conditions for which observed data does not exist.  The 
second purpose is to lend insight into understanding the processes that are important in a 
system.  Hydrologic engineers use their knowledge of known relationships between 
rainfall, runoff, infiltration, and evapotranspiration for river flow forecasting, flood 
insurance map creation, water availability studies, and reservoir/river management.  
Modeling for these uses allows interested parties to analyze the factors that affect the 
system response and make informed decisions in planning for future conditions. 
Hydrologic models can be categorized in numerous ways.  The important 
questions that must be addressed include: 
1. Will uncertainty or randomness be accounted for in the model and if so, how? 
− Stochastic or Deterministic 
2. Will spatial variation be included, and if so, to what extent? 
− Lumped or Distributed 
3. Will time variation be allowed, and if so, what type? 
− Steady or Unsteady 
The terms associated with mathematical model classification that answer these 
questions have very specific meanings which will be discussed below and are outlined in 
Figure 3.1, a model classification flow chart. 
3.1.1 Stochastic or Deterministic 
Most processes that occur in nature are not completely understood and 
mathematical depictions of these processes, therefore, contain levels of uncertainty.  
 22
Stochastic models explicitly account for uncertainty in model parameters.  Deterministic 
models, on the other hand, characterize processes with specific values.  Uncertainty is not 
considered in the processes they characterize, therefore the same set of input values will 
always give the same set of output values.  HSPF is a deterministic model. 
3.1.2 Lumped or Distributed 
A further classification within deterministic models involves simplifications 
concerning spatial variability (Chow et al., 1988).  A lumped parameter model does not 
clearly account for spatial associations between model parameters, inputs, or outputs.  
Lumped models typically have some degree of spatial resolution, but because they are 
most often spatial averages, the complexity of a model is reduced significantly. 
Distributed parameter models explicitly account for spatial relationships among model 
variables and parameters. 
Lumped and distributed configurations for HSPF models should not be confused 
with the traditional definition of lumped and distributed models. No matter what the 
configuration, HSPF is essentially a lumped parameter model.  (HydroComp, 2006b)   
3.1.3 Steady or Unsteady 
Another classification subset in mathematical modeling entails the time 
dependence of the processes characterized.  Many deterministic hydrologic models make 
the assumption that flow is constant through time, which is defined as steady flow. 
Unsteady flow models allow for change in flow through the duration of the model run.  
This variability can complicate the hydrologic calculations considerably.  (Chow et al., 
1988)  HSPF has the ability to be either a steady or an unsteady flow model. 
3.1.4 Continuous or Event-Based 
An additional distinction in the time series classification of a hydrologic model is 
that of continuous vs. event based modeling.  In an event based model the model 
 23
simulates the hydrologic response for a single rainfall event.  An event based hydrologic 
simulation requires that the initial hydrologic conditions of the landscape be known.  But 
it only requires forcing data for the duration of the event to be modeled.  Continuous 
hydrologic models are required to keep track of the changes in the hydrologic conditions 
of the landscape that affect rainfall-runoff response between storm events.  An example 
of such a condition is soil moisture, which is an important component in infiltration and 
runoff processes.  Initial conditions are also required for a continuous model; however, 
the results from a continuous model become less dependent upon these initial conditions 
over longer simulation periods.  (HydroComp, 2006b) 
3.1.5 HSPF Model Classification 
Hydrologic Simulation Program – FORTRAN (HSPF) is a deterministic, lumped-
parameter, physically based, continuous model for simulating the water quality and 
quantity processes that occur in watersheds and in a river network.  
In reality, because environmental processes are occurring continuously in space 
and time, they are tremendously complicated to simulate precisely.  If environmental 
processes were completely understood, a mathematical model could be developed that is 
physically base, continuous, deterministic, and distributed.  The model would be able to 
forecast precisely the reaction at every point in a watershed with input data such as 
rainfall, evaporation, and pollutant deposition. 
 
 24 
 
Hydrologic Model 
Deterministi
c 
Distribute
d
 
Stochastic 
Space-Independent 
Space-Dependent 
Lumpe
d 
Time-
Correla
ted 
Steady 
Flow 
Unsteady 
Flow 
Time-
Independent
 
Time- 
Correla
ted 
Time-
Independent
 
Unsteady 
Flow 
Steady 
Flow 
Event Based 
Conti
nuou
s
 
Figure 3.1: 
Hydrologic Model Flow
 Ch
art [Adapted from Figure 1.4.1 (Chow 
et a
l
., 1988)] 
 25 
Unfortunately, at this time the governing processes of the natural environment are 
not completely understood.  Therefore, HSPF and every other hydrologic and water 
quality model rely on varying levels of spatial, temporal, and process averaging to predict 
the response in a watershed.  These mathematical models were developed to simulate 
processes as accurately as possible considering the limitations of the available data as 
well as an imperfect understanding of the underlying processes.  (Chow et al., 1988) 
3.2 HISTORY OF HSPF 
HSPF is based on the Stanford Watershed Model developed by Crawford and 
Lindsley in 1966.  A flowchart of the Stanford Watershed Model is presented in Figure 
3.2.   
 
Figure 3.2: Stanford Watershed Model (AquaTerra, 2005) 
Direct
Infiltration 
To 
Actual 
Potential ET, Precipitation
Temperature, Radiation 
Wind, Dewpoint
Snowmelt
Interception 
Storage
Lower Zone 
Storage
Groundwater
Storage
Interflow Upper Zone 
Storage
Overland Flow 
Deep or Inactive 
Groundwater 
CEPSC* 
BASETP* 
AGWETP* 
DEEPFR* 
LZSN* 
INFILT*
INTFW* 
UZSN* 
AGWRC* 
NSUR*
SLSUR* 
LSUR* 
IRC* 
Delayed Infiltration
PERC
   ET 
2 
   ET 
   ET 
   ET 
LZETP* 
  *     Parameters 
Output
Process Input 
Storage 
Order taken to 
meet ET demand 
Decision 
n
6 
5 
4 
3 
 26 
The developers of the Stanford Watershed Model made improvements on their 
original model and created the HydroComp Simulation Program (HSP), which included 
sediment transport and water quality simulation.  During the early 1970s other field level 
based watershed water quality programs were also being developed:  the Environmental 
Protection Agency’s Agricultural Runoff Management (ARM) Model (Donigian and 
Davis, 1978) and the Nonpoint Source Pollutant Loading (NPS) Model (Donigian and 
Crawford, 1979). 
During the latter part of the 1970s the EPA funded and directed the creation of a 
single program that could perform all of the functions included in HSP, ARM, and NPS.  
The result of this effort was HSPF, which was first released publicly in 1980, 26 years 
ago.  HSPF is considered to be one of the first comprehensive watershed models.  It is 
widely used and has undergone many modifications and additions over its lifetime. 
Just after the release of HSPF, the USGS began developing software to help 
facilitate watershed modeling by providing interactive capabilities for model input 
development, data storage, data analysis, and model output analysis.  ANNIE, WDM, 
Scenario Generator (GenScn), and HSPEXP are all USGS software products.  They have 
facilitated watershed model creation, analysis, and report creation. 
Throughout the 1980s and 1990s, HSPF went through a series of algorithm and 
code enhancements, which have culminated in the current release version 12.  (Bicknell 
et al., 2001)  Although data requirements are extensive and learning to correctly use the 
model requires a significant amount time, the Environmental Protection Agency 
recommends its use as the most appropriate management tool available for the continuous 
simulation of hydrology and water quality in watersheds. 
In 1994 development began for EPA’s Better Assessment Science Integrating 
Point and Non-point Sources (BASINS) modeling system.  BASINS provides a full range 
 27 
of tools and data which are integrated into a single modeling package that includes 
environmental databases, accepted EPA models, assessment tools, processing utilities, 
and report generating software.  Today the HSPF/BASINS package serves as a focal 
point for cooperation and integration of watershed modeling and model support activities 
between the USGS and the EPA. 
HSPF is currently one of the most comprehensive and flexible models of 
watershed hydrology and water quality available.  It is one of a small number of available 
models that can simulate a continuous, dynamic event, or steady-state behavior of both 
hydrologic/hydraulic and water quality processes in a watershed with an integrated 
linkage between surface, soil, and stream processes.  (AquaTerra, 2005) 
3.3 HSPF OVERVIEW 
Hydrologic Simulation Program – FORTRAN (HSPF) is an analytical tool that 
has applications in the design, management, and operation of water resources systems.  
HSPF uses forcing data such as rainfall, temperature, and evaporation, as well as 
parameters related to land use patterns, soil characteristics, and agricultural practices to 
simulate the processes that occur in a watershed.  HSPF simulates a timeseries of the 
quantity and quality of water transported over the land surface and through various soil 
zones and groundwater aquifers to the stream network.  Runoff flow rate, sediment loads, 
nutrients, pesticides, toxic chemicals, and other water quality constituent concentrations 
can be predicted.  HSPF can then produce a timeseries of water quantity and quality at 
any initially specified point in the watershed. 
3.3.1 HSPF Perspective of the Hydrologic Cycle 
Within the HSPF modeling environment the movement and storage of water is 
conceptualized as presented in Figure 3.3.  The major characteristics of the modeled 
 28 
hydrologic cycle are precipitation, evapotranspiration, land use / land cover, vegetation 
and soil type, groundwater qualities, and the river network.  
Figure 3.3: Hydrologic Cycle 
In HSPF, hydrologic processes are characterized mathematically as flows and 
storages.  Typically, each inflow is an outflow from a storage, which includes 
groundwater, soils, and even the river reach itself.  This relationship is usually expressed 
as a connection between the current storage amount and the physical characteristics of the 
subsystem.  Although, for the most part, HSPF is based on physical characteristics, it has 
many processes that are represented by abridged or theoretical approaches. Although this 
 29 
method requires that parameters be calibrated, there is an advantage in avoiding 
computation of all of the physical characteristics of the watershed. 
The watershed, in an HSPF model, is represented in terms of land segments and 
water bodies.  In general, a particular land segment is defined by having similar 
hydrologic characteristics. Water, sediment, and chemical and biological pollutants move 
laterally downslope as they flow across the watershed toward a different land segment or 
reach.  In HSPF, land segments can be defined as either pervious or impervious.  Each 
segment of land that has the capacity to allow infiltration is considered pervious, 
otherwise it is considered impervious.  Pervious and impervious land segments are 
simulated independently in HSPF. 
The soil environment, within a pervious segment, is divided into three major 
groups: upper zone, lower zone, and intermediate zone.  Vegetation influences the 
movement of water into and out of this soil environment through interception and 
transpiration.  Below the soil zone, groundwater is divided into two zones: an active 
groundwater zone, which may discharge to streams, and an inactive groundwater zone, 
which recharges the aquifer. 
3.3.2 HSPF Application Modules 
HSPF simulates the processes in and of water through the watershed with three 
application modules and eight utility modules.  The three application modules simulate 
the hydrology/hydraulic and water quality components of a watershed.  They are 
PERLND, IMPLND, and RCHRES.  PERLND simulates the runoff and water quality 
constituents from pervious land segments.  IMPLND simulates the runoff and water 
quality constituents from impervious land segments.  RCHRES simulates the movement 
of water and water quality constituents in streams and impoundments.  See Table 3.1 for 
the list of modules and their associated uses. 
 30 
Table 3.1: Modules and Associated Uses (Bicknell et al., 2001) 
PERLND 
Snow, Water, Sediment, Soil Temperature, Water 
Quality, Pesticide, Nitrogen, Phosphorus, Tracer 
IMPLND Snow, Water, Solids, Water Quality Application 
Modules 
RCHRES 
Hydraulics, Conservative, Temperature, Sediment 
Non-conservatives, BOD/DO, Nitrogen, 
Phosphorous, Carbon/pH, Plankton 
COPY Data Transfer 
PLTGEN Plot Data 
DISPLAY Tabulate, Summarize 
DURANL Duration 
GENER Transform or Combine Timeseries Data 
MUSTIN Timeseries Data 
BMP Compute pollutant removal via control measures 
Utility 
Modules 
REPORT Customize and view model report 
3.3.3 PERLND Module 
PERLND is the most frequently used module in HSPF because it simulates the 
activities in pervious land segments.  Water can move within the PERLND module along 
one of three paths:  overland flow, interflow, and groundwater flow.  These paths each 
have different water release delay parameters and interaction with water quality 
constituents. 
Figure 3.4 defines the structure and components of the PERLND module.  The 
PERLND module features individual subroutines for specific modeling purposes.  
The PWATER subroutine in the PERLND module is used to calculate the water 
budget components resulting from water movement in, out, and through pervious land 
segments.  As a result it is the key component of the PERLND module. 
 
 31 
Figure 3.4: PERLND Structure Chart (AquaTerra, 2005) 
The only other component used in this TMDL study was PQUAL.  It simulates 
general water quality constituents, including Fecal Coli Form bacteria, in the outflows, 
both on and below the surface, of a pervious land segment using simple relationships 
with water and/or sediment yield.  HSPF allows quantities in surface outflow to be 
simulated by either one or both, of the two available methods.  The first is to use a 
“potency factors” to indicate constituent strength relative to the sediment removal 
computed by SEDMNT.  The second is to model the storage of a constituent on the land 
surface, considering the accumulation and depletion or removal of the constituent, with a 
 32 
first-order wash off rate of the remaining constituent removed by overland flow after a 
storm event, which is computed by PWATER.  Both formulations can be used to 
represent the wash off behavior of particulate and dissolved components of specific 
pollutants. 
3.3.4 IMPLND Module 
The IMPLND module is used for impervious land surfaces, which consist mainly 
of urban land use categories where little or no infiltration occurs.  Water, solids, and 
various pollutants are removed from the IMPLND land surfaces by the lateral movement 
of water down slope to another land segment, a stream channel, or a reservoir.  A 
complete layout of the IMPLND structure is shown in Figure 3.5.  
Figure 3.5: IMPLND Structure Chart (AquaTerra, 2005) 
 33 
The main subroutine in IMPLAND is IWATER, which calculates the water 
budget in an impervious land segment.  IWATER was the only subroutine used in the 
HSPF model for this study. 
3.3.5 RCHRES Module 
The RCHRES module is used to route runoff and water quality constituents 
simulated by PERLND and IMPLND through stream channel networks and reservoirs.  
This module simulates the processes that occur in a series of open or closed channel 
reaches or completely mixed impoundments.  The flow in a water body is modeled as 
unidirectional.  A number of processes can be modeled, they include hydraulic behavior 
and DO and BOD balances.  Figure 3.6 defines the structure and contents of the 
RCHRES module. 
 
Figure 3.6: RCHRES Structure Chart (AquaTerra, 2005) 
 34 
 The HYDR subroutine of the RCHRES module simulates the processes that 
occur in a single reach of an open channel or completely mixed impoundment.  The 
hydraulic behavior is modeled using the kinematic wave method; therefore the 
momentum of flow is not considered.  All the inflows into a reach are assumed by HSPF 
to enter at a single upstream point.  The outflow of a single reach may be distributed 
across several outlets that represent normal outflows, diversions, or multiple gates in a 
reservoir.  In HSPF, outflows can be represented by either, or both of two methods.  First, 
the outflow can be modeled as a function of reach volume for situations in which there 
are no controls on flows, or gate settings are only a function of water level.  Second, the 
outflow can also be simulated as a function of time to represent demands from municipal, 
industrial, or agricultural use. 
There are no assumptions as to channel shape, but HSPF does make two 
assumptions for stream hydraulics.  First, there is, for every reach, a preset, user-defined 
relationship between water depth, surface area, volume, and discharge. This is specified 
in the Function Table (FTABLE) of the .uci file.  Second, for any outflow demand with a 
volume-dependent component, the relationship between the four variables listed above is 
typically constant in time.  However, seasonal or daily variations in discharge values can 
be input by the user. 
3.4 CLOSING 
The U.S. Environmental Protection Agency recommends the use of HSPF for 
hydrologic and water quality watershed process modeling because of its ability to 
calculate multiple water quality constituents continuously in an unsteady flow 
environment.  These characteristics make HSPF an ideal model for many different types 
of watersheds across the United States and the world.  But it also makes HSPF an 
extremely complex model, which requires a good deal of time and effort to master. 
 35 
Even though the parameters, for the most part, are physically defined there are 
still a number of them which are undefined and must be calibrated.  The vagaries in these 
parameters can often be used to compensate for the unknowns characteristics of the 
physical system or the lack of precision and accuracy in the known data. 
The structural construction of HSPF takes into account the lack of complete 
understanding of the physical system in which water and pollutants interact and travel.  It 
was created at a time in which the known physical system characteristics could not be 
defined at the detailed spatial resolution that is obtainable today.  Limitations in the 
coded structure of HSPF reduce the advancements in hydrologic modeling which could 
be made given the readily accessible spatial and temporal data now available.
 36 
Chapter 4 Motivation 
The forcing data required for a simple hydrologic model in HSPF are precipitation 
and evaporation.  Traditionally, weather data is acquired from single point gauges and 
applied using Thiessen polygons over the modeled watershed area.  This technique is 
standard practice and adequate in a climate with a significant amount of frontal weather 
systems or a densely gauged area.  The Sandies and Elm watershed is located in a semi-
arid climate known for significant convective storm events.  The flow variability of the 
streams is defined by these convective storm systems.  Bacteria and dissolved oxygen 
monitoring were performed on a storm event basis.  The model needs to be calibrated to 
these storm events, and therefore the storm event data input into the model should be 
accurately represented with reference to both volume and spatially distribution. 
4.1 PRECIPITATION DATA SOURCES 
There are multiple available sources of archived precipitation data.  Each has 
strong and weak points associated with use in a hydrologic model.  Some are spatial in 
nature, others are point driven.  Brief descriptions of the different sources are discussed 
below. 
4.1.1 NCDC 
In the United States, the National Oceanic and Atmospheric Administration 
(NOAA) operates the National Climate Data Center (NCDC) whose function is to collect, 
archive, quality assess, and disseminate conventional surface and upper air data needed 
for national and international environmental research programs.  (Shea et al., 1994) 
The NCDC is the traditional source of the forcing data that is required by HSPF.  
The NCDC has a vast array of information available for download from their website, 
www.ncdc.noaa.gov.  This information includes reports, analysis, summaries, and 
 37 
averages for both event, mean, and interval weather and climate related data.  NCDC has 
many stations across the United States that gather this data.  Depending on the order of 
the station, different intervals of data are collected.  The recording intervals include 
hourly, daily, monthly, and annual.  Acquiring information on anything greater than a 
daily time step would be unreasonable for continuous model output. 
4.1.1.1 Daily 
A search of NCDC precipitation stations was conducted in the five county area 
surrounding the 712 square mile Sandies and Elm study area.  There are 1,436 NCDC 
daily stations available in Texas.  Twenty-seven (27) of these stations are located in the 
five county area surrounding the Sandies and Elm watershed as shown in Figure 4.1.  Of 
these 27 stations, 15 had data available for 2000 through 2004, but only one, Nixon, is 
actually located in the Sandies and Elm watershed as indicated in Figure 4.2.  
Unfortunately, Nixon precipitation data is missing for October 2002 through November 
2004. 
 38 
Figure 4.1: Available NCDC Daily Precipitation Stations (NOAA: NCDC, 2006b) 
Figure 4.2: Available NCDC Daily Precipitation Stations for years 2000 thru 2004 
 39 
4.1.1.2 Hourly 
There are 525 NCDC hourly stations available in Texas.  Three of these stations 
are located in the five county area surrounding the Sandies and Elm watershed.  See 
Figure 4.3 below.  Of these three stations only one, Cheapside, had data available for 
2000 through 2004.  The Cheapside station was located near, but not in, the Sandies and 
Elm Watershed (See Figure 4.2). 
 
Figure 4.3: Available NCDC Hourly Precipitation Stations (NOAA: NCDC, 2006b) 
4.1.2 NEXRAD 
The most effective tool to detect spatial coverage of precipitation is RADAR.  
RADAR, which stands for RAdio Detection And Ranging, has been used to detect 
precipitation, and especially thunderstorms, since the 1940's. 
Cheapside 
 40 
NEXRAD, which stands for NEXt Generation RADAR, is a Doppler RADAR.  
The National Weather Service's Doppler RADARs can detect most precipitation within 
approximately 90 miles of the RADAR (as indicated by the size of the circles shown in 
Figure 4.4) and intense rain or snow within approximately 155 miles.  However, light 
rain, light snow, or drizzle from shallow cloud weather systems is not necessarily 
detected.  (Weather Underground, 2006) 
 
Figure 4.4: National Doppler RADAR Coverage (NOAA: NWS, 2006d) 
The RADAR used by the National Weather Service (NWS) is called the WSR-
88D, which stands for Weather Surveillance RADAR - 1988 Doppler (the prototype of 
this RADAR was built in 1988).  As its name suggests, the WSR-88D is a Doppler 
 41 
RADAR, meaning it can detect motions toward or away from the RADAR as well as the 
location of precipitation areas. 
There are 155 WSR-88D Doppler RADAR stations in the nation, including the 
United States Territory of Guam and the Commonwealth of Puerto Rico, operated by the 
NWS and the Department of Defense (DOD) as shown in Figure 4.5 below.  (NOAA, 
NWS, 2006b) 
 
Figure 4.5: National Doppler RADAR Sites (NOAA, NWS, 2006a) 
Level II data are collected at each of these RADAR sites.  Level II data are the 
three meteorological base data quantities: reflectivity, mean radial velocity, and spectrum 
 42 
width. From these measurements, computer processing generates numerous 
meteorological analysis products known as Level III data.  (NOAA, NCDC, 2006a) 
NEXRAD Level III precipitation data represents the best estimate of rainfall 
available from the National Weather Service (NWS). One of these Level III products is 
NEXRAD precipitation data which is collected by the National Weather Service (NWS) 
and distributed for the entire conterminous United States on a 16 square kilometer grid. 
4.1.3 DAYMET 
DAYMET stands for DAilY METeorological, and is a model that creates daily 
surface weather and climatological summaries for the conterminous United States. 
DAYMET was developed at the University of Montana, Numerical Terradynamic 
Simulation Group (NTSG), to fulfill the need for fine resolution, daily meteorological 
and climatological data necessary for plant growth model inputs.  It is now maintained by 
the National Center for Atmospheric Research (NCAR). 
Using a digital elevation model and daily observations of minimum and 
maximum temperatures and precipitation from ground-based gauged meteorological 
stations, a 25 year (1980 - 2004) daily data set of temperature, precipitation, humidity and 
radiation has been produced as a continuous surface at a 1 km resolution.  (DAYMET, 
2006a)  An example of the DAYMET national 18-year monthly mean total precipitation 
for the month of August is shown in Figure 4.6. 
 43 
Figure 4.6: National 18-Year Mean Monthly Total Precipitation for August (DAYMET, 
2006b) 
4.1.4 NARR 
NARR stands for North American Regional Reanalysis of climate.  NARR was 
created by the National Center for Environmental Prediction (NCEP) with cooperation 
from the National Weather Service, the National Oceanic and Atmospheric 
Administration, and the Department of Commerce.  NCEP has published the output of 
their current weather models that were run using historical observation data, which have 
interpolated weather related data for a large portion of the North America at a three hour, 
daily, and monthly average time steps on a 32 kilometer grid.  The available weather 
related data are numerous and include both precipitation and evaporation.  NARR data is 
currently difficult to harvest, and was not considered for this project, but efforts are 
 44 
currently being undertaken that will eliminate this difficulty and make NARR data 
gathering easier for hydrologic and watershed science analysis in the near future. 
4.2 PRECIPITATION DATA SPATIAL COMPARISON 
Given the lack of gauging stations across the Sandies and Elm 712 square mile 
watershed, and the lack of data for over two years of the study period at the one station in 
the watershed, spatial interpolation of the data from daily stations with available data was 
attempted. 
4.2.1 Initial Precipitation Data Comparison 
ArcGIS has multiple tools that calculate rasters files from point data.  Of the 
available GIS methods, the ones chosen for an initial trial include Spline and Inverse 
Distance Weighted (IDW).  The initial interpretation was measured against one day of 
NEXRAD data that was available for a significant storm which took place on August 27, 
2001.  The results of this interpolation are shown below.  When compared against the 
NEXRAD image from that day (Figure 4.10) both interpolation methods significantly 
underestimate the storm.  Images of the NCDC gauge data Spline interpolation is shown 
in Figure 4.7 and the IDW interpolation method is shown in Figure 4.9.   
 45 
 
Figure 4.7: NCDC Gauge Spline Interpolation, August 27, 2000 
All three of the interpreted storms below are shown at the same color scale, seen 
in Figure 4.8. 
Figure 4.8: Storm Color Scale (hundredth inch) 
 
 46 
The Spline interpolation has a nice “rain-like” coverage across the watershed, but 
has one very large flaw.  The areas that are indicated in purple and pink are areas in 
which the spline method interpolated negative rain.  The interpolation by the Inversed 
Distance Weighted method is shown in Figure 4.9.   
 
Figure 4.9: NCDC Gauge IDW Interpolation, August 27, 2000 
Although the coverage is not quite as “rain-like” as the spline method, there is no 
negative rain.  The Inverse Distance Weighted method was used for all additional gauge 
interpolations. 
 47 
The underestimation by the gauges can be explained for a number of reasons, the 
first being that there are no gauges near the center of the storm cell.  This storm event is 
an example of storms that are common in the semi-arid regions in the summer months.   
Figure 4.10: NEXRAD Image, August 27, 2000 
Intense storm events are dominated by the presence of convective rain cells.  
(Rebora and Ferraris, 2006)  These cells are intense rainfall structures with spatial 
dimensions from 5 to 10 kilometers that are embedded in regions of more widespread 
rainfall.  The cells tend to last around 30 minutes and produce peak precipitation of 2 to 4 
inches/hour.  (Austin and Houze, 1972)  The storm cell in Figure 4.10 is typical of the 
 48 
above definition.  It is 5 km by 20 km with a total precipitation of 3 inches with 2.3 
inches of that falling within a one hour time period. 
A study of the most severe storms for each month during the study period of 2000 
through 2004 was undertaken to examine whether the storm cell phenomena of August 
27, 2001 was typical.  Stage III NEXRAD data was download from the NOAA, West 
Gulf River Forecast Center.  (NOAA:NWS, 2005b)  For more information about this 
process see section 5.2.1.  This data was translated into a database file and evaluated 
using Microsoft Access. 
One set of storms was chosen by using the precipitation from the day in which the 
maximum value occurred on a single NEXRAD cell for each month of the five year 
period.  This selection method tended to expose the storms containing convective cells.  
For the remainder of this thesis, this set will be referred to as the Convective Storm Set.  
Another set of storms was chosen by using the storm in which the maximum value 
occurred at an NCDC gauge.  This technique tended to uncover either widespread intense 
storms or ones of a frontal system.  From this point forward this set will be referred to as 
the Frontal Storm Set.  Table 4.1 lists the storms that were studied.  The storms that are in 
italics are the storms that were selected for study using both methods. 
NEXRAD images from each of these storms were compared to the storms as 
defined by NCDC daily precipitation stations and interpolated by Inverse Distance 
Weighting and DAYMET.  See Appendix A and Appendix B for figures and data 
associated with the Convective Storm Set and the Frontal Storm Set, respectively. 
 49 
Table 4.1: Selected Convective and Frontal Storms 
 Convective Storms Frontal Storms 
January January 27, 2000 January 8, 2000 
February February 23, 2000 February 21, 2003 
March March 11, 2000 March 15, 2000 
April April 23, 2001 April 8, 2002 
May May 13, 2004 May 20, 2000 
June June 10, 2000 June 30, 2002 
July July 31, 2000 July 15, 2002 
August August 31, 2001 August 31, 2001 
September September 22, 2001 September 7, 2002 
October October 25, 2003 October 9, 2002 
November November 17, 2003 November 17, 2003 
December December 12, 2002 December 4, 2002 
4.2.2 Precipitation Spatial Evaluation Results 
One of the difficulties of spatial interpolation of daily gauge data occurs because 
each station’s precipitation is recorded at a different time.  For instance, the Nixon station 
information is consistently taken at seven in the morning and the New Braunfels 
Municipal Airport data is taken at midnight.  The Cuero 3NW and Cheapside stations 
present an even more interesting challenge in that the data is taken at these stations at 
different hours through the five year period.  Sometimes the data is taken at eight in the 
morning and sometimes it is taken at five in the afternoon.  Fortunately, the majority of 
the stations through the five year comparison period took their data at seven in the 
morning.  The New Braunfels Municipal Airport, which consistently took their data at 
midnight, is far enough away from the watershed that it does not significantly affect the 
 50 
interpolation.  Therefore, the NEXRAD data, which is in an hourly format, was 
aggregated from 7am to 7am to compare accurately with the NCDC gauge data. 
The DAYMET interpolation of the daily data makes no attempt at equalizing the 
recording interval.  Therefore, for this area at least, the DAYMET data is also on a 7 am 
to 7 am time period. 
The precipitation rasters were evaluated both visually and using ArcGIS’ spatial 
analyst.  All of the storms are shown with the same color scale (See Figure 4.11), so that 
the intensity of the storms can be seen not just between interpolations for a certain storm 
but across all of the storms interpolated throughout the study.  The storms are measured 
in hundredth of an inch, which is how they are gauged at NCDC stations. 
Figure 4.11: Storm Color Scale (hundredth inch) 
In the Convective Storm Set, the NCDC gage rainfall interpolation 
underestimated all but one of the chosen storms.  The main difference between the two 
storm sets was the inability of the gauges to interpret the small and intense convective 
cells that dominated this series of storms. 
An example of this can be seen in the May 13, 2004 storm.  The gauged rainfall 
from this storm was interpolated well over the watershed area in reference to total 
precipitation.  It only had a 12.4% difference between the gage interpolation and 
NEXRAD over the watershed, but a large and intense storm cell was completely missed 
just off the watershed boundary as shown in Figure 4.12 and Figure 4.13 below. 
 
 51 
 
Figure 4.12: NEXRAD May 13, 2004 
 
Figure 4.13: NCDC Gauge IDW Interpolation May 13, 2004 
There was only one storm in the Convective Storm Set in which the NCDC 
overestimated the precipitation, November 17, 2003.  The total precipitation interpolated 
from the gauges was 103% greater than that measured by NEXRAD.  See the NEXRAD 
 52 
and NCDC Interpolation images of the November 17, 2003 storm in Figure 4.14 and 
Figure 4.15, respectively, below. 
 
Figure 4.14: NEXRAD November 17, 2003 
 
Figure 4.15: NCDC Gauge IDW Interpolation November 17, 2003 
 53 
During this storm the convective cell was located nearly directly above the Cuero 
3NW gaging station.  This gauge was interpolated with a greater spatial significance than 
was measured by NEXRAD and greatly influenced the interpolation between the gauges 
across the basin. 
The storm from October 25, 2003 shows how a significant storm can miss being 
captured by the NCDC gaging stations.  The Nixon station was not in operation at this 
time and the storm, a significant one, passed above the station through the center of the 
watershed and had a maximum NEXRAD recorded rainfall near 4.5 inches.  The NCDC 
gauges show no rain, but during this time the USGS flow gauge increases from 5.2 cfs to 
15 cfs during the course of a day, which indicates a significant amount of precipitation 
over the watershed.  (See Figure 4.16) 
 
Figure 4.16: NEXRAD October 25, 2003 
In the Frontal Storm Set, NCDC overestimated six of the twelve storms evaluated 
and this overestimation produced an average difference in total precipitation between, the 
 54 
NCDC interpolated values and the NEXRAD values of 138%.  Yet, for four of the twelve 
storms the difference between NCDC and NEXRAD was below 10% in this batch as 
opposed to only one of the twelve storms in the Convective Storm Set, and that storm is 
one that is also included in this set, August 31, 2001. 
Visually the Frontal Set storms were very different.  This difference was found to 
be due mainly to the longer precipitation duration of these storms and the differences in 
recording times between the different NCDC stations. 
The most visually obvious example of this difference is shown in Figure 4.17 and 
Figure 4.18 for the storm from February 21, 2003.  This storm had the worst spatial and 
precipitation total correlation, a 584% difference between the NCDC gage interpolation 
and NEXRAD data. 
 
Figure 4.17: NEXRAD February 21, 2003 
 55 
 
Figure 4.18: NCDC Gauge IDW Interpolation February 21, 2003 
These images were so dramatically different that the data was checked multiple 
times to make certain that the interpolation was correct.  NEXRAD data shows that the 
storm began at 5:00 am on February 20, 2003 and ended at 10:00 am on February 22, 
2003.  The NEXRAD data showed the storm to peak between 10:00 and 11:00 pm on 
February 20, 2003.  Therefore, most of the body of this storm and its peak should be 
encapsulated by two days of NCDC gauge data, given the 7am measurement time.  
Instead it is spread over four days of records as shown in Table 4.2. 
An interpolation of the entire storm was created.  Taking the whole storm into 
account greatly reduced the difference in total precipitation between the NCDC 
interpolation and NEXRAD, but the overall visual comparison is still not good.  This is 
most likely due in part to the data missing at two stations, Gonzales 10 SW and Nixon.  
See Figure 4.19 and Figure 4.20 below for the total storm interpolations. 
 56 
Table 4.2: NCDC Data for February 21, 2003 Storm 
Precipitation (h.i.) 
 2/19/2003 2/20/2003 2/21/2003 2/22/2003 Sum 
BELMONT                        
0 0 206 0 206 
CHEAPSIDE                      
0 10 152 15 177 
CUERO 3 NW                     
0 0 0 0 0 
FALLS CITY 4 WSW          
0 16 60 0 76 
FLORESVILLE                    
0 92 35 0 127 
GONZALES 1                     
0 0 0 0 0 
KARNES CITY                    
0 47 90 9 146 
KINGSBURY                      
0 172 235 21 428 
NEW BRAUNFELS MAP    
57 170 21 0 248 
RUNGE                          
26 97 0 0 123 
SEGUIN 1 SSW                   
0 60 210 58 328 
STOCKDALE                      
15 102 14 0 131 
YORKTOWN                       
19 82 6 0 107 
 
Figure 4.19: NEXRAD 2/19/2003 thru 2/22/2003 
 57 
 
Figure 4.20: NCDC Gauge IDW Interpolation 2/19/2003 thru 2/22/2003 
Given the very significant increase in flow at the gauge from 219 cfs to 2650 cfs 
from February 20, 2003 to February 23, 2003 it is reasonable to guess that NEXRAD 
underestimated this storm rather than the NCDC gauges overestimating it. 
The entire storm is not nearly as undervalued as the one day of rain in February 
that was initially evaluated.  NEXRAD still underestimates the storm by 35.8%; see 
Table 4.3 below, but the range, mean, and standard deviation are much closer together. 
Table 4.3: Spatial Analysis of Precipitation Methods over Sandies & Elm Watershed 
Date Type Total (in) 
Min 
(in) 
Max 
(in) 
Mean 
(in) 
Std. Dev. 
(in) 
NCDC 256,309.00 0.00 2.80 1.39 0.49 
NEXRAD 188,752.00 0.24 2.18 1.02 0.40 
February 21, 
2003 Storm 
Difference -35.8% 0.24 -0.62 -0.37 -0.09 
 
 58 
Another storm in which a visual inspection of the interpolations gave pause was 
the storm from March 14, 2000.  Comparison of Figure 4.21 and Figure 4.22 shows a 
large discrepancy between the two methods.  The visual inconsistency was so great 
between the NEXRAD and NCDC gauge interpolation that the entire storm was 
interpolated and checked. 
The NEXRAD data indicates that the rain from this storm fell between 6:00 pm 
on March 14, 2000 and 6:00 am on March 15, 2000.  Therefore, the storm should be 
encompassed by one day of NCDC daily gauge data (see Table 4.4 for NCDC 
precipitation data) if the measurements were taken, as indicated, at 7:00 am.  Instead, the 
storm appears to be spread over two days, March 14 and 15.  The interpolation of the 
entire storm is shown in Figure 4.23 and Figure 4.24. 
 
Figure 4.21: NEXRAD March 14, 2000 
 59 
 
Figure 4.22: NCDC Gauge IDW Interpolation March 14, 2000 
Table 4.4: NCDC Data for March 14, 2000 Storm 
Precipitation (h.i.) 
 3/14/2000 3/15/2000 Sum 
BELMONT                      110 0 110 
CHEAPSIDE                   0 192 192 
CUERO 3 NW                 0 201 201 
FALLS CITY 4 WSW    0 0 0 
FLORESVILLE              22 134 156 
GONZALES 1                 0 156 156 
GONZALES 10 SW        165 0 165 
KARNES CITY               17 282 299 
NIXON                          0 144 144 
RUNGE                          0 139 139 
SEGUIN 1 SSW               0 80 80 
STOCKDALE                 135 0 135 
YORKTOWN                  215 0 215 
 
 60 
 
Figure 4.23: NEXRAD 3/14/2000 thru 3/15/2000 
 
Figure 4.24: NCDC Gauge IDW Interpolation 3/14/2000 thru 3/15/2000 
 61 
The precipitation totals from the two methods compare more reasonably for this 
storm.  Only a 17.2% difference was detected between the two methods as shown in 
Table 4.5. 
Table 4.5: Spatial Analysis of Precipitation Methods over Sandies & Elm Watershed 
Date Type Total (in) 
Min 
(in) 
Max 
(in) 
Mean 
(in) 
Std. Dev. 
(in) 
NCDC 296,079.00 1.00 2.11 1.61 0.24 
NEXRAD 357,625.00 1.07 3.58 1.94 0.63 
March 14, 
2000 Storm 
Difference 17.2% 0.07 1.47 0.33 0.39 
One of the very best interpolations according to the precipitation totals, with only 
1% difference between the NCDC interpolation and NEXRAD, was the interpolation of 
the storm from June 30, 2002.  As shown in Figure 4.25 and Figure 4.26, the overall 
precipitation pattern was well formed over the watershed, but the NCDC did interpolate 
the northwest corner with more rain than was estimated from the NEXRAD data. 
 
Figure 4.25: NEXRAD June 30, 2002 
 62 
 
Figure 4.26: NCDC Gauge IDW Interpolation June 30, 2002 
4.2.3 Precipitation Spatial Evaluation Summary 
Overall the NCDC stations underestimated the precipitation measured by 
NEXRAD 70% of the time.  When the total precipitation was underestimated it was 
underestimated by an average of 43.2%.  When the total precipitation was overestimated 
it was overestimated by an average of 138%.  The overall average total precipitation 
estimation differed by 71.4% for the two methods. 
On average each storm studied had between 1 and 3 convective cells measuring 
between 5 and 10 kilometers.  The total precipitation assessment of the gauge 
interpolation versus NEXRAD shows that the gauges did a good job (less than 30% 
difference) of defining the overall precipitation in 7 out of 22 storms analyzed.  Table 4.6 
and Table 4.7 summarize the GIS spatial analysis of the NCDC Interpolation and 
NEXRAD precipitation over the Sandies and Elm watershed. 
 
 63 
Table 4.6: Convective Storm Set Spatial Analysis over the Sandies & Elm Watershed 
Date Type Total (in) 
Min 
(in) 
Max 
(in) 
Mean 
(in) 
Std. Dev. 
(in) 
NCDC 64,788.80 0.12 0.76 0.35 0.17 
NEXRAD 94,459.80 0.11 1.35 0.51 0.25 January 27, 2000 
Difference 31.4% -0.01 0.59 0.16 0.08 
NCDC 189,615.00 0.00 2.16 1.03 0.44 
NEXRAD 308,198.00 0.28 2.98 1.67 0.59 February 23, 2000 
Difference 38.5% 0.28 0.82 0.64 0.15 
NCDC 9,695.44 0.00 0.18 0.05 0.04 
NEXRAD 126,867.00 0.00 5.20 0.69 1.14 March 11, 2000 
Difference 92.4% 0.00 5.02 0.64 1.10 
NCDC 44,991.70 0.00 2.04 0.24 0.24 
NEXRAD 242,869.00 0.15 3.29 1.32 0.67 April 23, 2001 
Difference 81.5% 0.15 1.25 1.08 0.43 
NCDC 139,660.00 0.00 1.64 0.76 0.35 
NEXRAD 159,472.00 0.00 2.16 0.87 0.44 May 13, 2004 
Difference 12.4% 0.00 0.52 0.11 0.09 
NCDC 286,549.00 0.58 2.85 1.56 0.47 
NEXRAD 406,569.00 0.88 5.50 2.21 0.93 June 10, 2000 
Difference 29.5% 0.30 2.65 0.65 0.46 
NCDC 2,554.15 0.00 0.08 0.01 0.02 
NEXRAD 59,559.30 0.00 2.92 0.32 0.39 July 31, 2000 
Difference 95.7% 0.00 2.84 0.31 0.37 
NCDC 739,440.00 0.32 8.30 4.02 1.77 
NEXRAD 772,034.00 0.77 9.17 4.19 2.14 August 31, 2001 
Difference 4.2% 0.45 0.87 0.17 0.37 
NCDC 38,421.20 0.02 0.75 0.21 0.17 
NEXRAD 68,008.50 0.00 1.72 0.37 0.32 September 22, 2001 
Difference 43.5% -0.02 0.97 0.16 0.15 
NCDC 0.00 0.00 0.00 0.00 0.00 
NEXRAD 46,978.50 0.00 4.47 0.25 0.50 October 25, 2003 
Difference 100.0% 0.00 4.47 0.25 0.50 
NCDC 194,011.00 0.03 5.30 1.05 1.04 
NEXRAD 95,273.60 0.13 4.00 0.52 0.50 November 17, 2003 
Difference -103.6% 0.10 -1.30 -0.53 -0.54 
NCDC 87,005.60 0.00 1.80 0.47 0.40 
NEXRAD 178,093.00 0.26 3.71 0.97 0.62 December 12, 2002 
Difference 51.1% 0.26 1.91 0.50 0.22 
 64 
Table 4.7: Frontal Storm Set Spatial Analysis over the Sandies & Elm Watershed 
Date Type Total (in) 
Min 
(in) 
Max 
(in) 
Mean 
(in) 
Std. Dev. 
(in) 
NCDC 274,628.00 0.63 3.32 1.49 0.60 
NEXRAD 152,924.00 0.36 1.85 0.83 0.20 January 7, 2000 
Difference -79.6% -0.27 -1.47 -0.66 -0.40
NCDC 119,736.00 0.00 1.98 0.65 0.42 
NEXRAD 17,497.20 0.00 0.34 0.09 0.60 February 21, 2003 
Difference -584.3% 0.00 -1.64 -0.56 0.18
NCDC 111,738.00 0.00 1.86 0.61 0.42 
NEXRAD 357,625.00 1.07 3.58 1.94 0.63 March 14, 2000 
Difference 68.8% 1.07 1.72 1.33 0.21
NCDC 595,932.00 1.10 5.08 3.23 1.02 
NEXRAD 557,688.00 0.47 5.56 3.03 1.30 April 8, 2002 
Difference -6.9% -0.63 0.48 -0.20 0.28
NCDC 190,395.00 0.00 4.20 1.03 0.78 
NEXRAD 233,947.00 0.17 3.26 1.27 0.67 May 20, 2000 
Difference 18.6% 0.17 -0.94 0.24 -0.11
NCDC 346,926.00 0.80 3.74 1.88 0.41 
NEXRAD 350,552.00 1.00 3.51 1.90 0.49 June 30, 2002 
Difference 1.0% 0.20 -0.23 0.02 0.08
NCDC 211,415.00 0.71 1.90 1.15 0.25 
NEXRAD 610,469.00 1.67 4.71 3.31 0.59 July 15, 2002 
Difference 65.4% 0.96 2.81 2.16 0.34
NCDC 739,440.00 0.32 8.30 4.02 1.77 
NEXRAD 772,034.00 0.77 9.17 4.19 2.14 August 31, 2001 
Difference 4.2% 0.45 0.87 0.17 0.37
NCDC 431,025.00 1.27 4.98 2.36 0.64 
NEXRAD 290,018.00 0.03 4.23 1.57 1.12 September 7, 2002 
Difference -48.6% -1.24 -0.75 -0.79 0.48
NCDC 314,660.00 0.22 6.29 1.71 0.91 
NEXRAD 303,712.00 0.63 4.49 1.65 0.69 October 9, 2002 
Difference -3.6% 0.41 -1.80 -0.06 -0.22
NCDC 194,011.00 0.03 5.30 1.05 1.04 
NEXRAD 95,273.60 0.13 4.00 0.52 0.50 November 17, 2003 
Difference -103.6% 0.10 -1.30 -0.53 -0.54
NCDC 157,014.00 0.00 2.45 0.85 0.48 
NEXRAD 278,305.00 0.85 2.29 1.51 0.37 December 4, 2002 
Difference 43.6% 0.85 -0.16 0.66 -0.11
 65 
4.3 PRECIPITATION STUDY RESULTS 
There are many regions of the country where NCDC gauges are able to accurately 
represent the precipitation pattern over a watershed.  This region of south central Texas is 
not one of them.  The area is afflicted by storm systems which have multiple convective 
cells with high intensity precipitation.  The NCDC gauges are very far apart and not 
consistent in their recording patterns and availability.  This creates a high degree of 
unreliability in the precipitation interpolation data.  NEXRAD is available on an hourly 
basis where all but one NCDC gauge only had data on a daily time step.  For all of these 
reasons NEXRAD data was chosen for use as the precipitation forcing data in the HSPF 
model of the Sandies and Elm watershed. 
Images of NEXRAD, gauge interpolation, and DAYMET for each of the studied 
storms are included for the Convective Storm Set in Appendix A and for the Frontal 
Storm Set in Appendix B.   
 66
Chapter 5 Model Development 
5.1 GIS TO HSPF OVERVIEW  
The ArcGIS HSPF Preprocessing methodology was designed to facilitate the 
development of an HSPF model in the ESRI ArcGIS environment.  This methodology 
emulates the EPA’s Better Assessment Science Integrating Point and Nonpoint Sources 
(BASINS) HPSF Preprocessing methodology, but implements it in the ArcGIS 
environment.  The only major conceptual difference between the two methods concerns 
the effort to maintain a geospatial description of elements from GIS data in the HSPF 
model.  Though spatial information is not explicitly stored in the HSPF model input file, 
each model element simulated by HSPF represents some spatial location in the real 
world.  In order to facilitate the transfer of information to and from the GIS environment, 
a spatial representation of the areas of land simulated by HSPF is created and must be 
maintained.  The following are the major tasks accomplished by the ArcGIS HSPF 
Preprocessing methodology and utilities in developing a new HSFP model. 
1) Drainage areas boundaries and river networks are defined 
2) Land Segments are defined 
3) Other physically-based attributes are calculated 
4) HSPF input files are created, which include 
a) The user control input (.uci) file 
b) Three intermediate files 
i) Reaches (.rch) file 
ii) Channel geometry (.ptf) file 
iii) Watershed delineation (.wsd) file 
c) Forcing data input (.wdm) file 
 67
Table 5.1 displays an overview of the processes and tools used in the ArcGIS to 
HSPF Preprocessing methodology. 
Table 5.1: Overview of ArcGIS, HSPF, and Timeseries Preprocessing Methodologies 
(Johnson, 2005) 
 
 
 68
For more information about the ArcGIS to HSPF Preprocessing methodology see 
ArcGIS and HSPF Model Development.  (Johnson, 2005) 
5.2 DATA COLLECTION 
The most important activity when creating an HSPF model is to characterize the 
watershed accurately.  GIS based data is widely used both to estimate physically-based 
parameters and to define areas of similar hydrologic character.  (Singh and Woolhiser, 
2002)  GIS data is available from many federal, state, and local government agencies 
such as the United States Geological Survey (USGS), the Environmental Protection 
Agency (EPA), and the Texas Commission for Environmental Quality (TCEQ).  These 
data sources define many watershed characteristics such as, stream networks, topography, 
land use / land cover, geology, and soils.  More recently, spatially defined climatic data 
has also become available for use in a GIS environment.  The ArcGIS HSPF 
Preprocessing methodology, which is summarized in the previous section, was designed 
to incorporate spatially defined weather data, such as NEXRAD precipitation into an 
HSPF model. 
5.2.1 Precipitation 
NEXRAD spatial precipitation files were downloaded for the area around the 
Sandies and Elm watershed from the West Gulf River Forecast Center (WGRFC) 
website.  (NOAA: NWS, 2005b)  The extent of NEXRAD data for the Sandies and Elm 
watershed is shown in See Figure 5.1.   
The WGRFC area is defined by the watershed areas from rivers draining into the 
Gulf of Mexico.  This area includes the majority of Texas, and parts of New Mexico, 
Colorado, and Mexico.  Figure 5.2 displays the area of interest for the West Gulf River 
Forecast Center.  
 
 69
Figure 5.1: NEXRAD Cell Coverage of the Sandies & Elm Watershed 
The incorporation of NEXRAD precipitation data into the ArcGIS and 
subsequently the HSPF environment is a complex and tedious task.  NEXRAD data from 
the WGRFC site is organized in the Hydrologic Rainfall Analysis Project (HRAP) 
coordinate system, which is a polar stereographic (spherical earth datum) projection.  In 
comparison, most geospatial data are in geodetic datum (ellipsoidal earth) coordinate 
system.  The precipitation datasets are in nested compressed binary format files (XMRG).  
For one year of data there are twelve compressed binary monthly files, 672 to 744 
uncompressed ASCII hourly files.  (NOAA: NWS, 2006b; Xie, et al., 2003) 
 
 70
Figure 5.2: West Gulf River Forecast Center Area of Interest (NOAA: NWS, 2005b) 
NEXRAD precipitation data is stored in a format very different from the .wdm 
file format required for HSPF modeling.  ArcGIS and HSPF Model Development, 
Appendix B (Johnson, 2005) describes the process used to extract NEXRAD data from 
its native binary format and write it into the Arc Hydro timeseries format.  GIS tools are 
then used to transfer the precipitation data from Arc Hydro timeseries format into the 
.wdm file format required by HSPF. 
A GIS representation of the HSPF concept of the meteorological segments is then 
used to organize and prepare input time series.  Figure 5.3, below, illustrates the overall 
concept of the ArcGIS Timeseries Preprocessing methodology.  At the heart of the 
ArcGIS Timeseries Preprocessing system is the GIS MetSegment feature class.  It 
 71
contains information that joins the associated features of the Arc Hydro timeseries data to 
the HSPF model files.  (Johnson, 2005)  This connection is important given the spatial 
relationship that is required to accurately transfer data between the GIS and HSPF 
environments. 
 
Figure 5.3: Schematic Overview of ArcGIS Timeseries Preprocessing Methodology 
(Johnson, 2005) 
5.2.2 Evaporation 
A search of NCDC evaporation stations in the five county area produced no 
results.  Extending the radius, five evaporation stations, shown in Figure 5.4, were found 
in the nearby area.  The evaporation data from these sites were incomplete; therefore an 
average of the available data was taken and put into one evaporation timeseries for the 
 72
entire watershed.  Since these stations were all at large reservoirs a pan evaporation factor 
of 0.70 was applied to the evaporation timeseries in the HSPF model. 
Figure 5.4: NCDC Evaporation Stations 
5.2.3 Land Use / Land Cover 
The 2000 land use / land cover data set is not currently available for the Sandies 
and Elm watershed.  Therefore, digital raster images of the 1992 land use / land cover 
were downloaded from the United States Geological Survey (USGS), Seamless site.  (See 
Figure 5.5)  (USGS: Seamless, 2005)  The use of this data is not considered erroneous 
because the watershed is not a region of rapid growth or change.   
The National Land Cover Data 1992 (NLCD 92) is a 21-category land cover 
classification scheme that has been applied consistently over the conterminous United 
States.  The NLCD 92 classification is provided as raster data with a spatial resolution of 
30 meters.  The data is expressed in geographic coordinates (latitude/longitude), and it is 
referenced to the North American Datum of 1983 (NAD83).  (USGS: Seamless, 2006a) 
 
Canyon Dam 
SeaWorld SAT
Beeville 5 NE
Choke Canyon DAM 
Coleto Creek Res.
 73
 
Figure 5.5: Land Use / Land Cover Data (USGS: Seamless, 2006a) 
5.2.4 Streams 
The high-resolution streams from the national hydrography dataset were 
downloaded from the NHD website as seen in Figure 5.6.  (USGS: NHD, 2005) 
The National Hydrography Dataset (NHD) is a feature-based database that 
interconnects and uniquely identifies the stream segments or reaches that make up the 
nation's surface water drainage system.  The high-resolution NHD, was developed at a 
1:24,000 to a 1:12,000 scale.  This increase in resolution added a good amount of detail 
from the original 1:100,000-scale NHD.  (USGS: NHD, 2005) 
 
010205
Kilometers
¯
Land Use / Land Cover
Open Water
Light Residential
Heavy Residential
Commercial/Industrial
Bare Rock/Sand/Clay
Quarries/Strip Mines
Deciduous Forest
Evergreen Forest
Mixed Forest
Shrubland
Grassland
Pasture/Hay
Row Crops
Small Grains
Urban/RecGrass
Woody Wetlands
Herbaceous Wetlands
 74
Figure 5.6: NHD High-Resolution Flowlines for the Sandies and Elm Watershed 
5.2.5 Topography 
Digital raster images of the 1/3 arc second topographic information were 
downloaded from the USGS: Seamless site as seen in Figure 5.7.  (USGS: Seamless, 
2005)  The National Elevation Dataset (NED) 1/3 Arc Second is a raster product 
assembled by the USGS.  NED 1/3 Arc Second is designed to provide National elevation 
data in a seamless form with a consistent datum, elevation unit, and projection.  NED 1/3 
Arc Second has a resolution of 1/3 arc-second which is approximately 10 meters.  The 
dataset is referenced to NAD83 as horizontal datum, and all the data are recast in a 
geographic projection.  (USGS: Seamless, 2006b) 
 75
 
Figure 5.7: 1/3 Arc Second National Elevation Data (USGS: Seamless, 2005)  
5.2.6 Geology and Soils 
Detailed soil infiltration information is helpful for hydrologic modeling on large 
scales.  For the United States two databases are available from the United States 
Department of Agriculture, Natural Resource Conservation Service: the Soil Survey 
Geographic (SSURGO) database and the State Soil Geographic (STATSGO) database.  
The STATSGO database was developed from 1:250,000 scale soil maps and the 
SSURGO information was developed from 1:24,000 scale soil maps.  Figure 5.8 shows 
the STATSGO coverage for the Hydrologic Soil Groups (A, B, C, and D).  Descriptions 
of hydrologic soil groups are summarized in Table 5.2. 
Elevation Legend
227 meters
 
40 meters
¯
 76
 
Figure 5.8: STATSGO Hydrologic Soil Groups 
Table 5.2: Hydrologic Soil Groups 
Hydrologic 
Group 
Description 
A 
High infiltration rates.  Soils are deep, well drained to excessively 
drained sands and gravels 
B 
Moderate infiltration rates.  Deep and moderately deep, moderately well 
and well-drained soils with moderately course textures. 
C 
Slow infiltration rates.  Soils with layers impeding downward movement 
of water, or soils with moderately fine or fine textures. 
D Very slow infiltration rates.  Soils are clayey, have a high water table. 
 77
5.2.7 Stream Flow 
Daily stream flow data from the USGS gage 08175000 on Sandies Creek at 
Westhoff, Texas in DeWitt County was used to calibrate the hydrologic portion of the 
HSPF model.  The gage is located at 29º12’54” North and 97º26’57” West (NAD 27) and 
is 178.27 feet (54.34 meters) above sea level (NGVD29).  The gage has a contributing 
area of 549 square miles. 
USGS Gage 08175000 Flow for 1999 thru 2004
0
1
10
100
1000
10000
100000
1
/1/9
9
5
/
1/99
9
/
1/99
1
/1/0
0
5
/1/0
0
9
/
1/00
1
/1/0
1
5
/
1/01
9
/
1/01
1
/1/0
2
5
/
1/02
9
/
1/02
1
/1/0
3
5
/
1/03
9
/
1/03
1
/
1/04
5
/1/0
4
9
/
1/04
Date
F
l
ow (cfs)
 
Figure 5.9: Sandies Creek USGS Gage Flow 1999 thru 2004 
5.3 MODEL CONSTRUCTION 
HSPF models simulate a watershed through a sequence of HSPF processes which 
each simulate a finite portion of the watershed.  HSPF has two types of operations that 
simulate the land surface, Pervious Land Segments (PERLND) and Impervious Land 
Segments (IMPLND).  These two land segment processes are frequently linked to Reach 
 78
Segment Operations (RCHRES), which simulate the flow of water in rivers.  Water 
flowing across the land to rivers is intrinsic to the movement of water in the environment 
and is the driving force in non-point source pollution.  It is, therefore, an understandable 
choice for the elemental structure of an HSPF model. 
Many decisions beyond this basic structure are made by the modeler.  These 
decisions eventually influence how the overall character of the watershed is displayed.  
These choices include many items, but the degree to which the model is lumped or 
distributed is of paramount importance.  The terms “Lumped” and “Distributed” have 
explicit connotations when describing mathematical models, see Chapter Two.  The 
designation of a model with one of these two categories involves both the spatial scale 
and techniques used for the solution.  HSPF and the processes within the model are 
“Lumped.”  HSPF does not consider the partial derivatives of processes with respect to 
space in simulations.  (Singh and Woolhiser, 2002) 
Despite  these explicit definitions, when describing HSPF model configurations, 
the terms “Lumped” and “Distributed” are often used to describe the degree to which the 
land surface and river systems have been segmented.  “Lumped” often means that large 
areas of land which may or may not have similar spatially variable properties are 
simulated as a single Land Segment.  “Distributed” often means that an attempt was 
made to segment the model so that spatially variable parameters and data are relatively 
uniform over an individual Land Segment. 
One of the motivating factors in configuring an HSPF model is the desire to 
capture the spatial variability of processes occurring on or over the land surface.  As 
explained in Chapter Three, there is significant spatial variability in precipitation over the 
Sandies and Elm watershed that is not described through the available hourly or daily 
NCDC stations.  Therefore, NEXRAD precipitation data was used for this model.  This 
 79
choice of precipitation data type is an important factor in the configuration of the HSPF 
model.  The structure of HSPF processes for land segments requires that forcing data 
such as rainfall be applied uniformly over the land segment.  HSPF processes are often 
broken down to represent an area with homogeneous land use and soil characteristics, but 
because of the structure of the HSPF model, the entire area represented by an HSPF 
Operation must also receive uniform forcing data, in this case, precipitation.  Therefore, 
even if two areas of land have identical land use, topographic, and soil characteristics, if 
they do not receive the same amount of precipitation, they must be modeled with two 
separate HSPF Operations. 
A second motivating factor in the model creation process is the overall objective 
behind the model.  The purpose of this water quality model requires that results be 
produced at specific locations along the river network for calibration of the model to 
monitored bacteria levels.  This objective requires that river segments be divided at 
locations where monitoring station exist so that model results can be directly compared 
with observed data. 
5.3.1 Watershed Delineation 
Keeping in mind both of the motivating factors in the structure of the watershed 
model, the Sandies and Elm watershed was delineated.  The subbasins were delineated on 
a small enough scale in order to capture the spatial variability of precipitation across the 
basin and with breaks at the bacteria and flow monitoring stations. 
5.3.2 River Reaches 
The underlying structure of the watershed delineation was in the physical 
locations of the stream segments as defined by the high-resolution NHD.  There were a 
total of over 2000 reach segments in the high-resolution dataset.  This number was 
excessive and was, therefore, reduced to 107 by eliminating the un-named streams from 
 80
the total.  The rationale for this is that, without any actual field data available, the named 
streams were the more important in the basin and more often contained flowing water.  
Figure 5.10 shows the high-resolution NHD streams that were used in modeling the 
Sandies and Elm watershed. 
Figure 5.10: Sandies and Elm Drainage Lines 
WRAP Hydro was then used to find the subbasin areas for each of the named 
streams in the NHD stream network within the Sandies and Elm watershed. 
5.3.3 Subbasins 
Figure 5.11 shows the subbasin delineation for the Sandies and Elm watershed.  
Once the subbasins were delineated it was noted that the watershed would need to be 
 81
broken up into two models, an upper and a lower section, to allow for an adequate 
number of land uses to be applied within each subbasin.  The reason for this is explained 
in Section 5.3.4. 
 
Figure 5.11: Sandies and Elm Watershed Delineation 
The subbasins range in size from 0.4 square kilometers to 67.0 square kilometers 
with a mean of 15.3 square kilometers in the Upper Sandies and Elm and from 0.6 square 
kilometers to 70.4 square kilometers with a mean of 19.9 square kilometers in the Lower 
Sandies. There are 107 subbasins in the Sandies and Elm watershed that are, on average, 
18 square kilometers in size, which is comparable to the approximately 124 NEXRAD 
cells across the watershed that are 16 square kilometers in size.  Therefore, the subbasin 
 82
delineation should adequately represent the spatial variability of the precipitation over the 
watershed. 
5.3.4 Land Use / Land Cover 
As described in Chapter Two, HSPF applies an Operation to a land segment, or 
land use type, even if that land segment is not spatially contiguous within the zone of the 
Operation.   The basis for this choice of the characterization of spatially discontinuous 
areas of land with a single Land Segment is associated with the process used to model 
water movement over the land surface.  HSPF processes calculate a vertical water 
balance, and if a type of land segment within a subbasin has similar land surface 
characteristics, there is no reason to consider that a water balance over an area will be 
different even if they are not connected. 
GIS data commonly contains 21 or more categories of land use / land cover, but 
HSPF models typically simulate fewer than 10 types of land use.  Reduction of total land 
use types into a coherent group is defined by both the watershed and the model focus.   
The Sandies and Elm basin is agricultural in nature and the focus of the TMDL 
study is non-point source pollution associated with the agricultural practices in the 
watershed.  The USGS Seamless raster information for land use / land cover is shown in 
Figure 5.5.  The Sandies and Elm basin includes 17 of the 21 possible land use / land 
cover types.  The total number of land use types was reduced for the HSPF model to the 
land use categories listed in Table 5.3. 
The HSPF categories were chosen by defining the major uses in the watershed 
and combining the minor uses with similar traits.  For instance, the Bare Rock and 
Quarries land use was added into the Developed land use because of the impervious 
nature of all land types included in the category.  In addition the very small percentage of 
the total watershed area represented by these land uses implies that the differences 
 83
between the grouped types are inconsequential.  The areas were further reduced to keep 
the number of categories at or below six.  HSPF has a limit to the number of operation 
sequences that can be performed from an input file, 500.  This limit, along with the 
number of delineated subbasins, restricted the number of land uses that could be applied 
to six.  An illustration of the above reclassification is shown in Figure 5.12. 
Table 5.3: Land Use Breakdown  
Seamless Land Use / Land Cover HSPF Land Use / Land Cover 
Categories Percentage Percentage
Pervious 
Categories 
Impervious 
Categories 
Light Residential 0.08% 
Heavy Residential 0.03% 
Commercial/Indust 0.27% 
BareRock/Sand/Clay 0.13% 
Quarries/StripMines 0.08% 
Rec. Grasses 0.03% 
0.63% Developed Developed 
Deciduous Forest 19.62% 
Evergreen Forest 5.36% 
Mixed Forest 0.02% 
25.00% Forest 
Shrubland 21.04% 21.04% Shrubland 
Grassland 24.27% 24.27% Grassland 
Pasture 24.79% 
Row Crops 3.46% 
Small Grains 0.30% 
28.54% Planted 
Woody Wetlands 0.09% 
Herbaceous 
Wetlands 
0.12% 
Open Water 0.31% 
0.52% Wetlands 
 
 
 84
 
Figure 5.12: Reclassification of Land Uses for HSPF Model 
ArcGIS tools were used to translate USGS land use categories into HSPF land use 
categories.  Figure 5.13 illustrates the process of calculating the amount of each land use 
type that contributes to each river segment.  Subbasin areas overlay the condensed land 
use polygons to identify the land use allocation in each.   
 
Figure 5.13: Land Use / Subbasin Intersection Illustration 
 85
The result of the application illustrated in Figure 5.13 is a polygon feature class in 
which each feature represents the area of a single land use type that contributes to a single 
river segment.  (Figure 5.14)  (Johnson, 2005) 
 
Figure 5.14: HSPF Land Uses and Subbasins 
5.3.5 Cross-Section and Outflow 
In HSPF, the outflow of water from the River Segments is modeled using a 
simple volume or stage vs. discharge relationship.  A lumped flow routing scheme is 
applied using an invariable, single valued storage function relating discharge from the 
segment to storage in the segment.  (Bicknell et al., 2001) 
The USGS historical stage-discharge information for USGS gauging station 
08175000 was downloaded from the National Water Information System (NWIS) 
 86
website.  (USGS: NWIS, 2005)  The USGS gauging station for the Sandies and Elm 
Watershed is located near Westhoff, Texas and drains 549 square miles at that point, 
which is 79.75% of the total watershed.  The historical information was evaluated for 
Width vs. Flow and Width vs. Low Flow as shown in Figure 5.15 and Figure 5.16. 
Figure 5.15: USGS Gaging Station 08175000 Historical Width versus Flow 
Distinct changes in the relationship between width and flowrate are evident in 
these figures.  A change in the slope for the USGS Gaging Station 08175000 occurs at a 
high flowrate of 3390 CFS and 219-ft width.  A low flow change in slope or break occurs 
at about 438 CFS and 50-ft width.  These flows are associated with 8.65 ft and 20 ft in 
depth respectively.  (Figure 5.17) 
0
500
1000
1500
2000
2500
3000
3500
4000
4500
0.1 1 10 100 1000 10000 100000
Flow (CFS)
Wi
dth (Ft)
Breakpoint
 87
Figure 5.16: USGS Gaging Station 08175000 Historical Width versus Low Flow 
The minimum width of the cross-section fluctuates around the 5 to 7 foot mark.  
A side-slope of 2.5:1 was estimated, which with a 50-ft width and 8.65-ft depth allowed a 
bottom width of 6.75 feet, which falls within the USGS data range.  Analysis of the 
historical data, in the above fashion, produces a cross-section at the gauging station with 
distinct breaks at certain widths and depths as depicted in Figure 5.18. 
0
50
100
150
200
250
0.1 1 10 100 1000 10000
Flow (CFS)
Wi
d
t
h (Ft)
Low flow (main 
channel) 
breakpoint
 88
Figure 5.17: USGS Gaging Station 08175000 Historical Depth versus Flow 
Figure 5.18: Historical Cross-Section at USGS Gauge 08175000 
A stage-discharge relationship needed to be defined for each reach in the entire 
river network of the Sandies and Elm watershed.  Field flow rates and survey data were 
unavailable; therefore the stage discharge relationship was derived for the whole 
0
5
10
15
20
25
30
35
0.1 1 10 100 1000 10000 100000
Flow (CFS)
Depth (
F
t)
Corresponding 
depth to 
breakpoint in high 
flow width
Corresponding depth to breakpoint
in low flow width
 
 89
watershed from the data available from the USGS gauging station.  From the historical 
cross-section and flow data the reach cross-sections were estimated in the following way. 
First a watershed drainage area to main channel flow relationship was defined.  
According to the historical data, the main channel allows 438 CFS of water flow for 549 
square miles of drainage area.  Therefore, main channel relationship is: 
Equation 5.1:  Main Channel Flow 
Main Channel Flow = 0.798 CFS/square mile 
Similarly the Lower and Upper Floodplain Flows were defined. 
Equation 5.2:  Lower Floodplain Flow 
Lower Floodplain Flow = 6.175 CFS/square mile 
Equation 5.3:  Upper Floodplain Flow 
Upper Floodplain Flow = 38.616 CFS/square mile 
 These relationships were used to define the flows for each reach in the HSPF model 
stream network. 
The bottom width of the channel was defined by dividing the 6.75 ft. bottom 
width, from the historical data, by 549 square miles.  This number was then rounded to 
the nearest 0.05 feet. 
Equation 5.4:  Bottom Width 
Bottom Width = 0.0123 feet/square mile 
From here the rest of the cross-section was defined by geometry and Manning’s 
equation. 
Equation 5.5:  Manning’s Equation 
AS
P
A
n
Q
⎥
⎥
⎦
⎤
⎢
⎢
⎣
⎡
⎟
⎠
⎞
⎜
⎝
⎛
=
2
1
3
1
49.1
  
 
 90
n: Manning’s Coefficient 
A: Cross-Sectional Area 
P: Wetted Perimeter 
S: Longitudinal Slope 
Manning’s coefficient was set to values of 0.05 for the Main Channel and 0.07 for both 
the Upper and Lower Floodplains. 
Equation 5.6:  Top Width 
Top Width = Bottom Width + (2 * Side Slope * Depth) 
The side slopes were defined by the gauge historical data cross-section using the values 
in Table 5.4 for side slopes. 
Table 5.4: Section Side Slope 
Section Side Slope 
Main Channel 2.5:1 
Lower Floodplain 7:1 
Upper Floodplain 252:1 
From these equations, an Excel spreadsheet was set up to optimize the depth using 
Manning’s equation to match the required flow and the geometric relationships defined 
above.  See tables in Appendix C for all channel cross-sections defined this way. 
5.3.6 Physical Parameter Definition 
There are a few parameters in an HSPF model that can either be defined or 
initially estimated from readily available information on the physical watershed.  The 
parameters listed in Table 5.5 were calculated using know physical parameters. 
 91
Table 5.5: HSPF Physical Parameters 
Range of Values 
Typical Possible Name Units 
Min Max Min Max 
Function of 
PWATER – PARAMETER SET 2 
LZSN Inches 3.0 8.0 2.0 15.0 Soils, Climate 
INFILT In/hr 0.01 0.25 0.001 0.50 Soils, Land Use 
LSUR Feet 200 500 100 700 Topography 
SLSUR Ft/ft 0.01 0.15 0.001 0.30 Topography 
PWATER – PARAMETER SET 4 
CEPSC Inches 0.03 0.20 0.01 0.40 Vegetation Type/Density 
UZSN Inches 0.10 1.0 0.05 2.0 Surface Soil Conditions 
NSUR None 0.15 0.35 0.05 0.50 Surface Conditions 
LZETP None 0.2 0.7 0.1 0.9 Vegetation Type/Density 
The parameters highlighted in yellow were calculated.  The parameters highlighted in 
blue were estimated and then calibrated. 
5.3.7 Length of Overland Flow Plane (LSUR) 
Length of overland flow plane (LSUR) approximates the average length of travel 
for water to reach a stream reach or any drainage path within the subbasin.  The length of 
overland flow can be estimated from the drainage density of the subbasins.  The drainage 
density is defined as the sum of all drainage path lengths divided by the area.  To find the 
drainage density ArcGIS was utilized.  All of the drainage lines in the high-resolution 
National Hydrography Dataset were used to calculate the total drainage path length, and 
that length was divided by the subbasin area to find the drainage density.   
Equation 5.7:  Overland Flow (LSUR) 
Overland Flow (LSUR) = (2*Drainage Density)
-1
 
 92
The statistics of the drainage densities calculated for the subbasins in the Upper Sandies 
and Elm and Lower Sandies are listed in Table 5.6.  Appendix E lists all of the LSUR 
values for each of the subbasins. 
Table 5.6: Drainage Density Statistics (kilometer/square kilometer) 
 Upper Sandies & Elm Lower Sandies 
Minimum 0.96 1.43 
Maximum 5.95 5.63 
Mean 2.00 2.00 
Standard Deviation 0.88 0.66 
Patton and Baker (1976) estimated the drainage density of streams in central 
Texas to be around 4.05 kilometer/square kilometer.  The drainage densities calculated 
for the Sandies and Elm watershed were, for the most part, lower than this average.  This 
could be due to the level of streams shown in the high-resolution NHD. 
5.3.8 Slope of Overland Flow Path (SLSUR) 
SLSUR was calculated using the ArcGIS to HSPF Preprocessing Methodology.  
(Johnson, 2005)  Utilizing ArcGIS Zonal Statistics and the Digital Elevation Model, the 
maximum and minimum elevations for each subbasin are calculated.  The difference in 
these elevations is then divided by the output of the ArcHydro tool, Longest Flow Path, 
for each subbasin.  This calculation gives a general estimate for the slope of the terrain 
within each subbasin. 
5.3.9 Manning’s n for Overland Flow Plane (NSUR) 
NSUR values were defined based on land use / land cover.  An average of the 
values given in EPA BASINS Technical Note 6 (US EPA, 2000) for different land uses 
was applied to the six land uses defined for the Sandies and Elm watershed.  Table 5.7 
 93
lists the NSUR parameters used for the Sandies and Elm watershed along with the 
associated land use description and range from Technical Note 6.  (US EPA, 2000) 
Table 5.7: Sandies & Elm NSUR Parameters 
Land Use Technical Note 6 Description Tech. Note 6 Range NSUR 
Developed Normal Roads and parking lots 0.10 0.10 
Forest Heavy turf, forest litter 0.30 – 0.45 0.35 
Shrubland Moderate turf / pasture (high) 0.20 – 0.30 0.30 
Grassland Moderate turf / pasture (low) 0.20 – 0.30 0.20 
Planted Rough fallow / cultivated 0.20 – 0.30 0.25 
Wetlands Same as river bed  0.05 
5.3.10 Lower Zone Evapotranspiration (LZETP) 
LZETP is an index to the lower zone evapotranspiration.  It is a coefficient that 
defines the opportunity for evapotranspiration.  The LZETP was estimated from the land 
use value ranges given in EPA BASINS Technical Note 6.  (US EPA, 2000)  Values were 
applied on a monthly basis with land use / land cover type.  See Table 5.8 for monthly 
values of LZETP for each land use and month. 
Table 5.8: LZETP Monthly Values per Land Use 
LZETP 
Land Use 
Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec 
Developed 0.05 0.05 0.10 0.15 0.20 0.25 0.35 0.30 0.25 0.20 0.15 0.10 
Forest 0.15 0.15 0.30 0.40 0.50 0.60 0.70 0.80 0.60 0.50 0.40 0.30 
Shrubland 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.45 0.40 0.30 0.20 
Grassland 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.45 0.40 0.30 0.20 
Planted 0.15 0.15 0.30 0.40 0.50 0.60 0.70 0.70 0.55 0.40 0.30 0.20 
Wetlands 0.20 0.20 0.40 0.50 0.60 0.70 0.80 0.90 0.80 0.70 0.50 0.30 
 94
5.3.11 Lower Zone Nominal Soil Moisture Storage (LZSN) 
LZSN is related to both precipitation patterns and soil characteristics of a 
watershed.  Technical Note 6 (US EPA, 2000) provides an initial estimate calculation 
method for the LZSN by Viessman, et al. (1989).  Viessman et al. estimated the LZSN to 
be one-quarter of the mean annual rainfall plus four inches for arid to semi-arid regions, 
or one-eighth annual mean rainfall plus four inches for coastal, humid, or subhumid 
climates.  But, it is noted that this formula tends to estimate values higher than what is 
seen in final calibrated models.  A Viessman calculation estimates LZSN at 8.1 to 12.3 
inches for the Sandies and Elm watershed. 
5.3.12 Index to Mean Soil Infiltration Rate (INFILT) 
INFILT is the mean soil infiltration rate in inches per hour.  It is the parameter 
that effectively controls the overall division of the available moisture from precipitation 
(after interception – see section below) into surface and subsurface flow.  Since INFILT 
is not a maximum rate nor an infiltration capacity term, its values are normally much less 
than published infiltration rates found in literature.  (US EPA, 2000)  INFILT is primarily 
based on soil characteristics and ranges of values have been related to the SCS hydrologic 
soil groups.  See Table 5.9. 
Table 5.9: SCS Hydrologic Soil Group Characteristics 
Hydrologic 
Group 
Description 
A 
High infiltration rates.  Soils are deep, well drained to excessively 
drained sands and gravels 
B 
Moderate infiltration rates.  Deep and moderately deep, moderately well 
and well-drained soils with moderately course textures. 
C 
Slow infiltration rates.  Soils with layers impeding downward movement 
of water, or soils with moderately fine or fine textures. 
D Very slow infiltration rates.  Soils are clayey, have a high water table. 
 95
5.3.13 Rainfall Vegetation Interception (CEPSC) 
CEPSC is the amount of precipitation that is captured by vegetative cover and 
never reaches the land surface, in inches.  Values for maximum interception range from 
0.10 to 0.25.  Monthly values are normally used for interception rates in largely 
agricultural areas.  (US EPA, 2000)  Table 5.10 presents monthly interception rates used 
for the Sandies and Elm watershed model. 
Table 5.10: Monthly Interception Rates (Inches) 
CEPSC 
Land Use 
Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec 
All 0.00 0.00 0.02 0.04 0.08 0.10 0.10 0.10 0.10 0.05 0.03 0.01 
5.3.14 Nominal Upper Zone Soil Moisture Storage (UZSN) 
UZSN is the nominal upper zone soil moisture storage, in inches.  US EPA 
Technical Note 6 provides an estimate method by Donigian and Davis (1978) for an 
initial UZSN estimate.  Donigian and Davis calculate UZSN to be 0.06 of LZSN for 
steeply sloping terrain or light vegetative cover; 0.08 of LZSN for moderately sloping 
terrain or moderate vegetative cover; and 0.14 of LZSN for heavy vegetative cover.  The 
initial estimate of UZSN, by this definition, would be from 0.50 to 1.72, given the above 
LZSN range of 8.1 to 12.3. 
This chapter has explained the development of the model from the known 
physical aspects.  The HSPF model of the Sandies and Elm watershed requires this 
information for model calibration.  The next chapter explains the process and results of 
the calibration of those parameters which can not be determined based on available data 
or known physical processes. 
 96
Chapter 6 Model Calibration 
The calibration of the Sandies and Elm HSPF model followed the standard model 
calibration procedures described in the HSPF Application Guide (Donigian et al., 1984).  
The following model calibration explanation focuses exclusively on the HSPF hydrologic 
parameters; water quality parameters are not discussed. 
6.1 PARAMETER ESTIMATION 
Calibration of an HSPF model is an iterative process of parameter estimation 
comparison and refinement.  This approach is required for parameters that cannot be 
uniquely determined from known physical characteristics of the watershed.  Simulated 
model flow and observed flow data are compared so that the undetermined parameters 
can be calibrated to the observed hydrologic data.  Fortunately, a minority of HSPF 
parameters fall into this category.  Table 6.1 below lists the PWATER parameters that 
can be varied during model calibration, normal ranges of these parameters, and possible 
sources for initial parameterization.  A number of these parameters initial estimates were 
discussed in the previous chapter. 
The result of a model calibration is a set of parameters that produce the best 
overall agreement between simulated and observed values during the calibration period 
based on standard statistical measures. 
 97
Table 6.1: HSPF PWATER Parameters (US EPA, 2000) 
Range of Values 
Typical Possible Name Units 
Min Max Min Max 
Function of Comment 
PWATER – PARAMETER SET 2 
FOREST None 0.0 0.50 0.0 0.95 Forest Cover Only when SNOW is active 
LZSN Inches 3.0 8.0 2.0 15.0 Soils, Climate Calibration 
INFILT In/hr 0.01 0.25 0.001 0.50 Soils, Land Use Calibration 
LSUR Feet 200 500 100 700 Topography Estimate from topography, GIS 
SLSUR Ft/ft 0.01 0.15 0.001 0.30 Topography Estimate from topography, GIS 
KVARY 1/inches 0.0 3.0 0.0 5.0 
Baseflow Recession 
Variation 
Used when recession rate varies with 
groundwater 
AGWRC None 0.92 0.99 0.85 0.999 Baseflow Recession Calibration 
PWATER – PARAMETER SET 3 
PETMAX Deg. F 35.0 45.0 32.0 48.0 Climate, Vegetation Only when SNOW is active 
PETMIN Deg. F 30.0 35.0 30.0 40.0 Climate, Vegetation Only when SNOW is active 
INFEXP None 2.0 2.0 1.0 3.0 Soils Variability Default to 2.0 
INFILD None 2.0 2.0 1.0 3.0 Soils Variability Default to 2.0 
DEEPFR None 0.0 0.20 0.0 0.50 Geology, GW Recharge Accounts for subsurface losses 
BASETP None 0.0 0.05 0.0 0.20 Riparian Vegetation Direct ET from riparian vege. 
AGWETP None 0.0 0.05 0.0 0.20 Marsh Wetland Extent Direct ET from shallow GW 
PWATER – PARAMETER SET 4 
CEPSC Inches 0.03 0.20 0.01 0.40 Vegetation Type/Density Monthly values usually used 
UZSN Inches 0.10 1.0 0.05 2.0 Surface Soil Conditions Near surface retention 
NSUR None 0.15 0.35 0.05 0.50 Surface Conditions Monthly values used for Ag. 
INTFW None 1.0 3.0 1.0 10.0 Soils, Topography Calibration 
IRC None 0.5 0.7 0.3 0.85 Soils, Topography Start with 0.7 then adjust 
LZETP None 0.2 0.7 0.1 0.9 Vegetation Type/Density Calibration 
 98
6.2 HSPF STANDARD CALIBRATION 
A classic HSPF calibration includes a comparison of flow for annual, seasonal, 
and monthly time intervals, individual storm events, and flow duration curves.  These 
different intervals are all considered in order to ensure proper calibration of the 
hydrological parameters of the model.  This weight of evidence approach is taken 
because no single method has been widely accepted as being capable of creating an 
acceptable model.  A traditional hydrologic calibration involves the successive 
examination of the following four components of the watershed hydrology in the 
subsequent order. 
1) Annual water balance 
2) Seasonal and monthly flow volumes 
3) Baseflow 
4) Storm events 
Simulated and observed values for reach characteristics are examined and critical 
parameters are adjusted to attain acceptable levels of agreement. 
6.2.1 Annual Water Balance 
The annual water balance is: 
Equation 6.1:  Annual Water Balance 
Runoff =Precipitation – Evapotranspiration – Deep Infiltration – Change in Soil Moisture 
An HSPF model requires input of forcing data, in this case precipitation and 
evaporation, to drive the hydrology of the watershed and the model.  A list, description, 
and range of the more important HSPF parameters for an annual water balance are shown 
in Table 6.2. 
 
 99
Table 6.2: Annual Water Balance Calibration Parameters 
Parameter Description Range 
LZSN Lower zone soil moisture storage (inches) 3.00 – 8.00 
LZETP Vegetation evapotranspiration index (dimensionless) 0.20 – 0.70 
INFILT 
Infiltration index for the division of surface and 
subsurface flow (inches/hour) 
0.01 – 0.25 
UZSN Upper zone soil moisture storage (inches) 0.10 – 1.00 
DEEPFR 
Fraction of groundwater inflow to deep recharge 
(dimensionless) 
0.00 – 0.20 
LZSN and LZETP affect evapotranspiration by influencing the amount of 
moisture available for that process.  LZSN and INFILT affect the amount of precipitation 
that percolates.  UZSN affects annual discharge volumes because of its influence on 
individual storm events.  DEEPFR is used to represent loss from the annual water balance 
whenever there are losses that are measured at the flow gauge, such as recharge. 
6.2.2 Seasonal and Monthly Distribution 
The next step in hydrologic calibration is the seasonal or monthly distribution of 
runoff which is adjusted with the INFILT, AGWRC, and KVARY parameters.  Seasonal 
distribution is accomplished by INFILT by dividing the precipitation between surface 
runoff, interflow, and groundwater storage.  By increasing INFILT the immediate surface 
runoff, which includes interflow, is reduced and increases the groundwater storage.  By 
increasing the groundwater storage this causes a delay in the time required for water to be 
reach the stream, which therefore moves water volume between seasons.  This often 
means transferring the surface water from storm events to low-flow periods during the 
dry season.  The shape of this groundwater recession, baseflow discharge, is controlled 
by AGWRC and KVARY.  A list, description, and range of the parameters important in 
seasonal and monthly distribution are shown in Table 6.3. 
 
 100
Table 6.3: Seasonal and Monthly Distribution Parameters 
Parameter Description Range 
INFILT 
Infiltration index for the division of surface and 
subsurface flow (inches/hour) 
0.01 – 0.25 
AGWRC Groundwater recession rate (per day) 0.92 – 0.99 
KVARY Index for nonlinear groundwater recession 0.00 – 3.00 
AGWRC is calculated as the rate of baseflow on one day divided by the baseflow 
on the previous day, therefore AGWRC is the parameter that controls the flow of water 
from groundwater storage into the stream.  The KVARY index allows the model to have 
a non linear recession so that the slope of recession can be changed as a function of the 
groundwater gradient.  KVARY is usually set to zero unless the observed flows show a 
definite seasonal change in recession rate. 
6.2.3 Storm Event Calibration 
This is the final step in hydrologic calibration of the HSPF model after the annual 
water balance and seasonal and monthly distributions have been satisfied.  Calibration to 
selected storm events was completed using the following two parameters, INTFW and 
IRC.  A list, description, and range of the parameters important in storm calibration are 
shown in Table 6.4. 
Table 6.4: Seasonal and Monthly Distribution Parameters 
Parameter Description Range 
INTFW Interflow inflow parameter (dimensionless) 1.00 – 3.00 
IRC Interflow recession parameter (per day) 0.50 – 0.70 
Both INTFW and IRC are used to fine-tune the shape of the hydrograph for a 
better fit with observed data.  The parameters are first estimated from past experience and 
other studies in the area, and then adjusted during calibration.  Adjustments to INFILT 
 101
can also be made to improve simulation, but should be minor to prevent disruption in 
annual and monthly calibration results. 
6.2.4 Specific Calibration Rules and Procedures 
The previous sections described the calibration procedure in general.  Below are 
rules that guide specific calibration procedure for parameters in the PERLND module. 
1) The infiltration exponent (INFEXP) and infiltration max to mean ratio (INFILD) 
was set to 2.0. 
2) IRC, AGWRC, and KVARY were based on calculated stream flow recessions 
from recorded data. 
3) The length of surface runoff (LSUR), slope of surface runoff (SLSUR), and 
Manning’s roughness for the surface runoff (NSUR) was based on the physical 
characteristics in the watershed. 
4) Base evapotranspiration (BASETP) and active groundwater evapotranspiration 
(AGWETP) was initially set to zero. 
5) DEEPFR was initially be set to zero, but was increased to provide a good water 
balance when all other parameters have been set. 
6) The number one priority in this calibration process was the accurate simulation of 
the annual flow volumes to within a ten percent margin of observed flows. 
6.2.5 Calibration Targets 
The following specific comparisons of simulated versus observed flow were 
completed: 
1. Annual Water Volume (inches) 
2. Seasonal Distribution (cfs) 
3. Monthly Distribution (cfs) 
4. Flow Duration Curve (cfs) 
 102
The simulated and observed flows were divided into categories and then 
evaluated according to defined criteria so that specific flow ranges and events could be 
targeted.  The calibration criteria are shown in Table 6.5 below.  Most, but not all, of the 
criteria need to be met to classify the model as properly calibrated. 
Table 6.5: HSPF Calibration Criteria (adapted from Donigian et al., 1984) 
Calibration Target 
Simulated
(-) 
Observed 
(-) 
Difference 
(%) 
Criteria 
(%) 
Meets 
Criteria* 
Total (in)    10  
10% Highest (cfs) 10 
25% Highest (cfs)    15  
50% Lowest (cfs) 15 
25% Lowest (cfs)    15  
10% Lowest (cfs) 15 
Storm Volume (In)    20  
Average Storm Peak (cfs) 15 
Spring Volume (In)    15  
Summer Volume (In) 20 
Fall Volume (In)    15  
Winter Volume (In) 10 
* Excellent = more than 5% below criteria required 
 Good = less than Criteria required 
 Ok = less than 5% above criteria required 
 Poor = greater than 5% above criteria required 
6.3 SANDIES AND ELM CALIBRATION 
The model period for the Sandies and Elm watershed was six years and included 
years 1999 thru 2004.  Model calibration resulted in parameter values that produced the 
best overall agreement between measured and modeled values throughout the calibration 
period. 
The calibration process included the comparison of annual, seasonal, and monthly 
values as well as individual storm events.  Additionally, both simulated and observed 
 103
stream flow data were analyzed on a frequency basis and the resulting flow duration 
curves were compared to assess model conformity over the full range of storm 
occurrences.  All of these comparisons were performed to ensure a proper calibration of 
hydrologic parameters.  
Calibration of the Sandies and Elm watershed was atypical in the respect that the 
seasonal and annual water volumes were, for the most part, dependent on large storm 
events.  The monthly flow volumes were also almost completely dependent on single 
storm flow values.  The watershed system has so much flow variability that if the 
precipitation input was incorrectly estimated, even by a few percent, the flow response 
was incorrect and therefore the monthly, and perhaps seasonal, flow volumes were 
wrong. 
6.3.1 Calibration Period 
The full five year calibration of the model was very poor, as seen in Table 6.6.  
The main reason for the differences between simulated and observed data is that the flow 
in the Sandies and Elm watershed is defined by the large storm events and is therefore 
highly dependent on accurate precipitation data.  The NEXRAD data, which was used for 
precipitation input, was missing for August 2000 to November 2000, a number of the 
large storm events were missed in early 2003, and storm intensity was undervalued in late 
2003 through most of 2004.  A data comparison of each of these missing storms can be 
seen in Appendix D. 
As shown in Appendix D and Figure 6.1 the sequence of accurate precipitation
1
 
runs from January 2000 through October 2000 and April 2001 through November 2002.  
                                                 
1
 A comparison of NCDC Cheapside station daily gauge precipitation against the NEXRAD precipitation 
in the vicinity of the gauge was completed for years 2000 through 2004.  If the storm precipitation values 
were within 20% of each other then the storm was deemed good, else it was deemed no good.  (See 
Appendix D for more information) 
 104
These are the sections in which the model was externally calibrated.  1999 was set aside 
for model internal calibration. 
When only the period from April 2001 through November 2002 was evaluated the 
model calibration criteria was good for the annual volume and flow duration 
comparisons.  The seasonal flow volumes were poor overall, because they depend so 
greatly on single storms.  (See Table 6.7 and Figure 6.3 below) 
Table 6.6: HSPF Calibration Criteria Results - Full Calibration Period 
Calibration Target 
Simulated
(-) 
Observed 
(-) 
Difference 
(%) 
Criteria 
(%) 
Meets 
Criteria 
Total (in) 10.56 15.60 32.3 10 Poor 
10% Highest (cfs) 69.60 192.00 63.8 10 Poor 
25% Highest (cfs) 20.00 33.00 39.4 15 Poor 
50% Lowest (cfs) 12.80 14.00 8.6 15 Excellent 
25% Lowest (cfs) 7.20 5.40 33.3 15 Poor 
10% Lowest (cfs) 3.50 2.30 52.2 15 Poor 
Storm Volume (In) 9.00 14.00 35.7 20 Poor 
Average Storm Peak (cfs) 831.00 1,344.00 38.2 15 Poor 
Spring Volume (In) 1.32 2.14 38.3 15 Poor 
Summer Volume (In) 4.37 2.90 50.6 20 Poor 
Fall Volume (In) 3.33 7.44 55.2 15 Poor 
Winter Volume (In) 1.54 3.11 50.6 10 Poor 
 
 105
Table 6.7: HSPF Calibration Criteria Results – Shortened Calibration Period 
Calibration Target 
Simulated
(-) 
Observed 
(-) 
Difference 
(%) 
Criteria 
(%) 
Meets 
Criteria 
Total (in) 6.85 7.37 7.1 10 Good 
10% Highest (cfs) 197.00 189.00 4.2 10 Excellent 
25% Highest (cfs) 23.40 22.00 6.4 15 Excellent 
50% Lowest (cfs) 11.10 11.00 0.9 15 Excellent 
25% Lowest (cfs) 5.50 4.60 19.6 15 OK 
10% Lowest (cfs) 1.40 1.70 17.6 15 OK 
Storm Volume (In) 6.75 7.26 7.1 20 Excellent 
Average Storm Peak (cfs) 2,569.00 3,228.00 20.4 15 Poor 
Spring Volume (In) 0.44 0.29 52.2 15 Poor 
Summer Volume (In) 3.44 1.67 106.1 20 Poor 
Fall Volume (In) 2.60 5.01 48.1 15 Poor 
Winter Volume (In) 0.37 0.39 7.4 10 Good 
Because the fluctuation in flow at the gauge can change by three orders of 
magnitude during one storm event, it is difficult to obtain a perfect fit for each storm 
event in the simulation.  This difference becomes very apparent in the monthly/seasonal 
flow data, where a slight visual difference in the daily flow on the logarithmic scale 
translates into significant error in the monthly cumulative analysis.  See Figure 6.3. 
This translates into a flow at or below 1.7 cfs.  This was considered acceptable 
given first that the watershed has extreme flow variability and second that the calculated 
7Q2, at which all water quality regulations cease to be applied, is 1.1 cfs.  See Figure 6.4. 
  A complete listing of calibrated parameters for each subbasin is listed in 
Appendix E.
 106
 
Figure 6.1: Daily Flow
GoodGood
Model 
Internal 
Calibration 
Period 
 107
 
Figure 6.2: Daily Flow Calibration Period 
 108
  
Figure 6.3: Monthly Cumulative Flow - Calibration Period 
 109
 
Figure 6.4: Daily Flow Duration Curve - Calibration Period 
7Q2 = 1.1 CFS – Water Quality Regulations Are No Longer Applicable 
 110
Chapter 7 Conclusions and Recommendations 
There are two main purposes for mathematical modeling.  The first is to 
characterize situations or predict conditions for which no observed data exists.  The 
second is to lend insight into understanding the processes that are important in a system.  
Modeling for these purposes allows engineers and managers to analyze the factors that 
affect a system’s response and make informed decisions in planning for future conditions. 
The overall objective of this project was to develop a watershed model of the 
Sandies and Elm basin.   During the course of the model’s development, multiple 
observations and conclusions were made concerning the structure of Hydrologic 
Simulation Program – FORTRAN (HSPF), its weaknesses, its strengths, and its future. 
7.1 SPATIAL PRECIPITATION DATA FINDINGS 
HSPF was chosen because of its ability to simulate non-point pollution discharge 
from agricultural areas on a continuous time frame.  The classic source of precipitation 
forcing data, the National Climatic Data Center, lacked enough gage precipitation 
stations with data during the time span required for calibration.  Alternate data sources 
were reviewed as sources of accurate forcing data for the model.   
This underlying motivational study uncovered a variety of weaknesses in the 
precipitation sources currently available.  Although precipitation gauging stations, such 
as those run by the NCDC, are accurate for the point at which they are gauging, they are 
unable to truly capture the spatial nature of precipitation at their current level of spatial 
distribution.  NEXRAD captures the spatial characteristics of precipitation, but the 
intensity of storms is not always accurately interpreted.  DAYMET, which spatially 
interpolates daily rain gauge data, also has the same problems as other interpolation 
 111
methods of point precipitation data in convective, semi-arid, regions, in that it also does 
not truly capture the spatial nature of rain on the watershed scale. 
But, despite the flaws in all of these systems, it is important to note that weather 
related phenomena are both spatial and temporal in nature, and if the goal of a  model is 
to accurately capture the effects of precipitation on the landscape, it must allow for both 
aspects of the nature of weather. 
7.2 HSPF 
Hydrologic Simulation Program – FORTRAN (HSPF) is recommended by the 
Environmental Protection Agency for hydrologic and water quality watershed process 
modeling because of its ability to calculate multiple water quality constituents 
continuously in an unsteady flow environment.  These characteristics make HSPF an 
ideal model for many different types of watersheds across the United States and the 
world.  But, despite these advantages, HSPF does not adapt well to geo-spatial 
complexity, especially when that complexity comes in the form of precipitation or other 
meteorological data. 
The choice of NEXRAD as the precipitation forcing data was an important factor 
in the configuration of the HSPF model.  HSPF processes are often partitioned to 
represent an area with homogeneous land use, soil, and topographic characteristics.  But, 
because of the structure of the HSPF model, the entire area represented by an HSPF 
Operation must also receive uniform forcing data, in this case precipitation.  Therefore 
each area with unique meteorological data must be described by a separate HSPF 
Operation.  The coded structure of HSPF only allows for a total of 500 Operations within 
one model.  This maximum number of Operations limits the ability of HSPF to adapt in a 
world where the spatial classifications of the physical characteristics in and of a 
watershed are continuously becoming defined at a higher resolution.  Because of this 
 112
limitation, HSPF is hindered in its ability to advance research in hydrologic modeling 
given the readily accessible spatial and temporal data now available. 
7.3 HSPF FUTURE 
The reason for a TMDL study is two-fold.  First, it is to substantiate to both the 
agencies and the stakeholders that the assumption that the problems that have been 
measured are indeed created by non-point source pollution.  Second, it is to persuade the 
stakeholders that the best management practices suggested are in their best interest and 
will have an effect to the greater good. 
The vision perceived for the future of non-point source pollution water quality 
modeling is to apply the “raindrop drainage model”, as described in Chapter Four of Arc 
Hydro: GIS for Water Resources (Maidment, 2002), to parcel level resolution landscape 
data, so that known factors can be applied. 
During the course of this study a survey was conducted of each stakeholder who 
wished to participate.  The survey covered their current number of stock and management 
and grazing practices.  Currently, HSPF only allows this information to be utilized on a 
percentage basis.  For example, the average subbasin in this, rather distributed, HSPF 
model is 16 square kilometers (approximately 4000 acres).  The majority of the farms in 
the area are between 50 and 100 acres.  (USDA: NASS, 2005)  This data can only be 
applied, in the current HSPF format, as an average across the subbasin.  The ability to 
apply this type of information accurately would improve modeling capabilities and 
provide better direct correlation between individual agricultural practices and water 
quality.  A rancher, who can visually see the connection between the density of animals 
and practice effects per parcel in his area to the level of river pollution in that same area, 
may be more willing to undertake the suggested best management practices. 
 113
To this end, GIS should take an even greater role in the future of watershed 
modeling than it currently does.  GIS is currently used to provide the data information on 
the front end and sometimes the output information on the back end, but during the 
intervening time the information is taken out of the GIS environment and placed in a 
computer program with no real spatial interpretation of the data.  This creates a model in 
which a great many parameters are lumped together due to the nature of the program. 
The development of GIS and the spatial data that has become and is continuing to 
become available has induced an environment for watershed hydrologic modeling which 
justifies model restructuring.  The true spatial interactions in nature should be taken into 
account in modeling.  A watershed is defined, not only by it land use, but also by its place 
in the world.  The climate, soils, topography, and history all combine to create an 
extremely varied and unique watershed character.  No lumped model could truly 
represent a watershed in all its complexities.  The spatial differences that define one 
watershed from another also define that watershed’s response to precipitation, land use 
changes, and pollution.  To truly understand the consequences of decisions and 
environmental changes made in a watershed on the ecosystem, a more complete 
understanding of the processes and interactions in nature must be undertaken.  The recent 
progress in the spatial resolution of the characteristic composition of a watershed has 
allowed water resource scientist and engineers to begin to understand the changes in a 
watershed’s response to anthropogenic and climatological changes. 
The study of the physical world has been transformed through the use of 
Geographic Information Systems.  It has enhanced analysis of hydrologic systems by 
allowing more detailed representation and modeling of topography, soils, and vegetative 
data.  GIS can display many things in great physical detail, for example a 1-second DEM 
grid displays elevations at more than 1,000 locations per square kilometer.  This 
 114
increased level of detail encourages the idea that simulating at a million points in a 
watershed is better than at a few hundred or a thousand locations. This is too simplistic.  
(HydroComp, 2006a) 
The accuracy of a model depends on many things:  knowledge of the underlying 
processes, accurate as well as precise data, and a modeler’s skill and experience in 
calibrating model parameters from available watershed data.  But, what it should not 
depend on is the limits of the modeling program. 
The new spatially defined model should be, in essence, a digital watershed.  It 
should be created as multiple layers that have interactive processes in and between 
themselves.  First, an atmospheric layer that is composed of precipitation, evaporation, 
temperature, wind, cloud cover, and moisture content should act as the topmost forcing 
layer.  Second, the land surface layer made up of parcels, land use, vegetation, 
topography, and surface water will be the layer in which human and nature interact.  
Third is the sub-terrain layer, in which the archives of the history of the watershed are 
kept, will encompass the soils, water table, aquifers, and bedrock. 
Within this layered system would be a storehouse for the development of the 
myriad of relationships and processes that occur between the layers.  I foresee one day 
not only gaining an understanding on the response of a watershed to the weather, but also 
achieving a much greater knowledge and appreciation of the effects that changes in the 
watershed has on the climate. 
7.4 A WORD OF CAUTION 
The use of detailed spatial information could lend an element of precision that is 
not real and dupe an unwary modeler into an overconfidence in the robustness of the 
model.  A model is only as good as its individual parts.  There is incredible complexity in 
nature; the interactions within Her are so amazing as to appear simple in their beauty.  
 115
These spatial improvements in modeling are suggested not because they are, in any way, 
more accurate than the lumped models available today, but rather, because they will 
highlight the gaps in our knowledge and allow for advances in learning about the 
complex process and spatial interactions of nature.   
 116
Appendix A:  Convective Set Spatial Interpretation of Precipitation 
JANUARY 27, 2000 
NCDC Missing Stations:  New Braunfels Municipal AP 
USGS Gage Flow Day Before: 5.2 cfs Day After: 27.9 cfs 
NEXRAD  Minimum: 0.11 in. Maximum: 1.35 in.
NCDC  Minimum: 0.12 in. Maximum: 0.76 in. 
Convective Cells: Number: 0 Size: NA
Scale (hundredth inch) 
 
Figure A.1:  NEXRAD January 27, 2000 
 
 117
 
Figure A.2:  NCDC Gage IDW Interpolation January 27, 2000 
 
Figure A.3:  DAYMET Gage Interpolation January 27, 2000 
 118
FEBRUARY 23, 2000 
NCDC Missing Stations:  Kingsbury and New Braunfels Municipal AP 
USGS Gage Flow Day Before: 6.2 cfs Day After: 214 cfs 
NEXRAD  Minimum: 0.28 in. Maximum: 2.98 in.
NCDC  Minimum: 0 in. Maximum: 2.16 in. 
Convective Cells: Number: 2 Size: 10 km.
Scale (hundredth inch) 
 
Figure A.4:  NEXRAD February 23, 2000 
 
 119
 
Figure A.5:  NCDC Gage IDW Interpolation February 23, 2000 
 
Figure A.6:  DAYMET Gage Interpolation February 23, 2000 
 120
MARCH 11, 2000 
NCDC Missing Stations:  Kingsbury and New Braunfels Municipal AP 
USGS Gage Flow Day Before: 6.1 cfs Day After: 20 cfs 
NEXRAD  Minimum: 0 in. Maximum: 5.2 in.
NCDC  Minimum: 0 in. Maximum: 0.18 in. 
Convective Cells: Number: 1 Size: 10 km.
Scale (hundredth inch) 
 
Figure A.7:  NEXRAD March 11, 2000 
 
 121
 
Figure A.8:  NCDC Gage IDW Interpolation March 11, 2000 
 
Figure A.9:  DAYMET Gage Interpolation March 11, 2000 
 122
APRIL 23, 2001 
NCDC Missing Stations:  New Braunfels Municipal AP 
USGS Gage Flow Day Before: 9.8 cfs Day After: 26 cfs 
NEXRAD  Minimum: 0.15 in. Maximum: 3.29 in.
NCDC  Minimum: 0 in. Maximum: 2.04 in. 
Convective Cells: Number: 3 Size: 5 km.
Scale (hundredth inch) 
 
Figure A.10:  NEXRAD April 23, 2001 
 
 123
 
Figure A.11:  NCDC Gage IDW Interpolation April 23, 2001 
 
Figure A.12:  DAYMET Gage Interpolation April 24, 2001 
DAYMET showed no rain for April 23, 2001.  April 24, 2001 is shown instead. 
 124
MAY 13, 2004 
NCDC Missing Stations:  Nixon 
USGS Gage Flow Day Before: 33 cfs Day After: 640 cfs 
NEXRAD  Minimum: 0 in. Maximum: 2.16 in.
NCDC  Minimum: 0 in. Maximum: 1.64 in. 
Convective Cells: Number: 1 Size: 10 km.
Scale (hundredth inch) 
 
Figure A.13:  NEXRAD May 13, 2004 
 
 125
 
Figure A.14:  NCDC Gage IDW Interpolation May 13, 2004 
DAYMET data is not available for 2004. 
 126
JUNE 10, 2000 
NCDC Missing Stations:  New Braunfels Municipal AP 
USGS Gage Flow Day Before: 39 cfs Day After: 420 cfs 
NEXRAD  Minimum: 0.88 in. Maximum: 5.5 in.
NCDC  Minimum: 0.58 in. Maximum: 2.85 in. 
Convective Cells: Number: 2 Size: 10 km.
Scale (hundredth inch) 
 
Figure A.16:  NEXRAD June 10, 2000 
 
 127
 
Figure A.17:  NCDC Gage IDW Interpolation June 10, 2000 
 
Figure A.18:  DAYMET Gage Interpolation June 10, 2000 
 
 128
JULY 31, 2000 
NCDC Missing Stations:  New Braunfels Municipal AP 
USGS Gage Flow Day Before: 1.8 cfs Day After: 1.7 cfs 
NEXRAD  Minimum: 0 in. Maximum: 2.92 in.
NCDC  Minimum: 0 in. Maximum: 0.08 in. 
Convective Cells: Number: 26 Size: 5 km.
Scale (hundredth inch) 
 
Figure A.19:  NEXRAD July 31, 2000 
 
 129
 
Figure A.20:  NCDC Gage IDW Interpolation July 31, 2000 
 
Figure A.21:  DAYMET Gage Interpolation July 31, 2000 
 130
AUGUST 31, 2001 
NCDC Missing Stations:  Falls City 4WNW, Karnes City, and New Braunfels MAP 
USGS Gage Flow Day Before: 174 cfs Day After: 25,900 cfs 
NEXRAD  Minimum: 0.77 in. Maximum: 9.17 in.
NCDC  Minimum: 0.32 in. Maximum: 8.3 in. 
Convective Cells: Number: 0 Size: NA
Scale (hundredth inch) 
 
Figure A.22:  NEXRAD August 31, 2001 
 
 131
 
Figure A.23:  NCDC Gage IDW Interpolation August 31, 2001 
 
Figure A.24:  DAYMET Gage Interpolation August 31, 2001 
 132
SEPTEMBER 22, 2001 
NCDC Missing Stations:  Falls City 4WNW, Karnes City, and New Braunfels MAP 
USGS Gage Flow Day Before: 21 cfs Day After: 18 cfs 
NEXRAD  Minimum: 0 in. Maximum: 1.72 in.
NCDC  Minimum: 0.02 in. Maximum: 0.75 in. 
Convective Cells: Number: 1 Size: 10 km.
Scale (hundredth inch) 
 
Figure A.25:  NEXRAD September 22, 2001 
 
 133
 
Figure A.26:  NCDC Gage IDW Interpolation September 22, 2001 
 
Figure A.27:  DAYMET Gage Interpolation September 22, 2001 
 134
OCTOBER 25, 2003 
NCDC Missing Stations:  Nixon 
USGS Gage Flow Day Before: 5 cfs Day After: 15 cfs 
NEXRAD  Minimum: 0 in. Maximum: 4.47 in.
NCDC  Minimum: 0 in. Maximum: 0 in. 
Convective Cells: Number: 1 Size: 5 km.
Scale (hundredth inch) 
 
Figure A.28:  NEXRAD October 25, 2003 
 
 135
 
Figure A.29:  NCDC Gage IDW Interpolation October 25, 2003 
 
Figure A.30:  DAYMET Gage Interpolation October 25, 2003 
 136
NOVEMBER 17, 2003 
NCDC Missing Stations:  Nixon 
USGS Gage Flow Day Before: 6.8 cfs Day After: 8.5 cfs 
NEXRAD  Minimum: 0.13 in. Maximum: 4.0 in.
NCDC  Minimum: 0.03 in. Maximum: 5.3 in. 
Convective Cells: Number: 1 Size: 10 km.
Scale (hundredth inch) 
 
Figure A.31:  NEXRAD November 17, 2003 
 
 137
 
Figure A.32:  NCDC Gage IDW Interpolation November 17, 2003 
 
Figure A.33:  DAYMET Gage Interpolation November 17, 2003 
 138
DECEMBER 12, 2002 
NCDC Missing Stations:  Nixon 
USGS Gage Flow Day Before: 1050 cfs Day After: 1780 cfs 
NEXRAD  Minimum: 0.26 in. Maximum: 3.71 in.
NCDC  Minimum: 0 in. Maximum: 1.8 in. 
Convective Cells: Number: 1 Size: 5 km. 
Scale (hundredth inch) 
 
Figure A.34:  NEXRAD December 12, 2002 
 
 139
 
Figure A.35:  NCDC Gage IDW Interpolation December 12, 2002 
 
Figure A.36:  DAYMET Gage Interpolation December 12, 2002 
 
 140
Appendix B:  Frontal Storm Set Spatial Interpretation of Precipitation 
JANUARY 7, 2000 
NCDC Missing Stations:  New Braunfels Municipal AP 
USGS Gage Flow Day Before: 4.4 cfs Day After: 37 cfs
NEXRAD  Minimum: 0.36 in. Maximum: 1.85 in.
NCDC  Minimum: 0.63 in. Maximum: 3.32 in. 
Convective Cells: Number: 2 Size: 5 Km
Scale (hundredth inch) 
 
Figure B.1:  NEXRAD January 7, 2000 
 
 141
 
Figure B.2:  NCDC Gage IDW Interpolation January 7, 2000 
 
Figure B.3:  DAYMET Gage Interpolation January 7, 2000 
 142
FEBRUARY 21, 2003 
NCDC Missing Stations:  Gonzales 10 SW and Nixon 
USGS Gage Flow Day Before: 219 cfs Day After: 2460 cfs
NEXRAD  Minimum: 0 in. Maximum: 0.34 in.
NCDC  Minimum: 0 in. Maximum: 1.98 in. 
Convective Cells: Number: 0 Size: NA
Scale (hundredth inch) 
 
Figure B.4:  NEXRAD February 21, 2003 
 
 
 143
 
Figure B.5:  NCDC Gage IDW Interpolation February 21, 2003 
 
Figure B.6:  DAYMET Gage Interpolation February 21, 2003 
 144
FEBRUARY 21, 2003 STORM 
There was such a large discrepancy between NEXRAD and NCDC gage interpolation 
that the entire storm was interpolated and checked. 
NCDC Missing Stations:  Gonzales 10 SW and Nixon 
USGS Gage Flow Day Before: 219 cfs Day After: 2460 cfs
NEXRAD  Minimum: 0.24 in. Maximum: 2.18 in.
NCDC  Minimum: 0 in. Maximum: 2.80 in. 
Convective Cells: Number: 4 Size: 5 Km
Scale (hundredth inch) 
  
Figure B.7:  NEXRAD 2/19/2003 thru 2/22/2003 
 
 145
 
Figure B.8:  NCDC Gage IDW Interpolation 2/19/2003 thru 2/22/2003 
Given the very significant increase in flow at the gauge from 219 cfs to 2460 cfs from 
February 20, 2003 to February 23, 2003 it is reasonable to guess that NEXRAD 
underestimated this storm rather than NCDC gauges overestimating it. 
The entire storm is not nearly as undervalued as the one day of rain in February that was 
initially evaluated.  NEXRAD still underestimates the storm by 35.8%; see Table B.1 
below, but the range, mean, and standard deviation are much closer together. 
Table B.1:  Spatial Analysis of Precipitation Methods over Sandies & Elm Watershed 
Date Type Total (in) 
Min 
(in) 
Max 
(in) 
Mean 
(in) 
Std. Dev. 
(in) 
NCDC 256,309.00 0.00 2.80 1.39 0.49 
NEXRAD 188,752.00 0.24 2.18 1.02 0.40 
February 21, 
2003 Storm 
Difference -35.8% 0.24 -0.62 -0.37 -0.09 
 146
MARCH 14, 2000 
NCDC Missing Stations:  Kingsbury and New Braunfels Municipal AP 
USGS Gage Flow Day Before: 22 cfs Day After: 290 cfs
NEXRAD  Minimum: 1.07 in. Maximum: 3.58 in.
NCDC  Minimum: 0 in. Maximum: 1.86 in. 
Convective Cells: Number: 1 Size: 5 Km.
Scale (hundredth inch) 
 
Figure B.9:  NEXRAD March 14, 2000 
 
 147
 
Figure B.10:  NCDC Gage IDW Interpolation March 14, 2000 
 
Figure B.11:  DAYMET Gage Interpolation March 14, 2000 
 148
MARCH 14, 2000 STORM 
There was such a large discrepancy between NEXRAD and NCDC gage interpolation 
that the entire storm was interpolated and checked. 
NCDC Missing Stations:  Kingsbury and New Braunfels Municipal AP 
USGS Gage Flow Day Before: 22 cfs Day After: 218 cfs
NEXRAD  Minimum: 1.07 in. Maximum: 3.58 in.
NCDC  Minimum: 1.00 in. Maximum: 2.11 in. 
Convective Cells: Number: 0 Size: NA
Scale (hundredth inch) 
 
Figure B.12:  NEXRAD 3/14/2000 thru 3/15/2000 
 
 149
 
Figure B.13:  NCDC Gage IDW Interpolation 3/14/2000 thru 3/15/2000 
NEXRAD indicates that the rain from this storm fell between 6:00 pm on March 14, 2000 
and 6 am on March 15, 2000.  Therefore the storm should be encompassed by one day of 
NCDC daily gage data, if the measurements were taken at 7 am as the output suggests.  
Instead the data is spread over three days, March 14, 15, and 16. 
The storm totals compare very well, as seen in Table B.2 below, though the pattern of the 
rainfall is incongruent. 
Table B.2: Spatial Analysis of Precipitation Methods over Sandies & Elm Watershed 
Date Type Total (in) 
Min 
(in) 
Max 
(in) 
Mean 
(in) 
Std. Dev. 
(in) 
NCDC 296079.00 1.00 2.11 1.61 0.24 
NEXRAD 357,625.00 1.07 3.58 1.94 0.63 
March 14, 
2000 Storm 
Difference 17.2% 0.07 1.47 0.33 0.39 
 
 150
APRIL 8, 2002 
NCDC Missing Stations:  New Braunfels Municipal AP 
USGS Gage Flow Day Before: 9.9 cfs Day After: 784 cfs 
NEXRAD  Minimum: 0.47 in. Maximum: 5.56 in.
NCDC  Minimum: 1.10 in. Maximum: 5.08 in. 
Convective Cells: Number: 0 Size: NA
Scale (hundredth inch) 
 
Figure B.14:  NEXRAD April 8, 2002 
 
 151
 
Figure B.15:  NCDC Gage IDW Interpolation April 8, 2002 
 
Figure B.15:  DAYMET Gage Interpolation April 8, 2002 
  
 152
MAY 20, 2000 
NCDC Missing Stations:  New Braunfels Municipal AP 
USGS Gage Flow Day Before: 11 cfs Day After: 209 cfs 
NEXRAD  Minimum: 0.17 in. Maximum: 3.26 in.
NCDC  Minimum: 0 in. Maximum: 4.20 in. 
Convective Cells: Number: 3 Size: 5 km.
Scale (hundredth inch) 
 
Figure B.16:  NEXRAD May 20, 2000 
 
 153
 
Figure B.17:  NCDC Gage IDW Interpolation May 20, 2000 
 
Figure B.18:  DAYMET Gage Interpolation May 20, 2000 
 
 154
JUNE 30, 2002 
NCDC Missing Stations:  New Braunfels Municipal AP 
USGS Gage Flow Day Before: 8.9 cfs Day After: 292 cfs 
NEXRAD  Minimum: 1.0 in. Maximum: 3.51 in.
NCDC  Minimum: 0.8 in. Maximum: 3.74 in. 
Convective Cells: Number: 1 Size: 15 km.
Scale (hundredth inch) 
 
Figure B.19:  NEXRAD June 30, 2002 
 
 155
 
Figure B.20:  NCDC Gage IDW Interpolation June 30, 2002 
 
Figure B.21:  DAYMET Gage Interpolation June 30, 2002 
 
 156
JULY 15, 2002 
NCDC Missing Stations:  New Braunfels Municipal AP 
USGS Gage Flow Day Before: 85 cfs Day After: 1090 cfs 
NEXRAD  Minimum: 1.67 in. Maximum: 4.71 in.
NCDC  Minimum: 0.71 in. Maximum: 1.90 in. 
Convective Cells: Number: 0 Size: NA
Scale (hundredth inch) 
 
Figure B.22:  NEXRAD July 15, 2002 
 
 157
 
Figure B.23:  NCDC Gage IDW Interpolation July 15, 2002 
 
Figure B.24:  DAYMET Gage Interpolation July 15, 2002 
 158
AUGUST 31, 2001 
NCDC Missing Stations:  Falls City 4WNW, Karnes City, and New Braunfels MAP 
USGS Gage Flow Day Before: 174 cfs Day After: 25,900 cfs 
NEXRAD  Minimum: 0.77 in. Maximum: 9.17 in.
NCDC  Minimum: 0.32 in. Maximum: 8.30 in. 
Convective Cells: Number: 0 Size: NA
Scale (hundredth inch) 
 
Figure B.25:  NEXRAD August 31, 2001 
 
 159
 
Figure B.26:  NCDC Gage IDW Interpolation August 31, 2001 
 
Figure B.27:  DAYMET Gage Interpolation August 31, 2001 
 160
SEPTEMBER 7, 2002 
NCDC Missing Stations:  Cuero 3 NW 
USGS Gage Flow Day Before: 2.2 cfs Day After: 25 cfs 
NEXRAD  Minimum: 0.03 in. Maximum: 4.23 in.
NCDC  Minimum: 1.27 in. Maximum: 4.98 in. 
Convective Cells: Number: 1 Size: 10 km.
Scale (hundredth inch) 
 
Figure B.28:  NEXRAD September 7, 2002 
 
 161
 
Figure B.29:  NCDC Gage IDW Interpolation September 7, 2002 
 
Figure B.30:  DAYMET Gage Interpolation September 7, 2002 
 162
OCTOBER 9, 2002 
NCDC Missing Stations:  Nixon 
USGS Gage Flow Day Before: 1.1 cfs Day After: 4.0 cfs 
NEXRAD  Minimum: 0.63 in. Maximum: 4.49 in.
NCDC  Minimum: 0.22 in. Maximum: 6.29 in. 
Convective Cells: Number: 0 Size: NA
Scale (hundredth inch) 
 
Figure B.31:  NEXRAD October 9, 2002 
 
 163
 
FigureB.32:  NCDC Gage IDW Interpolation October 9, 2002 
 
Figure B.33:  DAYMET Gage Interpolation October 9, 2002 
 164
NOVEMBER 17, 2003 
NCDC Missing Stations:  Nixon 
USGS Gage Flow Day Before: 6.8 cfs Day After: 8.5 cfs 
NEXRAD  Minimum: 0.13 in. Maximum: 4.0 in.
NCDC  Minimum: 0.03 in. Maximum: 5.3 in. 
Convective Cells: Number: 1 Size: 10 km.
Scale (hundredth inch) 
 
Figure B.34:  NEXRAD November 17, 2003 
 
 165
 
Figure B.35:  NCDC Gage IDW Interpolation November 17, 2003 
 
Figure B.36:  DAYMET Gage Interpolation November 17, 2003 
 166
DECEMBER 4, 2002 
NCDC Missing Stations:  Nixon 
USGS Gage Flow Day Before: 15 cfs Day After: 32 cfs 
NEXRAD  Minimum: 0.85 in. Maximum: 2.29 in.
NCDC  Minimum: 0 in. Maximum: 2.45 in. 
Convective Cells: Number: 2 Size: 5 km. Scale  
(hundredth inch) 
 
Figure B.37:  NEXRAD December 4, 2002 
 
 167
 
Figure B.38:  NCDC Gage IDW Interpolation December 4, 2002 
 
Figure B.39:  DAYMET Gage Interpolation December 4, 2002 
 168
Appendix C   
Upper Sandies and Elm 
Main Channel Lower Floodplain Upper Floodplain 
No. HydroCode Length 
Drain 
Area 
(Mi^2) 
Long. 
Slope 
Flow 
Bottom 
Width 
Depth 
Top 
Width 
Flow Depth 
Top 
Width 
Flow Depth 
Top 
Width 
1 Little Elm Creek 6,937.78 5.70 0.0033 4.56 0.05 1.23 6.20 35.21 1.42 26.07 220.17 0.92 488.67 
2 Clear Fork Creek 18,331.27 40.48 0.0033 32.37 0.50 2.48 12.92 249.97 2.96 54.33 1,563.22 1.91 1,018.43 
3 Tally Branch 8,337.55 11.12 0.0040 8.89 0.15 1.51 7.70 68.66 1.76 32.40 429.38 1.14 607.24 
4 Clear Fork Creek 5,122.41 58.56 0.0012 46.82 0.70 3.47 18.05 361.58 4.13 75.90 2,261.21 2.67 1,422.58 
5 Nose Creek 8,303.13 8.80 0.0041 7.04 0.10 1.38 7.01 54.33 1.61 29.49 339.75 1.04 552.67 
6 Murray Branch 6,624.53 5.60 0.0053 4.48 0.05 1.12 5.64 34.57 1.29 23.73 216.21 0.84 444.74 
7 Murray Branch 1,732.36 15.75 0.0012 12.59 0.20 2.17 11.05 97.23 2.53 46.51 608.07 1.64 871.68 
8 Clear Fork Creek 1,627.51 74.86 0.0018 59.86 0.90 3.46 18.18 462.27 4.16 76.44 2,890.86 2.69 1,432.72 
9 Red Branch 7,234.84 5.94 0.0051 4.75 0.05 1.15 5.80 36.70 1.33 24.41 229.54 0.86 457.62 
10 Clear Fork Creek 12,642.99 100.29 0.0011 80.19 1.20 4.23 22.33 619.29 5.11 93.85 3,872.87 3.30 1,759.08 
11 Salt Branch 7,465.12 8.69 0.0043 6.95 0.10 1.36 6.92 53.66 1.58 29.10 335.54 1.02 545.39 
12 Cordell Creek 5,563.44 3.91 0.0086 3.13 0.05 0.89 4.50 24.15 1.03 18.92 151.01 0.67 354.59 
13 Sandies Creek 5,078.17 8.33 0.0096 6.66 0.10 1.15 5.85 51.43 1.34 24.60 321.64 0.87 461.05 
14 Sandies Creek 7,362.58 33.68 0.0042 26.93 0.40 2.23 11.54 207.99 2.64 48.53 1,300.69 1.71 909.55 
15 Tidwell Creek 7,052.61 7.78 0.0104 6.22 0.10 1.10 5.62 48.03 1.29 23.66 300.34 0.83 443.48 
16 Sandies Creek 10,970.50 74.27 0.0018 59.39 0.90 3.45 18.17 458.61 4.16 76.37 2,868.02 2.69 1,431.42 
17 Sandies Creek 8,009.60 91.73 0.0012 73.35 1.10 4.00 21.11 566.44 4.83 88.74 3,542.34 3.12 1,663.36 
18 Talley Branch 9,465.83 8.17 0.0049 6.53 0.10 1.30 6.60 50.44 1.51 27.77 315.41 0.98 520.49 
19 East Fork O'Neal Creek 7,374.45 6.68 0.0046 5.34 0.10 1.22 6.18 41.22 1.42 26.00 257.79 0.92 487.36 
20 O'Neal Creek 12,593.83 23.15 0.0056 18.51 0.25 1.85 9.49 142.97 2.17 39.92 894.11 1.41 748.20 
21 O'Neal Creek 1,894.32 32.47 0.0026 25.96 0.40 2.40 12.42 200.49 2.84 52.24 1,253.80 1.84 979.21 
22 Baker Branch 7,836.60 6.17 0.0040 4.93 0.05 1.22 6.17 38.07 1.41 25.97 238.09 0.91 486.82 
23 O'Neal Creek 2,562.95 41.80 0.0012 33.42 0.50 3.08 15.90 258.10 3.64 66.89 1,614.07 2.35 1,253.79 
24 O'Neal Creek 6,820.52 58.17 0.0013 46.51 0.70 3.38 17.60 359.17 4.03 74.03 2,246.14 2.61 1,387.66 
25 Sandies Creek 1,175.87 152.24 0.0009 121.73 1.80 5.13 27.45 940.06 6.28 115.32 5,878.84 4.06 2,161.48 
26 Sandies Creek 654.17 152.81 0.0015 122.19 1.80 4.57 24.64 943.59 5.63 103.46 5,900.91 3.64 1,939.15 
27 Yow Branch 10,363.24 11.55 0.0041 9.23 0.15 1.53 7.78 71.30 1.78 32.71 445.90 1.15 613.17 
 169
Upper Sandies and Elm 
Main Channel Lower Floodplain Upper Floodplain 
No. HydroCode Length 
Drain 
Area 
(Mi^2) 
Long. 
Slope 
Flow 
Bottom 
Width 
Depth 
Top 
Width 
Flow Depth 
Top 
Width 
Flow Depth 
Top 
Width 
28 Sandies Creek 13,030.92 183.19 0.0009 146.48 2.15 5.37 29.01 1,131.17 6.63 121.77 7,074.02 4.29 2,282.50 
29 Sandies Creek 3,600.16 285.64 0.0008 228.40 3.40 6.32 34.99 1,763.79 7.97 146.57 11,030.19 5.16 2,747.22 
30 Sandies Creek 18,659.16 331.30 0.0004 264.91 3.90 7.60 41.88 2,045.72 9.54 175.51 12,793.30 6.18 3,289.70 
31 Sandies Creek 3,673.11 332.65 0.0008 265.99 3.95 6.65 37.22 2,054.08 8.47 155.77 12,845.55 5.48 2,919.71 
32 Dykes Creek 4,050.32 1.74 0.0054 1.39 0.00 0.72 3.62 10.73 0.83 15.22 67.08 0.54 285.26 
33 Panther Branch 6,529.81 3.26 0.0051 2.61 0.05 0.92 4.64 20.14 1.06 19.54 125.95 0.69 366.20 
34 Jack Hand Branch 7,878.42 3.31 0.0046 2.65 0.05 0.94 4.76 20.43 1.09 20.02 127.79 0.70 375.22 
35 Panther Branch 4,803.64 12.81 0.0012 10.25 0.15 1.99 10.08 79.12 2.31 42.42 494.82 1.49 795.03 
36 Racetrack Creek 5,510.07 3.80 0.0049 3.04 0.05 0.98 4.94 23.45 1.13 20.80 146.62 0.73 389.93 
37 Willow Creek 11,134.97 15.90 0.0033 12.71 0.20 1.78 9.10 98.18 2.08 38.28 614.01 1.35 717.56 
38 Jack Pump Creek 8,787.90 11.63 0.0040 9.30 0.15 1.53 7.82 71.80 1.79 32.91 448.99 1.16 616.78 
39 Corral Creek 3,923.89 1.78 0.0048 1.43 0.00 0.75 3.73 11.01 0.86 15.70 68.87 0.55 294.36 
40 Jack Pump Creek 1,619.91 14.14 0.0025 11.31 0.15 1.81 9.21 87.34 2.11 38.74 546.20 1.36 726.06 
41 Brushy Creek 3 16,945.71 19.10 0.0042 15.27 0.25 1.82 9.33 117.94 2.14 39.26 737.59 1.38 735.94 
42 Mustang Creek 6,091.62 6.74 0.0043 5.39 0.10 1.24 6.29 41.62 1.44 26.48 260.30 0.93 496.26 
43 Brushy Creek 3 3,182.68 43.84 0.0003 35.06 0.50 4.04 20.71 270.71 4.74 87.14 1,692.94 3.07 1,633.38 
44 Elm Creek 15,606.91 29.46 0.0025 23.56 0.35 2.35 12.10 181.92 2.77 50.89 1,137.66 1.79 953.90 
45 Shockley Creek 12,795.83 16.59 0.0025 13.27 0.20 1.91 9.75 102.45 2.23 41.03 640.71 1.44 769.01 
46 Elm Creek 915.78 46.30 0.0011 37.02 0.55 3.24 16.74 285.92 3.83 70.42 1,788.03 2.48 1,319.93 
47 Elm Creek 6,665.28 107.65 0.0009 86.07 1.25 4.52 23.83 664.69 5.45 100.19 4,156.79 3.53 1,877.89 
48 Elm Creek 4,098.77 132.93 0.0010 106.29 1.55 4.77 25.42 820.83 5.81 106.81 5,133.19 3.76 2,001.96 
49 Wickey Branch 6,099.10 4.00 0.0049 3.20 0.05 1.00 5.04 24.71 1.15 21.20 154.54 0.75 397.41 
50 Elm Creek 1,696.58 139.73 0.0012 111.73 1.65 4.67 25.01 862.81 5.72 105.04 5,395.76 3.70 1,968.78 
51 Rusten Branch 2,501.98 1.00 0.0096 0.80 0.00 0.53 2.64 6.16 0.61 11.11 38.54 0.39 208.29 
52 Mound Creek 14,163.31 14.71 0.0040 11.76 0.15 1.68 8.53 90.84 1.95 35.87 568.08 1.26 672.35 
53 Mound Creek 7,197.20 20.26 0.0017 16.20 0.25 2.22 11.34 125.07 2.60 47.71 782.17 1.68 894.20 
54 Board Branch 5,286.55 2.91 0.0040 2.33 0.05 0.92 4.65 17.95 1.07 19.58 112.28 0.69 366.96 
55 Mound Creek 1,936.03 25.80 0.0015 20.63 0.30 2.46 12.59 159.28 2.88 52.96 996.11 1.86 992.60 
56 Elm Creek 10,146.75 180.64 0.0003 144.44 2.15 6.70 35.67 1,115.45 8.16 149.90 6,975.69 5.28 2,809.61 
 170
Upper Sandies and Elm 
Main Channel Lower Floodplain Upper Floodplain 
No. HydroCode Length 
Drain 
Area 
(Mi^2) 
Long. 
Slope 
Flow 
Bottom 
Width 
Depth 
Top 
Width 
Flow Depth 
Top 
Width 
Flow Depth 
Top 
Width 
57 Elm Creek 3,161.64 194.87 0.0009 155.82 2.30 5.45 29.53 1,203.30 6.74 123.93 7,525.08 4.36 2,322.95 
58 Cottonwood Creek 2 11,145.29 10.96 0.0038 8.76 0.15 1.52 7.73 67.67 1.77 32.52 423.20 1.14 609.54 
59 Elm Creek 4,008.72 209.43 0.0002 167.46 2.50 7.29 38.94 1,293.19 8.90 163.57 8,087.22 5.76 3,065.93 
60 Elm Creek 1,500.85 212.09 0.0013 169.59 2.50 5.23 28.63 1,309.61 6.53 120.04 8,189.89 4.23 2,249.96 
61 Rocky Creek 20,712.78 26.08 0.0028 20.86 0.30 2.21 11.35 161.07 2.60 47.75 1,007.26 1.68 895.00 
62 Elm Creek 2,545.52 239.92 0.0004 191.84 2.85 6.96 37.66 1,481.48 8.60 158.07 9,264.72 5.57 2,962.92 
                              
Lower Sandies Watershed 
Main Channel Lower Floodplain Upper Floodplain 
No. HydroCode Length 
Drain 
Area 
(Mi^2) 
Long. 
Slope 
Flow 
Bottom 
Width 
Depth 
Top 
Width 
Flow Depth 
Top 
Width 
Flow Depth 
Top 
Width 
1 Little Cooper Creek 3,975.05 1.33 0.0015 1.06 0.00 0.83 4.15 8.19 0.95 17.47 51.19 0.61 327.36 
2 Cooper Creek 6,832.36 4.71 0.0011 3.76 0.05 1.41 7.10 29.07 1.63 29.86 181.82 1.05 559.69 
3 Cooper Creek 1,007.62 6.25 0.0019 5.00 0.05 1.41 7.10 38.58 1.63 29.87 241.28 1.05 559.85 
4 Anderson Creek 9,212.19 5.42 0.0007 4.34 0.05 1.62 8.14 33.49 1.87 34.26 209.44 1.21 642.18 
5 Shoats Creek 25,028.06 27.19 0.0004 21.74 0.30 3.29 16.76 167.90 3.84 70.53 1,049.98 2.48 1,321.95 
6 Clear Creek 13,986.03 20.04 0.0007 16.03 0.25 2.64 13.47 123.78 3.09 56.69 774.05 2.00 1,062.59 
7 Clear Creek 5,286.44 55.60 0.0005 44.46 0.65 4.05 20.90 343.32 4.79 87.92 2,147.04 3.10 1,647.99 
8 Clear Creek 2,451.31 62.79 0.0008 50.21 0.75 3.85 19.98 387.72 4.57 84.02 2,424.70 2.96 1,574.81 
9 Clear Creek 2,742.22 71.49 0.0007 57.16 0.85 4.06 21.16 441.43 4.85 88.99 2,760.54 3.13 1,668.02 
10 Blackjack Creek 10,102.04 5.73 0.0007 4.58 0.05 1.64 8.24 35.39 1.89 34.65 221.32 1.22 649.43 
11 Clear Creek 7,677.78 84.19 0.0004 67.32 1.00 4.86 25.32 519.84 5.80 106.49 3,250.90 3.75 1,996.10 
12 Boggie Creek 9,648.21 6.04 0.0009 4.83 0.05 1.59 8.02 37.31 1.84 33.75 233.30 1.19 632.56 
13 Birds Creek 9,504.58 11.32 0.0008 9.05 0.15 2.08 10.53 69.89 2.41 44.32 437.06 1.56 830.71 
14 Five Mile Creek 15,421.07 23.97 0.0004 19.17 0.30 3.14 15.99 148.00 3.66 67.27 925.56 2.37 1,260.88 
15 Sadberry Creek 6,673.43 3.51 0.0007 2.81 0.05 1.38 6.97 21.70 1.60 29.31 135.72 1.03 549.37 
16 Five Mile Creek 4,059.30 31.00 0.0004 24.79 0.35 3.34 17.03 191.42 3.90 71.67 1,197.11 2.52 1,343.27 
17 Brushy Creek 2 11,176.35 10.56 0.0004 8.44 0.10 2.28 11.49 65.21 2.63 48.36 407.79 1.70 906.37 
18 Five Mile Creek 6,443.57 52.00 0.0003 41.58 0.60 4.21 21.65 321.12 4.96 91.07 2,008.17 3.21 1,707.07 
 171
Lower Sandies Watershed 
Main Channel Lower Floodplain Upper Floodplain 
No. HydroCode Length 
Drain 
Area 
(Mi^2) 
Long. 
Slope 
Flow 
Bottom 
Width 
Depth 
Top 
Width 
Flow Depth 
Top 
Width 
Flow Depth 
Top 
Width 
19 Brushy Creek 1 15,948.19 10.97 0.0003 8.77 0.05 2.41 12.08 67.76 2.77 50.82 423.72 1.79 952.49 
20 Buckhorn Creek 13,117.32 12.27 0.0005 9.81 0.15 2.34 11.86 75.78 2.72 49.89 473.87 1.76 935.17 
21 Alligator Creek 7,349.19 2.60 0.0006 2.08 0.05 1.27 6.38 16.05 1.46 26.83 100.34 0.94 502.98 
22 Sugar Creek 16,415.50 10.19 0.0005 8.15 0.10 2.17 10.96 62.94 2.51 46.11 393.62 1.62 864.36 
23 Liberty Creek 8,223.40 3.98 0.0007 3.18 0.05 1.45 7.32 24.56 1.68 30.80 153.56 1.08 577.35 
24 Cottonwood Creek 1 5,349.30 4.09 0.0007 3.27 0.05 1.48 7.43 25.26 1.70 31.24 157.98 1.10 585.54 
25 Cottonwood Creek 1 3,149.16 9.20 0.0007 7.36 0.10 1.95 9.83 56.81 2.25 41.38 355.27 1.46 775.56 
26 Turkey Creek 4,909.21 2.96 0.0008 2.37 0.05 1.24 6.27 18.29 1.44 26.36 114.39 0.93 494.13 
27 Cottonwood Creek 1 7,564.40 18.70 0.0004 14.95 0.20 2.86 14.48 115.47 3.32 60.93 722.13 2.14 1,142.00 
28 Sugar Creek 3,400.15 29.97 0.0006 23.96 0.35 3.09 15.78 185.05 3.61 66.39 1,157.24 2.34 1,244.33 
29 Sugar Creek 2,343.51 33.87 0.0007 27.08 0.40 3.13 16.03 209.14 3.67 67.45 1,307.89 2.37 1,264.35 
30 Salty Creek 7,057.36 53.93 0.0003 43.12 0.65 4.38 22.57 332.98 5.17 94.93 2,082.36 3.34 1,779.29 
31 Salty Creek 3,426.99 66.52 0.0006 53.19 0.80 4.18 21.69 410.73 4.97 91.24 2,568.57 3.21 1,710.09 
32 Putnam Branch 9,903.08 6.15 0.0005 4.92 0.05 1.80 9.07 37.98 2.08 38.16 237.53 1.34 715.22 
33 Salty Creek 11,146.94 89.43 0.0002 71.51 1.05 5.59 29.02 552.20 6.64 122.04 3,453.28 4.30 2,287.57 
34 Five Mile Creek 12,833.61 160.52 0.0002 128.35 1.90 7.01 36.96 991.17 8.46 155.37 6,198.49 5.47 2,912.30 
35 White Oak Branch 7,276.80 4.92 0.0007 3.94 0.05 1.57 7.90 30.40 1.81 33.26 190.09 1.17 623.34 
36 Sandies Creek 14,504.56 377.55 0.0005 301.89 4.45 7.67 42.78 2,331.32 9.74 179.08 14,579.35 6.30 3,356.75 
37 Sandies Creek 4,134.26 383.66 0.0005 306.77 4.55 7.76 43.34 2,369.04 9.86 181.41 14,815.24 6.39 3,400.41 
38 Sandies Creek 4,573.94 549.29 0.0005 439.21 6.50 8.56 49.31 3,391.78 11.17 205.65 21,211.11 7.24 3,854.82 
39 Sandies Creek 3,035.90 554.55 0.0007 443.42 6.55 7.99 46.50 3,424.29 10.51 193.65 21,414.46 6.82 3,629.80 
40 Sandies Creek 7,541.69 576.54 0.0003 461.00 6.80 9.61 54.87 3,560.03 12.45 229.13 22,263.32 8.07 4,294.78 
41 Sandies Creek 5,003.07 587.03 0.0004 469.39 6.95 9.37 53.82 3,624.83 12.20 224.57 22,668.55 7.91 4,209.45 
42 Sandies Creek 7,791.08 678.81 0.0003 542.78 8.05 10.08 58.46 4,191.56 13.22 243.60 26,212.74 8.58 4,566.01 
43 Sandies Creek 4,679.80 681.90 0.0006 545.25 8.05 8.90 52.54 4,210.65 11.84 218.37 26,332.10 7.69 4,093.22 
44 Deer Creek 16,042.83 24.72 0.0006 19.76 0.30 2.94 15.02 152.62 3.44 63.20 954.47 2.22 1,184.53 
45 Sandies Creek 5,733.61 711.24 0.0005 568.71 8.40 9.32 55.01 4,391.80 12.40 228.66 27,464.94 8.05 4,286.05 
 
 172
Appendix D 
NCDC daily storm totals were evaluated against NEXRAD storm totals for each 
storm with a daily value greater than ½ inch according to the Cheapside NCDC rain 
gauge.  NEXRAD totals were averaged across the 10 closest subbasins to the Cheapside 
station and aggregated for the 24 hours from 7 am to 7am.  (See Figure D.1)  An 
evaluation of OK was given for NEXRAD storms that came within +/- 20% of the NCDC 
storms. 
Figure D.1: Precipitation Stations, Thiessen Polygons, and Comparison Area
 173
Table D.1: Significant Storm Comparison - 2000 
Date 
NCDC 
(In) 
NEXRAD 
(in) Difference Evaluation Note 
1/7/2000 0.86 0.44 2.0 NG  
1/8/2000 2.45 0.79 3.1 NG  
1/28/2000 0.81 0.10 8.3 NG  
2/23/2000 2.24 2.42 0.9 OK   
3/15/2000 1.92 0.82 2.3 OK storm totals add up 
4/3/2000 0.68 0.92 0.7 NG  
5/1/2000 0.5 0.76 0.7 NG  
5/2/2000 1.65 2.08 0.8 OK   
5/3/2000 0.7 0.00 100.0 OK storm totals add up 
5/13/2000 0.9 0.92 1.0 OK   
5/20/2000 0.84 1.36 0.6 NG  
6/5/2000 1.42 1.89 0.8 OK   
6/9/2000 0.76 0.84 0.9 OK   
6/10/2000 1.8 1.89 1.0 OK   
6/11/2000 1.5 1.27 1.2 OK   
8/22/2000 0.53 0.20 2.7 OK storm totals add up 
9/22/2000 1.67 1.41 1.2 OK   
9/25/2000 0.51 0.50 1.0 OK   
10/8/2000 1.15 0.00 100.0 NG  
10/10/2000 0.62 0.00 100.0 NG  
10/22/2000 0.58 1.20 0.5 NG  
10/23/2000 0.88 0.30 2.9 NG  
11/4/2000 2.25 2.20 1.0 OK   
11/6/2000 1.33 0.00 100.0 NG  
11/18/2000 1.44 0.00 100.0 NG  
11/19/2000 1.27 0.00 100.0 NG  
11/24/2000 1.05 0.00 100.0 NG  
12/13/2000 0.75 0.00 100.0 NG  
 
 174
Table D.2: Significant Storm Comparison - 2001 
Date 
NCDC 
(In) 
NEXRAD 
(in) Difference Evaluation Note 
1/11/2001 0.99 0.00 100.0 OK storm totals add up 
3/2/2001 1.77 0.73 2.4 NG  
3/3/2001 0.64 0.30 2.2 NG  
3/4/2001 0.77 0.40 1.9 NG  
3/15/2001 1.72 1.23 1.4 NG  
5/5/2001 1.1 0.49 2.2 NG  
6/9/2001 0.54 0.49 1.1 OK   
8/30/2001 2.34 1.85 1.3 NG  
8/31/2001 8.6 8.83 1.0 OK   
9/1/2001 1.8 0.00 514.3 OK storm totals add up 
9/2/2001 1.05 0.28 3.8 OK storm totals add up 
9/6/2001 0.85 1.08 0.8 OK   
9/10/2001 2.12 0.13 16.1 NG  
10/6/2001 0.89 0.55 1.6 NG  
10/13/2001 1.52 1.56 1.0 OK   
11/29/2001 0.6 0.55 1.1 OK   
12/2/2001 0.71 1.70 0.4 NG  
12/3/2001 2.55 1.28 2.0 OK storm totals add up 
12/8/2001 0.71 0.63 1.1 OK   
12/12/2001 0.67 0.53 1.3 NG  
12/16/2001 0.64 0.19 3.4 NG  
 
 175
Table D.3: Significant Storm Comparison - 2002 
Date 
NCDC 
(In) 
NEXRAD 
(in) Difference Evaluation Note 
3/20/2002 0.89 0.95 0.9 OK   
4/8/2002 2.88 2.40 1.2 OK   
5/28/2002 1.48 0.59 2.5 NG  
6/16/2002 0.64 0.97 0.7 NG  
6/21/2002 0.91 0.11 8.1 NG  
6/27/2002 1.3 1.96 0.7 NG  
6/30/2002 2.31 2.57 0.9 OK   
7/2/2002 1.95 2.60 0.7 NG  
7/3/2002 1.25 2.18 0.6 NG  
7/10/2002 0.84 0.82 1.0 OK   
7/15/2002 1.35 4.69 0.3 NG  
7/16/2002 1.22 1.61 0.8 OK   
7/17/2002 1.33 0.40 3.3 NG  
8/15/2002 0.61 0.34 1.8 NG  
8/16/2002 1.05 0.14 7.5 NG  
9/7/2002 1.98 0.93 2.1 OK storm totals add up 
9/8/2002 1.24 2.55 0.5 OK storm totals add up 
9/9/2002 0.63 0.21 3.0 OK storm totals add up 
10/8/2002 0.87 0.39 2.2 OK storm totals add up 
10/9/2002 0.77 0.97 0.8 OK storm totals add up 
10/23/2002 2.55 1.40 1.8 OK storm totals add up 
10/25/2002 1.36 1.13 1.2 OK   
11/3/2002 0.79 0.84 0.9 OK   
11/4/2002 1.4 1.86 0.8 OK   
11/5/2002 2.4 1.13 2.1 OK storm totals add up 
12/5/2002 0.98 0.72 1.4 OK storm totals add up 
12/9/2002 0.86 1.58 0.5 NG  
12/10/2002 1.1 0.23 4.9 NG  
12/13/2002 2.86 0.00 100.0 OK storm totals add up 
12/24/2002 2.38 1.10 2.2 NG  
12/31/2002 1.1 1.00 1.1 OK   
 
 176
Table D.4: Significant Storm Comparison - 2003 
Date 
NCDC 
(In) 
NEXRAD 
(in) Difference Evaluation Note 
1/12/2003 0.88 1.32 0.7 NG  
1/13/2003 0.85 0.26 3.3 NG  
2/21/2003 1.52 0.35 4.4 NG  
6/4/2003 0.97 0.61 1.6 OK storm totals add up 
6/6/2003 0.63 0.60 1.0 OK   
6/14/2003 1.05 1.00 1.1 OK   
7/5/2003 1.17 1.48 0.8 OK   
7/8/2003 0.71 0.15 4.8 OK storm totals add up 
7/9/2003 0.61 0.46 1.3 NG  
7/16/2003 1.71 2.05 0.8 OK   
7/17/2003 1.01 0.17 5.8 OK storm totals add up 
7/28/2003 0.59 0.03 20.3 NG  
8/9/2003 0.79 0.62 1.3 NG  
8/12/2003 1.54 0.88 1.7 NG  
8/17/2003 0.52 0.22 2.4 NG  
9/2/2003 3.1 3.51 0.9 OK   
9/3/2003 0.63 0.07 8.8 OK storm totals add up 
9/12/2003 1.47 1.92 0.8 OK   
9/19/2003 1.05 0.53 2.0 NG  
9/21/2003 1.37 0.37 3.7 NG  
10/26/2003 0.87 0.57 1.5 NG  
11/18/2003 0.64 0.25 2.6 NG  
12/13/2003 0.83 0.40 2.1 OK storm totals add up 
12/29/2003 1.03 0.75 1.4 NG  
 
 177
Table D.5: Significant Storm Comparison - 2004 
Date 
NCDC 
(In) 
NEXRAD 
(in) Difference Evaluation Note 
1/17/2004 1.75 1.05 1.7 NG  
1/25/2004 0.78 0.54 1.4 NG  
2/11/2004 1.4 0.15 9.6 NG  
3/14/2004 0.6 0.14 4.2 NG  
4/3/2004 0.59 0.64 0.9 OK   
4/11/2004 1.37 1.12 1.2 OK   
4/24/2004 0.91 0.70 1.3 NG  
4/26/2004 0.53 0.10 5.4 OK storm totals add up 
4/29/2004 0.7 0.71 1.0 OK   
5/2/2004 0.51 0.01 50.1 OK storm totals add up 
5/12/2004 0.82 0.64 1.3 NG  
5/14/2004 2.35 1.76 1.3 NG  
6/5/2004 1.23 0.86 1.4 NG  
6/8/2004 1.79 0.91 2.0 NG  
6/9/2004 0.75 0.10 7.6 NG  
6/16/2004 0.56 0.61 0.9 OK   
6/26/2004 1.51 1.00 1.5 OK storm totals add up 
7/1/2004 1.31 0.83 1.6 OK storm totals add up 
7/24/2004 0.94 0.18 5.2 NG  
7/30/2004 1.05 1.40 0.7 NG  
8/22/2004 0.64 0.43 1.5 OK storm totals add up 
9/14/2004 1.08 0.73 1.5 NG  
9/15/2004 0.96 0.43 2.2 NG  
10/3/2004 1.63 0.33 5.0 NG  
10/7/2004 1.16 0.15 7.8 NG  
10/14/2004 1.5 1.46 1.0 OK   
10/24/2004 1.23 0.00 448.9 OK storm totals add up 
11/1/2004 1.14 1.11 1.0 OK   
11/17/2004 0.71 1.83 0.4 NG  
11/18/2004 1.46 0.05 31.0 OK storm totals add up 
11/21/2004 1.5 1.42 1.1 OK   
11/22/2004 0.86 1.81 0.5 NG  
11/23/2004 1.06 0.81 1.3 NG  
 178
Appendix E:  Model Parameters 
UPPER SANDIES 
PWATER – PARAMETER SET 2 
 
*** < PLS>    FOREST      LZSN    INFILT      LSUR     SLSUR     KVARY     AGWRC 
*** x  - x                (in)   (in/hr)      (ft)              (1/in)   (1/day) 
   11             0.       6.2      0.01      726.     0.042        0.     0.999 
   12   16        0.       6.2      0.02      726      0.042        0.     0.999 
   21             0.       6.2      0.01      663.     0.039        0.     0.999 
   22   26        0.       6.2      0.03      663.     0.039        0.     0.999 
   31             0.       6.2      0.01      686.     0.037        0.     0.999 
   32   36        0.       6.2      0.03      686.     0.037        0.     0.999 
   41             0.       6.2      0.01      845.      0.04        0.     0.999 
   42   46        0.       6.2      0.02      845.      0.04        0.     0.999 
   51             0.       6.2      0.01      479.     0.043        0.     0.999 
   52   56        0.       6.2      0.03      479.     0.043        0.     0.999 
   61             0.       6.2      0.01      849.     0.044        0.     0.999 
   62   66        0.       6.2      0.03      849.     0.044        0.     0.999 
   71             0.       6.2      0.01     1859.     0.046        0.     0.999 
   72   76        0.       6.2      0.03     1859.     0.046        0.     0.999 
   81             0.       6.2      0.01     1865.     0.083        0.     0.999 
   82   86        0.       6.2      0.03     1865.     0.083        0.     0.999 
   91             0.       6.2      0.01      691.     0.039        0.     0.999 
   92   96        0.       6.2      0.03      691.     0.039        0.     0.999 
  101             0.       6.2      0.01      837.     0.037        0.     0.999 
  102  106        0.       6.2      0.02      837.     0.037        0.     0.999 
  111             0.       6.2      0.01      546.     0.048        0.     0.999 
  112  116        0.       6.2      0.03      546.     0.048        0.     0.999 
  121             0.       6.2      0.01      700.     0.073        0.     0.999 
  122  126        0.       6.2      0.06      700.     0.073        0.     0.999 
  131             0.       6.2      0.01      739.     0.057        0.     0.999 
  132  136        0.       6.2      0.06      739.     0.057        0.     0.999 
  141             0.       6.2      0.01      688.     0.046        0.     0.999 
  142  146        0.       6.2      0.06      688.     0.046        0.     0.999 
  151             0.       6.2      0.01      760.     0.062        0.     0.999 
  152  156        0.       6.2      0.06      760.     0.062        0.     0.999 
  161             0.       6.2      0.01      564.     0.031        0.     0.999 
  162  166        0.       6.2      0.06      564.     0.031        0.     0.999 
  171             0.       6.2      0.01      717.     0.043        0.     0.999 
  172  176        0.       6.2      0.03      717.     0.043        0.     0.999 
  181             0.       6.2      0.01      924.     0.047        0.     0.999 
  182  186        0.       6.2      0.03      924.     0.047        0.     0.999 
  191             0.       6.2      0.01      723.     0.036        0.     0.999 
  192  196        0.       6.2      0.06      723.     0.036        0.     0.999 
  201             0.       6.2      0.01      652.     0.045        0.     0.999 
  202  206        0.       6.2      0.06      652.     0.045        0.     0.999 
  211             0.       6.2      0.01     1027.     0.036        0.     0.999 
  212  215        0.       6.2      0.03     1027.     0.036        0.     0.999 
  221             0.       6.2      0.01     1057.      0.05        0.     0.999 
  222  226        0.       6.2      0.03     1057.      0.05        0.     0.999 
  231             0.       6.2      0.01     1177.     0.035        0.     0.999 
  232  236        0.       6.2      0.03     1177.     0.035        0.     0.999 
  241             0.       6.2      0.01      941.     0.048        0.     0.999 
  242  246        0.       6.2      0.03      941.     0.048        0.     0.999 
  251             0.       6.2      0.01      974.     0.027        0.     0.999 
  252  256        0.       6.2      0.03      974.     0.027        0.     0.999 
  261             0.       6.2      0.01     1061.     0.042        0.     0.999 
  262  265        0.       6.2      0.03     1061.     0.042        0.     0.999 
  271             0.       6.2      0.01      877.      0.04        0.     0.999 
  272  276        0.       6.2      0.03      877.      0.04        0.     0.999 
 179
*** < PLS>    FOREST      LZSN    INFILT      LSUR     SLSUR     KVARY     AGWRC 
*** x  - x                (in)   (in/hr)      (ft)              (1/in)   (1/day) 
  281             0.       6.2      0.01      757.     0.037        0.     0.999 
  282  286        0.       6.2      0.02      757.     0.037        0.     0.999 
  291  296        0.       6.2      0.01     1201.     0.062        0.     0.999 
  301             0.       6.2      0.01      868.     0.033        0.     0.999 
  302  306        0.       6.2      0.02      868.     0.033        0.     0.999 
  312  316        0.       6.2      0.03     1069.     0.082        0.     0.999 
  322  326        0.       6.2      0.03     1013.     0.078        0.     0.999 
  332  336        0.       6.2      0.03      683.     0.058        0.     0.999 
  342  346        0.       6.2      0.03      935.     0.076        0.     0.999 
  351             0.       6.2      0.01     1366.     0.045        0.     0.999 
  352  356        0.       6.2      0.03     1366.     0.045        0.     0.999 
  361  366        0.       6.2      0.01      842.     0.055        0.     0.999 
  371  376        0.       6.2      0.01      865.     0.038        0.     0.999 
  381             0.       6.2      0.01      830.     0.039        0.     0.999 
  382  386        0.       6.2      0.03      830.     0.039        0.     0.999 
  391             0.       6.2      0.01      745.     0.072        0.     0.999 
  392  396        0.       6.2      0.03      745.     0.072        0.     0.999 
  401  405        0.       6.2      0.01     2051.     0.058        0.     0.999 
  411             0.       6.2      0.01      691.     0.045        0.     0.999 
  412  416        0.       6.2      0.03      691.     0.045        0.     0.999 
  421  426        0.       6.2      0.01      940.     0.037        0.     0.999 
  431  436        0.       6.2      0.01      876.     0.038        0.     0.999 
  441             0.       6.2      0.01      663.     0.028        0.     0.999 
  442  446        0.       6.2      0.02      663.     0.028        0.     0.999 
  451  456        0.       6.2      0.01      688.     0.037        0.     0.999 
  462  465        0.       6.2      0.02     2973.     0.079        0.     0.999 
  471             0.       6.2      0.01      886.     0.036        0.     0.999 
  472  476        0.       6.2      0.02      886.     0.036        0.     0.999 
  481  486        0.       6.2      0.01     1398.      0.04        0.     0.999 
  491  496        0.       6.2      0.01      671.     0.055        0.     0.999 
  501  506        0.       6.2      0.01     1031.      0.03        0.     0.999 
  511             0.       6.2      0.01      757.     0.086        0.     0.999 
  512  516        0.       6.2      0.03      757.     0.086        0.     0.999 
  521             0.       6.2      0.01      685.      0.05        0.     0.999 
  522  526        0.       6.2      0.03      685.      0.05        0.     0.999 
  531             0.       6.2      0.01     1268.     0.055        0.     0.999 
  532  536        0.       6.2      0.03     1268.     0.055        0.     0.999 
  542  546        0.       6.2      0.02      757.     0.056        0.     0.999 
  551  556        0.       6.2      0.01     1486.     0.037        0.     0.999 
  561  566        0.       6.2      0.01      993.     0.033        0.     0.999 
  572  576        0.       6.2      0.02     1056.     0.063        0.     0.999 
  581             0.       6.2      0.01     1039.     0.054        0.     0.999 
  582  586        0.       6.2      0.03     1039.     0.054        0.     0.999 
  591             0.       6.2      0.01     1117.     0.042        0.     0.999 
  592  596        0.       6.2      0.02     1117.     0.042        0.     0.999 
  601             0.       6.2      0.01     1509.     0.059        0.     0.999 
  602  606        0.       6.2      0.03     1509.     0.059        0.     0.999 
  611             0.       6.2      0.01      956.     0.048        0.     0.999 
  612  616        0.       6.2      0.02      956.     0.048        0.     0.999 
  621             0.       6.2      0.01     2377.     0.055        0.     0.999 
  622  626        0.       6.2      0.03     2377.     0.055        0.     0.999 
PWater – Parameter Set 3 
 
*** < PLS>    PETMAX    PETMIN    INFEXP    INFILD    DEEPFR    BASETP    AGWETP 
*** x  - x   (deg F)   (deg F) 
   11   15        0.        0.        2.        2.        0.        0.        0. 
   16             0.        0.        2.        2.        0.        0.      0.05 
   21   25        0.        0.        2.        2.        0.        0.        0. 
   26             0.        0.        2.        2.        0.        0.      0.05 
   31   35        0.        0.        2.        2.        0.        0.        0. 
   36             0.        0.        2.        2.        0.        0.      0.05 
   41   45        0.        0.        2.        2.        0.        0.        0. 
   46             0.        0.        2.        2.        0.        0.      0.05 
 180
*** < PLS>    PETMAX    PETMIN    INFEXP    INFILD    DEEPFR    BASETP    AGWETP 
*** x  - x   (deg F)   (deg F) 
   51   55        0.        0.        2.        2.        0.        0.        0. 
   56             0.        0.        2.        2.        0.        0.      0.05 
   61   65        0.        0.        2.        2.        0.        0.        0. 
   66             0.        0.        2.        2.        0.        0.      0.05 
   71   75        0.        0.        2.        2.        0.        0.        0. 
   76             0.        0.        2.        2.        0.        0.      0.05 
   81   85        0.        0.        2.        2.        0.        0.        0. 
   86             0.        0.        2.        2.        0.        0.      0.05 
   91   95        0.        0.        2.        2.        0.        0.        0. 
   96             0.        0.        2.        2.        0.        0.      0.05 
  101  105        0.        0.        2.        2.        0.        0.        0. 
  106             0.        0.        2.        2.        0.        0.      0.05 
  111  115        0.        0.        2.        2.        0.        0.        0. 
  116             0.        0.        2.        2.        0.        0.      0.05 
  121  125        0.        0.        2.        2.        0.        0.        0. 
  126             0.        0.        2.        2.        0.        0.      0.05 
  131  135        0.        0.        2.        2.        0.        0.        0. 
  136             0.        0.        2.        2.        0.        0.      0.05 
  141  145        0.        0.        2.        2.        0.        0.        0. 
  146             0.        0.        2.        2.        0.        0.      0.05 
  151  155        0.        0.        2.        2.        0.        0.        0. 
  156             0.        0.        2.        2.        0.        0.      0.05 
  161  165        0.        0.        2.        2.        0.        0.        0. 
  166             0.        0.        2.        2.        0.        0.      0.05 
  171  175        0.        0.        2.        2.        0.        0.        0. 
  176             0.        0.        2.        2.        0.        0.      0.05 
  181  185        0.        0.        2.        2.        0.        0.        0. 
  186             0.        0.        2.        2.        0.        0.      0.05 
  191  195        0.        0.        2.        2.        0.        0.        0. 
  196             0.        0.        2.        2.        0.        0.      0.05 
  201  205        0.        0.        2.        2.        0.        0.        0. 
  206             0.        0.        2.        2.        0.        0.      0.05 
  211  225        0.        0.        2.        2.        0.        0.        0. 
  226             0.        0.        2.        2.        0.        0.      0.05 
  231  235        0.        0.        2.        2.        0.        0.        0. 
  236             0.        0.        2.        2.        0.        0.      0.05 
  241  245        0.        0.        2.        2.        0.        0.        0. 
  246             0.        0.        2.        2.        0.        0.      0.05 
  251  255        0.        0.        2.        2.        0.        0.        0. 
  256             0.        0.        2.        2.        0.        0.      0.05 
  261  275        0.        0.        2.        2.        0.        0.        0. 
  276             0.        0.        2.        2.        0.        0.      0.05 
  281  285        0.        0.        2.        2.        0.        0.        0. 
  286             0.        0.        2.        2.        0.        0.      0.05 
  291  295        0.        0.        2.        2.        0.        0.        0. 
  296             0.        0.        2.        2.        0.        0.      0.05 
  301  305        0.        0.        2.        2.        0.        0.        0. 
  306             0.        0.        2.        2.        0.        0.      0.05 
  312  315        0.        0.        2.        2.        0.        0.        0. 
  316             0.        0.        2.        2.        0.        0.      0.05 
  322  325        0.        0.        2.        2.        0.        0.        0. 
  326             0.        0.        2.        2.        0.        0.      0.05 
  332  335        0.        0.        2.        2.        0.        0.        0. 
  336             0.        0.        2.        2.        0.        0.      0.05 
  342  345        0.        0.        2.        2.        0.        0.        0. 
  346             0.        0.        2.        2.        0.        0.      0.05 
  351  355        0.        0.        2.        2.        0.        0.        0. 
  356             0.        0.        2.        2.        0.        0.      0.05 
  361  365        0.        0.        2.        2.        0.        0.        0. 
  366             0.        0.        2.        2.        0.        0.      0.05 
  371  375        0.        0.        2.        2.        0.        0.        0. 
  376             0.        0.        2.        2.        0.        0.      0.05 
  381  385        0.        0.        2.        2.        0.        0.        0. 
  386             0.        0.        2.        2.        0.        0.      0.05 
  391  395        0.        0.        2.        2.        0.        0.        0. 
  396             0.        0.        2.        2.        0.        0.      0.05 
 181
*** < PLS>    PETMAX    PETMIN    INFEXP    INFILD    DEEPFR    BASETP    AGWETP 
*** x  - x   (deg F)   (deg F) 
  401  415        0.        0.        2.        2.        0.        0.        0. 
  416             0.        0.        2.        2.        0.        0.      0.05 
  421  425        0.        0.        2.        2.        0.        0.        0. 
  426             0.        0.        2.        2.        0.        0.      0.05 
  431  435        0.        0.        2.        2.        0.        0.        0. 
  436             0.        0.        2.        2.        0.        0.      0.05 
  441  445        0.        0.        2.        2.        0.        0.        0. 
  446             0.        0.        2.        2.        0.        0.      0.05 
  451  455        0.        0.        2.        2.        0.        0.        0. 
  456             0.        0.        2.        2.        0.        0.      0.05 
  462  475        0.        0.        2.        2.        0.        0.        0. 
  476             0.        0.        2.        2.        0.        0.      0.05 
  481  485        0.        0.        2.        2.        0.        0.        0. 
  486             0.        0.        2.        2.        0.        0.      0.05 
  491  495        0.        0.        2.        2.        0.        0.        0. 
  496             0.        0.        2.        2.        0.        0.      0.05 
  501  505        0.        0.        2.        2.        0.        0.        0. 
  506             0.        0.        2.        2.        0.        0.      0.05 
  511  515        0.        0.        2.        2.        0.        0.        0. 
  516             0.        0.        2.        2.        0.        0.      0.05 
  521  525        0.        0.        2.        2.        0.        0.        0. 
  526             0.        0.        2.        2.        0.        0.      0.05 
  531  535        0.        0.        2.        2.        0.        0.        0. 
  536             0.        0.        2.        2.        0.        0.      0.05 
  542  545        0.        0.        2.        2.        0.        0.        0. 
  546             0.        0.        2.        2.        0.        0.      0.05 
  551  555        0.        0.        2.        2.        0.        0.        0. 
  556             0.        0.        2.        2.        0.        0.      0.05 
  561  565        0.        0.        2.        2.        0.        0.        0. 
  566             0.        0.        2.        2.        0.        0.      0.05 
  572  575        0.        0.        2.        2.        0.        0.        0. 
  576             0.        0.        2.        2.        0.        0.      0.05 
  581  585        0.        0.        2.        2.        0.        0.        0. 
  586             0.        0.        2.        2.        0.        0.      0.05 
  591  595        0.        0.        2.        2.        0.        0.        0. 
  596             0.        0.        2.        2.        0.        0.      0.05 
  601  605        0.        0.        2.        2.        0.        0.        0. 
  606             0.        0.        2.        2.        0.        0.      0.05 
  611  615        0.        0.        2.        2.        0.        0.        0. 
  616             0.        0.        2.        2.        0.        0.      0.05 
  621  625        0.        0.        2.        2.        0.        0.        0. 
  626             0.        0.        2.        2.        0.        0.      0.05 
PWater – Parameter Set 4 
 
*** <PLS >     CEPSC      UZSN      NSUR     INTFW       IRC     LZETP 
*** x -  x      (in)      (in)                       (1/day) 
   11              0      0.10       0.1       4.0      0.55         0 
   12           0.15      0.10      0.35       4.0      0.55       0.4 
   13            0.1      0.10       0.3       4.0      0.55       0.3 
   14            0.1      0.10       0.2       4.0      0.55       0.1 
   15           0.15      0.10      0.25       4.0      0.55       0.2 
   16            0.1      0.10      0.05       4.0      0.55       0.4 
   21              0      0.10       0.1       4.0      0.55         0 
   22           0.15      0.10      0.35       4.0      0.55       0.4 
   23            0.1      0.10       0.3       4.0      0.55       0.3 
   24            0.1      0.10       0.2       4.0      0.55       0.1 
   25           0.15      0.10      0.25       4.0      0.55       0.2 
   26            0.1      0.10      0.05       4.0      0.55       0.4 
   31              0      0.10       0.1       4.0      0.55         0 
   32           0.15      0.10      0.35       4.0      0.55       0.4 
   33            0.1      0.10       0.3       4.0      0.55       0.3 
   34            0.1      0.10       0.2       4.0      0.55       0.1 
   35           0.15      0.10      0.25       4.0      0.55       0.2 
 182
*** <PLS >     CEPSC      UZSN      NSUR     INTFW       IRC     LZETP 
*** x -  x      (in)      (in)                       (1/day) 
   36            0.1      0.10      0.05       4.0      0.55       0.4 
   41              0      0.10       0.1       4.0      0.55         0 
   42           0.15      0.10      0.35       4.0      0.55       0.4 
   43            0.1      0.10       0.3       4.0      0.55       0.3 
   44            0.1      0.10       0.2       4.0      0.55       0.1 
   45           0.15      0.10      0.25       4.0      0.55       0.2 
   46            0.1      0.10      0.05       4.0      0.55       0.4 
   51              0      0.10       0.1       4.0      0.55         0 
   52           0.15      0.10      0.35       4.0      0.55       0.4 
   53            0.1      0.10       0.3       4.0      0.55       0.3 
   54            0.1      0.10       0.2       4.0      0.55       0.1 
   55           0.15      0.10      0.25       4.0      0.55       0.2 
   56            0.1      0.10      0.05       4.0      0.55       0.4 
   61              0      0.10       0.1       4.0      0.55         0 
   62           0.15      0.10      0.35       4.0      0.55       0.4 
   63            0.1      0.10       0.3       4.0      0.55       0.3 
   64            0.1      0.10       0.2       4.0      0.55       0.1 
   65           0.15      0.10      0.25       4.0      0.55       0.2 
   66            0.1      0.10      0.05       4.0      0.55       0.4 
   71              0      0.10       0.1       4.0      0.55         0 
   72           0.15      0.10      0.35       4.0      0.55       0.4 
   73            0.1      0.10       0.3       4.0      0.55       0.3 
   74            0.1      0.10       0.2       4.0      0.55       0.1 
   75           0.15      0.10      0.25       4.0      0.55       0.2 
   76            0.1      0.10      0.05       4.0      0.55       0.4 
   81              0      0.10       0.1       4.0      0.55         0 
   82           0.15      0.10      0.35       4.0      0.55       0.4 
   83            0.1      0.10       0.3       4.0      0.55       0.3 
   84            0.1      0.10       0.2       4.0      0.55       0.1 
   85           0.15      0.10      0.25       4.0      0.55       0.2 
   86            0.1      0.10      0.05       4.0      0.55       0.4 
   91              0      0.10       0.1       4.0      0.55         0 
   92           0.15      0.10      0.35       4.0      0.55       0.4 
   93            0.1      0.10       0.3       4.0      0.55       0.3 
   94            0.1      0.10       0.2       4.0      0.55       0.1 
   95           0.15      0.10      0.25       4.0      0.55       0.2 
   96            0.1      0.10      0.05       4.0      0.55       0.4 
  101              0      0.10       0.1       4.0      0.55         0 
  102           0.15      0.10      0.35       4.0      0.55       0.4 
  103            0.1      0.10       0.3       4.0      0.55       0.3 
  104            0.1      0.10       0.2       4.0      0.55       0.1 
  105           0.15      0.10      0.25       4.0      0.55       0.2 
  106            0.1      0.10      0.05       4.0      0.55       0.4 
  111              0      0.10       0.1       4.0      0.55         0 
  112           0.15      0.10      0.35       4.0      0.55       0.4 
  113            0.1      0.10       0.3       4.0      0.55       0.3 
  114            0.1      0.10       0.2       4.0      0.55       0.1 
  115           0.15      0.10      0.25       4.0      0.55       0.2 
  116            0.1      0.10      0.05       4.0      0.55       0.4 
  121              0      0.10       0.1       4.0      0.55         0 
  122           0.15      0.10      0.35       4.0      0.55       0.4 
  123            0.1      0.10       0.3       4.0      0.55       0.3 
  124            0.1      0.10       0.2       4.0      0.55       0.1 
  125           0.15      0.10      0.25       4.0      0.55       0.2 
  126            0.1      0.10      0.05       4.0      0.55       0.4 
  131              0      0.10       0.1       4.0      0.55         0 
  132           0.15      0.10      0.35       4.0      0.55       0.4 
  133            0.1      0.10       0.3       4.0      0.55       0.3 
  134            0.1      0.10       0.2       4.0      0.55       0.1 
  135           0.15      0.10      0.25       4.0      0.55       0.2 
  136            0.1      0.10      0.05       4.0      0.55       0.4 
  141              0      0.10       0.1       4.0      0.55         0 
  142           0.15      0.10      0.35       4.0      0.55       0.4 
  143            0.1      0.10       0.3       4.0      0.55       0.3 
  144            0.1      0.10       0.2       4.0      0.55       0.1 
  145           0.15      0.10      0.25       4.0      0.55       0.2 
 183
*** <PLS >     CEPSC      UZSN      NSUR     INTFW       IRC     LZETP 
*** x -  x      (in)      (in)                       (1/day) 
  146            0.1      0.10      0.05       4.0      0.55       0.4 
  151              0      0.10       0.1       4.0      0.55         0 
  152           0.15      0.10      0.35       4.0      0.55       0.4 
  153            0.1      0.10       0.3       4.0      0.55       0.3 
  154            0.1      0.10       0.2       4.0      0.55       0.1 
  155           0.15      0.10      0.25       4.0      0.55       0.2 
  156            0.1      0.10      0.05       4.0      0.55       0.4 
  161              0      0.10       0.1       4.0      0.55         0 
  162           0.15      0.10      0.35       4.0      0.55       0.4 
  163            0.1      0.10       0.3       4.0      0.55       0.3 
  164            0.1      0.10       0.2       4.0      0.55       0.1 
  165           0.15      0.10      0.25       4.0      0.55       0.2 
  166            0.1      0.10      0.05       4.0      0.55       0.4 
  171              0      0.10       0.1       4.0      0.55         0 
  172           0.15      0.10      0.35       4.0      0.55       0.4 
  173            0.1      0.10       0.3       4.0      0.55       0.3 
  174            0.1      0.10       0.2       4.0      0.55       0.1 
  175           0.15      0.10      0.25       4.0      0.55       0.2 
  176            0.1      0.10      0.05       4.0      0.55       0.4 
  181              0      0.10       0.1       4.0      0.55         0 
  182           0.15      0.10      0.35       4.0      0.55       0.4 
  183            0.1      0.10       0.3       4.0      0.55       0.3 
  184            0.1      0.10       0.2       4.0      0.55       0.1 
  185           0.15      0.10      0.25       4.0      0.55       0.2 
  186            0.1      0.10      0.05       4.0      0.55       0.4 
  191              0      0.10       0.1       4.0      0.55         0 
  192           0.15      0.10      0.35       4.0      0.55       0.4 
  193            0.1      0.10       0.3       4.0      0.55       0.3 
  194            0.1      0.10       0.2       4.0      0.55       0.1 
  195           0.15      0.10      0.25       4.0      0.55       0.2 
  196            0.1      0.10      0.05       4.0      0.55       0.4 
  201              0      0.10       0.1       4.0      0.55         0 
  202           0.15      0.10      0.35       4.0      0.55       0.4 
  203            0.1      0.10       0.3       4.0      0.55       0.3 
  204            0.1      0.10       0.2       4.0      0.55       0.1 
  205           0.15      0.10      0.25       4.0      0.55       0.2 
  206            0.1      0.10      0.05       4.0      0.55       0.4 
  211              0      0.10       0.1       4.0      0.55         0 
  212           0.15      0.10      0.35       4.0      0.55       0.4 
  213            0.1      0.10       0.3       4.0      0.55       0.3 
  214            0.1      0.10       0.2       4.0      0.55       0.1 
  215           0.15      0.10      0.25       4.0      0.55       0.2 
  221              0      0.10       0.1       4.0      0.55         0 
  222           0.15      0.10      0.35       4.0      0.55       0.4 
  223            0.1      0.10       0.3       4.0      0.55       0.3 
  224            0.1      0.10       0.2       4.0      0.55       0.1 
  225           0.15      0.10      0.25       4.0      0.55       0.2 
  226            0.1      0.10      0.05       4.0      0.55       0.4 
  231              0      0.10       0.1       4.0      0.55         0 
  232           0.15      0.10      0.35       4.0      0.55       0.4 
  233            0.1      0.10       0.3       4.0      0.55       0.3 
  234            0.1      0.10       0.2       4.0      0.55       0.1 
  235           0.15      0.10      0.25       4.0      0.55       0.2 
  236            0.1      0.10      0.05       4.0      0.55       0.4 
  241              0      0.10       0.1       4.0      0.55         0 
  242           0.15      0.10      0.35       4.0      0.55       0.4 
  243            0.1      0.10       0.3       4.0      0.55       0.3 
  244            0.1      0.10       0.2       4.0      0.55       0.1 
  245           0.15      0.10      0.25       4.0      0.55       0.2 
  246            0.1      0.10      0.05       4.0      0.55       0.4 
  251              0      0.10       0.1       4.0      0.55         0 
  252           0.15      0.10      0.35       4.0      0.55       0.4 
  253            0.1      0.10       0.3       4.0      0.55       0.3 
  254            0.1      0.10       0.2       4.0      0.55       0.1 
  255           0.15      0.10      0.25       4.0      0.55       0.2 
  256            0.1      0.10      0.05       4.0      0.55       0.4 
 184
*** <PLS >     CEPSC      UZSN      NSUR     INTFW       IRC     LZETP 
*** x -  x      (in)      (in)                       (1/day) 
  261              0      0.10       0.1       4.0      0.55         0 
  262           0.15      0.10      0.35       4.0      0.55       0.4 
  263            0.1      0.10       0.3       4.0      0.55       0.3 
  264            0.1      0.10       0.2       4.0      0.55       0.1 
  265           0.15      0.10      0.25       4.0      0.55       0.2 
  271              0      0.10       0.1       4.0      0.55         0 
  272           0.15      0.10      0.35       4.0      0.55       0.4 
  273            0.1      0.10       0.3       4.0      0.55       0.3 
  274            0.1      0.10       0.2       4.0      0.55       0.1 
  275           0.15      0.10      0.25       4.0      0.55       0.2 
  276            0.1      0.10      0.05       4.0      0.55       0.4 
  281              0      0.10       0.1       4.0      0.55         0 
  282           0.15      0.10      0.35       4.0      0.55       0.4 
  283            0.1      0.10       0.3       4.0      0.55       0.3 
  284            0.1      0.10       0.2       4.0      0.55       0.1 
  285           0.15      0.10      0.25       4.0      0.55       0.2 
  286            0.1      0.10      0.05       4.0      0.55       0.4 
  291              0      0.10       0.1       4.0      0.55         0 
  292           0.15      0.10      0.35       4.0      0.55       0.4 
  293            0.1      0.10       0.3       4.0      0.55       0.3 
  294            0.1      0.10       0.2       4.0      0.55       0.1 
  295           0.15      0.10      0.25       4.0      0.55       0.2 
  296            0.1      0.10      0.05       4.0      0.55       0.4 
  301              0      0.10       0.1       4.0      0.55         0 
  302           0.15      0.10      0.35       4.0      0.55       0.4 
  303            0.1      0.10       0.3       4.0      0.55       0.3 
  304            0.1      0.10       0.2       4.0      0.55       0.1 
  305           0.15      0.10      0.25       4.0      0.55       0.2 
  306            0.1      0.10      0.05       4.0      0.55       0.4 
  312           0.15      0.10      0.35       4.0      0.55       0.4 
  313            0.1      0.10       0.3       4.0      0.55       0.3 
  314            0.1      0.10       0.2       4.0      0.55       0.1 
  315           0.15      0.10      0.25       4.0      0.55       0.2 
  316            0.1      0.10      0.05       4.0      0.55       0.4 
  322           0.15      0.10      0.35       4.0      0.55       0.4 
  323            0.1      0.10       0.3       4.0      0.55       0.3 
  324            0.1      0.10       0.2       4.0      0.55       0.1 
  325           0.15      0.10      0.25       4.0      0.55       0.2 
  326            0.1      0.10      0.05       4.0      0.55       0.4 
  332           0.15      0.10      0.35       4.0      0.55       0.4 
  333            0.1      0.10       0.3       4.0      0.55       0.3 
  334            0.1      0.10       0.2       4.0      0.55       0.1 
  335           0.15      0.10      0.25       4.0      0.55       0.2 
  336            0.1      0.10      0.05       4.0      0.55       0.4 
  342           0.15      0.10      0.35       4.0      0.55       0.4 
  343            0.1      0.10       0.3       4.0      0.55       0.3 
  344            0.1      0.10       0.2       4.0      0.55       0.1 
  345           0.15      0.10      0.25       4.0      0.55       0.2 
  346            0.1      0.10      0.05       4.0      0.55       0.4 
  351              0      0.10       0.1       4.0      0.55         0 
  352           0.15      0.10      0.35       4.0      0.55       0.4 
  353            0.1      0.10       0.3       4.0      0.55       0.3 
  354            0.1      0.10       0.2       4.0      0.55       0.1 
  355           0.15      0.10      0.25       4.0      0.55       0.2 
  356            0.1      0.10      0.05       4.0      0.55       0.4 
  361              0      0.10       0.1       4.0      0.55         0 
  362           0.15      0.10      0.35       4.0      0.55       0.4 
  363            0.1      0.10       0.3       4.0      0.55       0.3 
  364            0.1      0.10       0.2       4.0      0.55       0.1 
  365           0.15      0.10      0.25       4.0      0.55       0.2 
  366            0.1      0.10      0.05       4.0      0.55       0.4 
  371              0      0.10       0.1       4.0      0.55         0 
  372           0.15      0.10      0.35       4.0      0.55       0.4 
  373            0.1      0.10       0.3       4.0      0.55       0.3 
  374            0.1      0.10       0.2       4.0      0.55       0.1 
  375           0.15      0.10      0.25       4.0      0.55       0.2 
 185
*** <PLS >     CEPSC      UZSN      NSUR     INTFW       IRC     LZETP 
*** x -  x      (in)      (in)                       (1/day) 
  376            0.1      0.10      0.05       4.0      0.55       0.4 
  381              0      0.10       0.1       4.0      0.55         0 
  382           0.15      0.10      0.35       4.0      0.55       0.4 
  383            0.1      0.10       0.3       4.0      0.55       0.3 
  384            0.1      0.10       0.2       4.0      0.55       0.1 
  385           0.15      0.10      0.25       4.0      0.55       0.2 
  386            0.1      0.10      0.05       4.0      0.55       0.4 
  391              0      0.10       0.1       4.0      0.55         0 
  392           0.15      0.10      0.35       4.0      0.55       0.4 
  393            0.1      0.10       0.3       4.0      0.55       0.3 
  394            0.1      0.10       0.2       4.0      0.55       0.1 
  395           0.15      0.10      0.25       4.0      0.55       0.2 
  396            0.1      0.10      0.05       4.0      0.55       0.4 
  401              0      0.10       0.1       4.0      0.55         0 
  402           0.15      0.10      0.35       4.0      0.55       0.4 
  403            0.1      0.10       0.3       4.0      0.55       0.3 
  404            0.1      0.10       0.2       4.0      0.55       0.1 
  405           0.15      0.10      0.25       4.0      0.55       0.2 
  411              0      0.10       0.1       4.0      0.55         0 
  412           0.15      0.10      0.35       4.0      0.55       0.4 
  413            0.1      0.10       0.3       4.0      0.55       0.3 
  414            0.1      0.10       0.2       4.0      0.55       0.1 
  415           0.15      0.10      0.25       4.0      0.55       0.2 
  416            0.1      0.10      0.05       4.0      0.55       0.4 
  421              0      0.10       0.1       4.0      0.55         0 
  422           0.15      0.10      0.35       4.0      0.55       0.4 
  423            0.1      0.10       0.3       4.0      0.55       0.3 
  424            0.1      0.10       0.2       4.0      0.55       0.1 
  425           0.15      0.10      0.25       4.0      0.55       0.2 
  426            0.1      0.10      0.05       4.0      0.55       0.4 
  431              0      0.10       0.1       4.0      0.55         0 
  432           0.15      0.10      0.35       4.0      0.55       0.4 
  433            0.1      0.10       0.3       4.0      0.55       0.3 
  434            0.1      0.10       0.2       4.0      0.55       0.1 
  435           0.15      0.10      0.25       4.0      0.55       0.2 
  436            0.1      0.10      0.05       4.0      0.55       0.4 
  441              0      0.10       0.1       4.0      0.55         0 
  442           0.15      0.10      0.35       4.0      0.55       0.4 
  443            0.1      0.10       0.3       4.0      0.55       0.3 
  444            0.1      0.10       0.2       4.0      0.55       0.1 
  445           0.15      0.10      0.25       4.0      0.55       0.2 
  446            0.1      0.10      0.05       4.0      0.55       0.4 
  451              0      0.10       0.1       4.0      0.55         0 
  452           0.15      0.10      0.35       4.0      0.55       0.4 
  453            0.1      0.10       0.3       4.0      0.55       0.3 
  454            0.1      0.10       0.2       4.0      0.55       0.1 
  455           0.15      0.10      0.25       4.0      0.55       0.2 
  456            0.1      0.10      0.05       4.0      0.55       0.4 
  462           0.15      0.10      0.35       4.0      0.55       0.4 
  463            0.1      0.10       0.3       4.0      0.55       0.3 
  464            0.1      0.10       0.2       4.0      0.55       0.1 
  465           0.15      0.10      0.25       4.0      0.55       0.2 
  471              0      0.10       0.1       4.0      0.55         0 
  472           0.15      0.10      0.35       4.0      0.55       0.4 
  473            0.1      0.10       0.3       4.0      0.55       0.3 
  474            0.1      0.10       0.2       4.0      0.55       0.1 
  475           0.15      0.10      0.25       4.0      0.55       0.2 
  476            0.1      0.10      0.05       4.0      0.55       0.4 
  481              0      0.10       0.1       4.0      0.55         0 
  482           0.15      0.10      0.35       4.0      0.55       0.4 
  483            0.1      0.10       0.3       4.0      0.55       0.3 
  484            0.1      0.10       0.2       4.0      0.55       0.1 
  485           0.15      0.10      0.25       4.0      0.55       0.2 
  486            0.1      0.10      0.05       4.0      0.55       0.4 
  491              0      0.10       0.1       4.0      0.55         0 
  492           0.15      0.10      0.35       4.0      0.55       0.4 
 186
*** <PLS >     CEPSC      UZSN      NSUR     INTFW       IRC     LZETP 
*** x -  x      (in)      (in)                       (1/day) 
  493            0.1      0.10       0.3       4.0      0.55       0.3 
  494            0.1      0.10       0.2       4.0      0.55       0.1 
  495           0.15      0.10      0.25       4.0      0.55       0.2 
  496            0.1      0.10      0.05       4.0      0.55       0.4 
  501              0      0.10       0.1       4.0      0.55         0 
  502           0.15      0.10      0.35       4.0      0.55       0.4 
  503            0.1      0.10       0.3       4.0      0.55       0.3 
  504            0.1      0.10       0.2       4.0      0.55       0.1 
  505           0.15      0.10      0.25       4.0      0.55       0.2 
  506            0.1      0.10      0.05       4.0      0.55       0.4 
  511              0      0.10       0.1       4.0      0.55         0 
  512           0.15      0.10      0.35       4.0      0.55       0.4 
  513            0.1      0.10       0.3       4.0      0.55       0.3 
  514            0.1      0.10       0.2       4.0      0.55       0.1 
  515           0.15      0.10      0.25       4.0      0.55       0.2 
  516            0.1      0.10      0.05       4.0      0.55       0.4 
  521              0      0.10       0.1       4.0      0.55         0 
  522           0.15      0.10      0.35       4.0      0.55       0.4 
  523            0.1      0.10       0.3       4.0      0.55       0.3 
  524            0.1      0.10       0.2       4.0      0.55       0.1 
  525           0.15      0.10      0.25       4.0      0.55       0.2 
  526            0.1      0.10      0.05       4.0      0.55       0.4 
  531              0      0.10       0.1       4.0      0.55         0 
  532           0.15      0.10      0.35       4.0      0.55       0.4 
  533            0.1      0.10       0.3       4.0      0.55       0.3 
  534            0.1      0.10       0.2       4.0      0.55       0.1 
  535           0.15      0.10      0.25       4.0      0.55       0.2 
  536            0.1      0.10      0.05       4.0      0.55       0.4 
  542           0.15      0.10      0.35       4.0      0.55       0.4 
  543            0.1      0.10       0.3       4.0      0.55       0.3 
  544            0.1      0.10       0.2       4.0      0.55       0.1 
  545           0.15      0.10      0.25       4.0      0.55       0.2 
  546            0.1      0.10      0.05       4.0      0.55       0.4 
  551              0      0.10       0.1       4.0      0.55         0 
  552           0.15      0.10      0.35       4.0      0.55       0.4 
  553            0.1      0.10       0.3       4.0      0.55       0.3 
  554            0.1      0.10       0.2       4.0      0.55       0.1 
  555           0.15      0.10      0.25       4.0      0.55       0.2 
  556            0.1      0.10      0.05       4.0      0.55       0.4 
  561              0      0.10       0.1       4.0      0.55         0 
  562           0.15      0.10      0.35       4.0      0.55       0.4 
  563            0.1      0.10       0.3       4.0      0.55       0.3 
  564            0.1      0.10       0.2       4.0      0.55       0.1 
  565           0.15      0.10      0.25       4.0      0.55       0.2 
  566            0.1      0.10      0.05       4.0      0.55       0.4 
  572           0.15      0.10      0.35       4.0      0.55       0.4 
  573            0.1      0.10       0.3       4.0      0.55       0.3 
  574            0.1      0.10       0.2       4.0      0.55       0.1 
  575           0.15      0.10      0.25       4.0      0.55       0.2 
  576            0.1      0.10      0.05       4.0      0.55       0.4 
  581              0      0.10       0.1       4.0      0.55         0 
  582           0.15      0.10      0.35       4.0      0.55       0.4 
  583            0.1      0.10       0.3       4.0      0.55       0.3 
  584            0.1      0.10       0.2       4.0      0.55       0.1 
  585           0.15      0.10      0.25       4.0      0.55       0.2 
  586            0.1      0.10      0.05       4.0      0.55       0.4 
  591              0      0.10       0.1       4.0      0.55         0 
  592           0.15      0.10      0.35       4.0      0.55       0.4 
  593            0.1      0.10       0.3       4.0      0.55       0.3 
  594            0.1      0.10       0.2       4.0      0.55       0.1 
  595           0.15      0.10      0.25       4.0      0.55       0.2 
  596            0.1      0.10      0.05       4.0      0.55       0.4 
  601              0      0.10       0.1       4.0      0.55         0 
  602           0.15      0.10      0.35       4.0      0.55       0.4 
  603            0.1      0.10       0.3       4.0      0.55       0.3 
  604            0.1      0.10       0.2       4.0      0.55       0.1 
 187
*** <PLS >     CEPSC      UZSN      NSUR     INTFW       IRC     LZETP 
*** x -  x      (in)      (in)                       (1/day) 
  605           0.15      0.10      0.25       4.0      0.55       0.2 
  606            0.1      0.10      0.05       4.0      0.55       0.4 
  611              0      0.10       0.1       4.0      0.55         0 
  612           0.15      0.10      0.35       4.0      0.55       0.4 
  613            0.1      0.10       0.3       4.0      0.55       0.3 
  614            0.1      0.10       0.2       4.0      0.55       0.1 
  615           0.15      0.10      0.25       4.0      0.55       0.2 
  616            0.1      0.10      0.05       4.0      0.55       0.4 
  621              0      0.10       0.1       4.0      0.55         0 
  622           0.15      0.10      0.35       4.0      0.55       0.4 
  623            0.1      0.10       0.3       4.0      0.55       0.3 
  624            0.1      0.10       0.2       4.0      0.55       0.1 
  625           0.15      0.10      0.25       4.0      0.55       0.2 
  626            0.1      0.10      0.05       4.0      0.55       0.4 
PWater – State Parameter Set 
 
*** < PLS>  PWATER state variables (in) 
*** x  - x      CEPS      SURS       UZS      IFWS       LZS      AGWS      GWVS 
   11  626        0.        0.      0.10        0.       6.2      1.66        0. 
 188
LOWER SANDIES 
PWater – Parameter Set 2 
 
*** < PLS>    FOREST      LZSN    INFILT      LSUR     SLSUR     KVARY     AGWRC 
*** x  - x                (in)   (in/hr)      (ft)              (1/in)   (1/day) 
   11              0       6.2      0.01       776     0.077        0.     0.999 
   12   16         0       6.2      0.03       776     0.077        0.     0.999 
   21              0       6.2      0.01       941     0.066        0.     0.999 
   22   26         0       6.2      0.03       941     0.066        0.     0.999 
   32   35         0       6.2      0.03      2816     0.089        0.     0.999 
   41              0       6.2      0.01       745     0.058        0.     0.999 
   42   46         0       6.2      0.03       745     0.058        0.     0.999 
   51              0       6.2      0.01       869     0.047        0.     0.999 
   52   56         0       6.2      0.03       869     0.047        0.     0.999 
   61              0       6.2      0.01       727     0.046        0.     0.999 
   62   66         0       6.2      0.02       727     0.046        0.     0.999 
   71              0       6.2      0.01       889     0.046        0.     0.999 
   72   76         0       6.2      0.02       889     0.046        0.     0.999 
   81              0       6.2      0.01       887      0.05        0.     0.999 
   82   86         0       6.2      0.03       887      0.05        0.     0.999 
   91              0       6.2      0.01      1002     0.051        0.     0.999 
   92   95         0       6.2      0.03      1002     0.051        0.     0.999 
  102  106         0       6.2      0.03       902     0.053        0.     0.999 
  111              0       6.2      0.01      1040     0.055        0.     0.999 
  112  116         0       6.2      0.03      1040     0.055        0.     0.999 
  122  126         0       6.2      0.03       926      0.07        0.     0.999 
  131              0       6.2      0.01       878     0.044        0.     0.999 
  132  136         0       6.2      0.02       878     0.044        0.     0.999 
  141  146         0       6.2      0.01       889      0.03        0.     0.999 
  151  156         0       6.2      0.01       822     0.046        0.     0.999 
  161              0       6.2      0.01      1320      0.04        0.     0.999 
  162  166         0       6.2      0.02      1320      0.04        0.     0.999 
  171              0       6.2      0.01       869     0.035        0.     0.999 
  172  176         0       6.2      0.03       869     0.035        0.     0.999 
  181              0       6.2      0.01      1074     0.031        0.     0.999 
  182  186         0       6.2      0.03      1074     0.031        0.     0.999 
  191  196         0       6.2      0.01       831     0.036        0.     0.999 
  201              0       6.2      0.01       859     0.036        0.     0.999 
  202  206         0       6.2      0.02       859     0.036        0.     0.999 
  211  216         0       6.2      0.01       728     0.051        0.     0.999 
  221              0       6.2      0.01       804     0.039        0.     0.999 
  222  226         0       6.2      0.02       804     0.039        0.     0.999 
  231              0       6.2      0.01       976     0.046        0.     0.999 
  232  236         0       6.2      0.03       976     0.046        0.     0.999 
  242  246         0       6.2      0.03       714     0.036        0.     0.999 
  251  256         0       6.2      0.01       988      0.05        0.     0.999 
  261  266         0       6.2      0.01       915     0.042        0.     0.999 
  271  276         0       6.2      0.01       875     0.032        0.     0.999 
  282  286         0       6.2      0.02      1276     0.059        0.     0.999 
  292  295         0       6.2      0.02      1590     0.041        0.     0.999 
  301  306         0       6.2      0.01       900     0.033        0.     0.999 
  311  315         0       6.2      0.01      1017     0.039        0.     0.999 
  321  326         0       6.2      0.01       808     0.041        0.     0.999 
  331              0       6.2      0.01      1161      0.03        0.     0.999 
  332  336         0       6.2      0.02      1161      0.03        0.     0.999 
  341              0       6.2      0.01      1104     0.036        0.     0.999 
  342  346         0       6.2      0.03      1104     0.036        0.     0.999 
  351              0       6.2      0.01       828     0.048        0.     0.999 
  352  356         0       6.2      0.02       828     0.048        0.     0.999 
  361              0       6.2      0.01      1002      0.04        0.     0.999 
  362  366         0       6.2      0.03      1002      0.04        0.     0.999 
  371              0       6.2      0.01      1513     0.075        0.     0.999 
  372  376         0       6.2      0.02      1513     0.075        0.     0.999 
 189
*** < PLS>    FOREST      LZSN    INFILT      LSUR     SLSUR     KVARY     AGWRC 
*** x  - x                (in)   (in/hr)      (ft)              (1/in)   (1/day) 
  381              0       6.2      0.01      1071      0.04        0.     0.999 
  382  386         0       6.2      0.02      1071      0.04        0.     0.999 
  391              0       6.2      0.01       953     0.047        0.     0.999 
  392  396         0       6.2      0.03       953     0.047        0.     0.999 
  401              0       6.2      0.01       950     0.044        0.     0.999 
  402  406         0       6.2      0.03       950     0.044        0.     0.999 
  412  416         0       6.2      0.03       999     0.054        0.     0.999 
  421              0       6.2      0.01       995     0.051        0.     0.999 
  422  426         0       6.2      0.03       995     0.051        0.     0.999 
  431              0       6.2      0.01       993     0.052        0.     0.999 
  432  436         0       6.2      0.03       993     0.052        0.     0.999 
  441              0       6.2      0.01       845     0.038        0.     0.999 
  442  446         0       6.2      0.03       845     0.038        0.     0.999 
  451              0       6.2      0.01       677     0.042        0.     0.999 
  452  456         0       6.2      0.03       677     0.042        0.     0.999 
 
PWater – Parameter Set 3 
 
*** < PLS>    PETMAX    PETMIN    INFEXP    INFILD    DEEPFR    BASETP    AGWETP 
*** x  - x   (deg F)   (deg F) 
   11   15        0.        0.        2.        2.        0.        0.        0. 
   16             0.        0.        2.        2.        0.        0.      0.05 
   21   25        0.        0.        2.        2.        0.        0.        0. 
   26             0.        0.        2.        2.        0.        0.      0.05 
   32   45        0.        0.        2.        2.        0.        0.        0. 
   46             0.        0.        2.        2.        0.        0.      0.05 
   51   55        0.        0.        2.        2.        0.        0.        0. 
   56             0.        0.        2.        2.        0.        0.      0.05 
   61   65        0.        0.        2.        2.        0.        0.        0. 
   66             0.        0.        2.        2.        0.        0.      0.05 
   71   75        0.        0.        2.        2.        0.        0.        0. 
   76             0.        0.        2.        2.        0.        0.      0.05 
   81   85        0.        0.        2.        2.        0.        0.        0. 
   86             0.        0.        2.        2.        0.        0.      0.05 
   91  105        0.        0.        2.        2.        0.        0.        0. 
  106             0.        0.        2.        2.        0.        0.      0.05 
  111  115        0.        0.        2.        2.        0.        0.        0. 
  116             0.        0.        2.        2.        0.        0.      0.05 
  122  125        0.        0.        2.        2.        0.        0.        0. 
  126             0.        0.        2.        2.        0.        0.      0.05 
  131  135        0.        0.        2.        2.        0.        0.        0. 
  136             0.        0.        2.        2.        0.        0.      0.05 
  141  145        0.        0.        2.        2.        0.        0.        0. 
  146             0.        0.        2.        2.        0.        0.      0.05 
  151  155        0.        0.        2.        2.        0.        0.        0. 
  156             0.        0.        2.        2.        0.        0.      0.05 
  161  165        0.        0.        2.        2.        0.        0.        0. 
  166             0.        0.        2.        2.        0.        0.      0.05 
  171  175        0.        0.        2.        2.        0.        0.        0. 
  176             0.        0.        2.        2.        0.        0.      0.05 
  181  185        0.        0.        2.        2.        0.        0.        0. 
  186             0.        0.        2.        2.        0.        0.      0.05 
  191  195        0.        0.        2.        2.        0.        0.        0. 
  196             0.        0.        2.        2.        0.        0.      0.05 
  201  205        0.        0.        2.        2.        0.        0.        0. 
  206             0.        0.        2.        2.        0.        0.      0.05 
  211  215        0.        0.        2.        2.        0.        0.        0. 
  216             0.        0.        2.        2.        0.        0.      0.05 
  221  225        0.        0.        2.        2.        0.        0.        0. 
  226             0.        0.        2.        2.        0.        0.      0.05 
  231  235        0.        0.        2.        2.        0.        0.        0. 
  236             0.        0.        2.        2.        0.        0.      0.05 
  242  245        0.        0.        2.        2.        0.        0.        0. 
 190
*** < PLS>    PETMAX    PETMIN    INFEXP    INFILD    DEEPFR    BASETP    AGWETP 
*** x  - x   (deg F)   (deg F) 
  246             0.        0.        2.        2.        0.        0.      0.05 
  251  255        0.        0.        2.        2.        0.        0.        0. 
  256             0.        0.        2.        2.        0.        0.      0.05 
  261  265        0.        0.        2.        2.        0.        0.        0. 
  266             0.        0.        2.        2.        0.        0.      0.05 
  271  275        0.        0.        2.        2.        0.        0.        0. 
  276             0.        0.        2.        2.        0.        0.      0.05 
  282  285        0.        0.        2.        2.        0.        0.        0. 
  286             0.        0.        2.        2.        0.        0.      0.05 
  292  305        0.        0.        2.        2.        0.        0.        0. 
  306             0.        0.        2.        2.        0.        0.      0.05 
  311  325        0.        0.        2.        2.        0.        0.        0. 
  326             0.        0.        2.        2.        0.        0.      0.05 
  331  335        0.        0.        2.        2.        0.        0.        0. 
  336             0.        0.        2.        2.        0.        0.      0.05 
  341  345        0.        0.        2.        2.        0.        0.        0. 
  346             0.        0.        2.        2.        0.        0.      0.05 
  351  355        0.        0.        2.        2.        0.        0.        0. 
  356             0.        0.        2.        2.        0.        0.      0.05 
  361  365        0.        0.        2.        2.        0.        0.        0. 
  366             0.        0.        2.        2.        0.        0.      0.05 
  371  375        0.        0.        2.        2.        0.        0.        0. 
  376             0.        0.        2.        2.        0.        0.      0.05 
  381  385        0.        0.        2.        2.        0.        0.        0. 
  386             0.        0.        2.        2.        0.        0.      0.05 
  391  395        0.        0.        2.        2.        0.        0.        0. 
  396             0.        0.        2.        2.        0.        0.      0.05 
  401  405        0.        0.        2.        2.        0.        0.        0. 
  406             0.        0.        2.        2.        0.        0.      0.05 
  412  415        0.        0.        2.        2.        0.        0.        0. 
  416             0.        0.        2.        2.        0.        0.      0.05 
  421  425        0.        0.        2.        2.        0.        0.        0. 
  426             0.        0.        2.        2.        0.        0.      0.05 
  431  435        0.        0.        2.        2.        0.        0.        0. 
  436             0.        0.        2.        2.        0.        0.      0.05 
  441  445        0.        0.        2.        2.        0.        0.        0. 
  446             0.        0.        2.        2.        0.        0.      0.05 
  451  455        0.        0.        2.        2.        0.        0.        0. 
  456             0.        0.        2.        2.        0.        0.      0.05 
 
PWater – Parameter Set 4 
 
*** <PLS >     CEPSC      UZSN      NSUR     INTFW       IRC     LZETP 
*** x -  x      (in)      (in)                       (1/day) 
   11             0.      0.10       0.1       4.0      0.55        0. 
   12           0.15      0.10      0.35       4.0      0.55       0.4 
   13            0.1      0.10       0.3       4.0      0.55       0.3 
   14            0.1      0.10       0.2       4.0      0.55       0.1 
   15           0.15      0.10      0.25       4.0      0.55       0.2 
   16            0.1      0.10      0.05       4.0      0.55       0.4 
   21             0.      0.10       0.1       4.0      0.55        0. 
   22           0.15      0.10      0.35       4.0      0.55       0.4 
   23            0.1      0.10       0.3       4.0      0.55       0.3 
   24            0.1      0.10       0.2       4.0      0.55       0.1 
   25           0.15      0.10      0.25       4.0      0.55       0.2 
   26            0.1      0.10      0.05       4.0      0.55       0.4 
   32           0.15      0.10      0.35       4.0      0.55       0.4 
   33            0.1      0.10       0.3       4.0      0.55       0.3 
   34            0.1      0.10       0.2       4.0      0.55       0.1 
   35           0.15      0.10      0.25       4.0      0.55       0.2 
   41             0.      0.10       0.1       4.0      0.55        0. 
   42           0.15      0.10      0.35       4.0      0.55       0.4 
   43            0.1      0.10       0.3       4.0      0.55       0.3 
 191
*** <PLS >     CEPSC      UZSN      NSUR     INTFW       IRC     LZETP 
*** x -  x      (in)      (in)                       (1/day) 
   44            0.1      0.10       0.2       4.0      0.55       0.1 
   45           0.15      0.10      0.25       4.0      0.55       0.2 
   46            0.1      0.10      0.05       4.0      0.55       0.4 
   51             0.      0.10       0.1       4.0      0.55        0. 
   52           0.15      0.10      0.35       4.0      0.55       0.4 
   53            0.1      0.10       0.3       4.0      0.55       0.3 
   54            0.1      0.10       0.2       4.0      0.55       0.1 
   55           0.15      0.10      0.25       4.0      0.55       0.2 
   56            0.1      0.10      0.05       4.0      0.55       0.4 
   61             0.      0.10       0.1       4.0      0.55        0. 
   62           0.15      0.10      0.35       4.0      0.55       0.4 
   63            0.1      0.10       0.3       4.0      0.55       0.3 
   64            0.1      0.10       0.2       4.0      0.55       0.1 
   65           0.15      0.10      0.25       4.0      0.55       0.2 
   66            0.1      0.10      0.05       4.0      0.55       0.4 
   71             0.      0.10       0.1       4.0      0.55        0. 
   72           0.15      0.10      0.35       4.0      0.55       0.4 
   73            0.1      0.10       0.3       4.0      0.55       0.3 
   74            0.1      0.10       0.2       4.0      0.55       0.1 
   75           0.15      0.10      0.25       4.0      0.55       0.2 
   76            0.1      0.10      0.05       4.0      0.55       0.4 
   81             0.      0.10       0.1       4.0      0.55        0. 
   82           0.15      0.10      0.35       4.0      0.55       0.4 
   83            0.1      0.10       0.3       4.0      0.55       0.3 
   84            0.1      0.10       0.2       4.0      0.55       0.1 
   85           0.15      0.10      0.25       4.0      0.55       0.2 
   86            0.1      0.10      0.05       4.0      0.55       0.4 
   91             0.      0.10       0.1       4.0      0.55        0. 
   92           0.15      0.10      0.35       4.0      0.55       0.4 
   93            0.1      0.10       0.3       4.0      0.55       0.3 
   94            0.1      0.10       0.2       4.0      0.55       0.1 
   95           0.15      0.10      0.25       4.0      0.55       0.2 
  102           0.15      0.10      0.35       4.0      0.55       0.4 
  103            0.1      0.10       0.3       4.0      0.55       0.3 
  104            0.1      0.10       0.2       4.0      0.55       0.1 
  105           0.15      0.10      0.25       4.0      0.55       0.2 
  106            0.1      0.10      0.05       4.0      0.55       0.4 
  111             0.      0.10       0.1       4.0      0.55        0. 
  112           0.15      0.10      0.35       4.0      0.55       0.4 
  113            0.1      0.10       0.3       4.0      0.55       0.3 
  114            0.1      0.10       0.2       4.0      0.55       0.1 
  115           0.15      0.10      0.25       4.0      0.55       0.2 
  116            0.1      0.10      0.05       4.0      0.55       0.4 
  122           0.15      0.10      0.35       4.0      0.55       0.4 
  123            0.1      0.10       0.3       4.0      0.55       0.3 
  124            0.1      0.10       0.2       4.0      0.55       0.1 
  125           0.15      0.10      0.25       4.0      0.55       0.2 
  126            0.1      0.10      0.05       4.0      0.55       0.4 
  131             0.      0.10       0.1       4.0      0.55        0. 
  132           0.15      0.10      0.35       4.0      0.55       0.4 
  133            0.1      0.10       0.3       4.0      0.55       0.3 
  134            0.1      0.10       0.2       4.0      0.55       0.1 
  135           0.15      0.10      0.25       4.0      0.55       0.2 
  136            0.1      0.10      0.05       4.0      0.55       0.4 
  141             0.      0.10       0.1       4.0      0.55        0. 
  142           0.15      0.10      0.35       4.0      0.55       0.4 
  143            0.1      0.10       0.3       4.0      0.55       0.3 
  144            0.1      0.10       0.2       4.0      0.55       0.1 
  145           0.15      0.10      0.25       4.0      0.55       0.2 
  146            0.1      0.10      0.05       4.0      0.55       0.4 
  151             0.      0.10       0.1       4.0      0.55        0. 
  152           0.15      0.10      0.35       4.0      0.55       0.4 
  153            0.1      0.10       0.3       4.0      0.55       0.3 
  154            0.1      0.10       0.2       4.0      0.55       0.1 
  155           0.15      0.10      0.25       4.0      0.55       0.2 
  156            0.1      0.10      0.05       4.0      0.55       0.4 
 192
*** <PLS >     CEPSC      UZSN      NSUR     INTFW       IRC     LZETP 
*** x -  x      (in)      (in)                       (1/day) 
  161             0.      0.10       0.1       4.0      0.55        0. 
  162           0.15      0.10      0.35       4.0      0.55       0.4 
  163            0.1      0.10       0.3       4.0      0.55       0.3 
  164            0.1      0.10       0.2       4.0      0.55       0.1 
  165           0.15      0.10      0.25       4.0      0.55       0.2 
  166            0.1      0.10      0.05       4.0      0.55       0.4 
  171             0.      0.10       0.1       4.0      0.55        0. 
  172           0.15      0.10      0.35       4.0      0.55       0.4 
  173            0.1      0.10       0.3       4.0      0.55       0.3 
  174            0.1      0.10       0.2       4.0      0.55       0.1 
  175           0.15      0.10      0.25       4.0      0.55       0.2 
  176            0.1      0.10      0.05       4.0      0.55       0.4 
  181             0.      0.10       0.1       4.0      0.55        0. 
  182           0.15      0.10      0.35       4.0      0.55       0.4 
  183            0.1      0.10       0.3       4.0      0.55       0.3 
  184            0.1      0.10       0.2       4.0      0.55       0.1 
  185           0.15      0.10      0.25       4.0      0.55       0.2 
  186            0.1      0.10      0.05       4.0      0.55       0.4 
  191             0.      0.10       0.1       4.0      0.55        0. 
  192           0.15      0.10      0.35       4.0      0.55       0.4 
  193            0.1      0.10       0.3       4.0      0.55       0.3 
  194            0.1      0.10       0.2       4.0      0.55       0.1 
  195           0.15      0.10      0.25       4.0      0.55       0.2 
  196            0.1      0.10      0.05       4.0      0.55       0.4 
  201             0.      0.10       0.1       4.0      0.55        0. 
  202           0.15      0.10      0.35       4.0      0.55       0.4 
  203            0.1      0.10       0.3       4.0      0.55       0.3 
  204            0.1      0.10       0.2       4.0      0.55       0.1 
  205           0.15      0.10      0.25       4.0      0.55       0.2 
  206            0.1      0.10      0.05       4.0      0.55       0.4 
  211             0.      0.10       0.1       4.0      0.55        0. 
  212           0.15      0.10      0.35       4.0      0.55       0.4 
  213            0.1      0.10       0.3       4.0      0.55       0.3 
  214            0.1      0.10       0.2       4.0      0.55       0.1 
  215           0.15      0.10      0.25       4.0      0.55       0.2 
  216            0.1      0.10      0.05       4.0      0.55       0.4 
  221             0.      0.10       0.1       4.0      0.55        0. 
  222           0.15      0.10      0.35       4.0      0.55       0.4 
  223            0.1      0.10       0.3       4.0      0.55       0.3 
  224            0.1      0.10       0.2       4.0      0.55       0.1 
  225           0.15      0.10      0.25       4.0      0.55       0.2 
  226            0.1      0.10      0.05       4.0      0.55       0.4 
  231             0.      0.10       0.1       4.0      0.55        0. 
  232           0.15      0.10      0.35       4.0      0.55       0.4 
  233            0.1      0.10       0.3       4.0      0.55       0.3 
  234            0.1      0.10       0.2       4.0      0.55       0.1 
  235           0.15      0.10      0.25       4.0      0.55       0.2 
  236            0.1      0.10      0.05       4.0      0.55       0.4 
  242           0.15      0.10      0.35       4.0      0.55       0.4 
  243            0.1      0.10       0.3       4.0      0.55       0.3 
  244            0.1      0.10       0.2       4.0      0.55       0.1 
  245           0.15      0.10      0.25       4.0      0.55       0.2 
  246            0.1      0.10      0.05       4.0      0.55       0.4 
  251             0.      0.10       0.1       4.0      0.55        0. 
  252           0.15      0.10      0.35       4.0      0.55       0.4 
  253            0.1      0.10       0.3       4.0      0.55       0.3 
  254            0.1      0.10       0.2       4.0      0.55       0.1 
  255           0.15      0.10      0.25       4.0      0.55       0.2 
  256            0.1      0.10      0.05       4.0      0.55       0.4 
  261             0.      0.10       0.1       4.0      0.55        0. 
  262           0.15      0.10      0.35       4.0      0.55       0.4 
  263            0.1      0.10       0.3       4.0      0.55       0.3 
  264            0.1      0.10       0.2       4.0      0.55       0.1 
  265           0.15      0.10      0.25       4.0      0.55       0.2 
  266            0.1      0.10      0.05       4.0      0.55       0.4 
  271             0.      0.10       0.1       4.0      0.55        0. 
 193
*** <PLS >     CEPSC      UZSN      NSUR     INTFW       IRC     LZETP 
*** x -  x      (in)      (in)                       (1/day) 
  272           0.15      0.10      0.35       4.0      0.55       0.4 
  273            0.1      0.10       0.3       4.0      0.55       0.3 
  274            0.1      0.10       0.2       4.0      0.55       0.1 
  275           0.15      0.10      0.25       4.0      0.55       0.2 
  276            0.1      0.10      0.05       4.0      0.55       0.4 
  282           0.15      0.10      0.35       4.0      0.55       0.4 
  283            0.1      0.10       0.3       4.0      0.55       0.3 
  284            0.1      0.10       0.2       4.0      0.55       0.1 
  285           0.15      0.10      0.25       4.0      0.55       0.2 
  286            0.1      0.10      0.05       4.0      0.55       0.4 
  292           0.15      0.10      0.35       4.0      0.55       0.4 
  293            0.1      0.10       0.3       4.0      0.55       0.3 
  294            0.1      0.10       0.2       4.0      0.55       0.1 
  295           0.15      0.10      0.25       4.0      0.55       0.2 
  301             0.      0.10       0.1       4.0      0.55        0. 
  302           0.15      0.10      0.35       4.0      0.55       0.4 
  303            0.1      0.10       0.3       4.0      0.55       0.3 
  304            0.1      0.10       0.2       4.0      0.55       0.1 
  305           0.15      0.10      0.25       4.0      0.55       0.2 
  306            0.1      0.10      0.05       4.0      0.55       0.4 
  311             0.      0.10       0.1       4.0      0.55        0. 
  312           0.15      0.10      0.35       4.0      0.55       0.4 
  313            0.1      0.10       0.3       4.0      0.55       0.3 
  314            0.1      0.10       0.2       4.0      0.55       0.1 
  315           0.15      0.10      0.25       4.0      0.55       0.2 
  321             0.      0.10       0.1       4.0      0.55        0. 
  322           0.15      0.10      0.35       4.0      0.55       0.4 
  323            0.1      0.10       0.3       4.0      0.55       0.3 
  324            0.1      0.10       0.2       4.0      0.55       0.1 
  325           0.15      0.10      0.25       4.0      0.55       0.2 
  326            0.1      0.10      0.05       4.0      0.55       0.4 
  331             0.      0.10       0.1       4.0      0.55        0. 
  332           0.15      0.10      0.35       4.0      0.55       0.4 
  333            0.1      0.10       0.3       4.0      0.55       0.3 
  334            0.1      0.10       0.2       4.0      0.55       0.1 
  335           0.15      0.10      0.25       4.0      0.55       0.2 
  336            0.1      0.10      0.05       4.0      0.55       0.4 
  341             0.      0.10       0.1       4.0      0.55        0. 
  342           0.15      0.10      0.35       4.0      0.55       0.4 
  343            0.1      0.10       0.3       4.0      0.55       0.3 
  344            0.1      0.10       0.2       4.0      0.55       0.1 
  345           0.15      0.10      0.25       4.0      0.55       0.2 
  346            0.1      0.10      0.05       4.0      0.55       0.4 
  351             0.      0.10       0.1       4.0      0.55        0. 
  352           0.15      0.10      0.35       4.0      0.55       0.4 
  353            0.1      0.10       0.3       4.0      0.55       0.3 
  354            0.1      0.10       0.2       4.0      0.55       0.1 
  355           0.15      0.10      0.25       4.0      0.55       0.2 
  356            0.1      0.10      0.05       4.0      0.55       0.4 
  361             0.      0.10       0.1       4.0      0.55        0. 
  362           0.15      0.10      0.35       4.0      0.55       0.4 
  363            0.1      0.10       0.3       4.0      0.55       0.3 
  364            0.1      0.10       0.2       4.0      0.55       0.1 
  365           0.15      0.10      0.25       4.0      0.55       0.2 
  366            0.1      0.10      0.05       4.0      0.55       0.4 
  371             0.      0.10       0.1       4.0      0.55        0. 
  372           0.15      0.10      0.35       4.0      0.55       0.4 
  373            0.1      0.10       0.3       4.0      0.55       0.3 
  374            0.1      0.10       0.2       4.0      0.55       0.1 
  375           0.15      0.10      0.25       4.0      0.55       0.2 
  376            0.1      0.10      0.05       4.0      0.55       0.4 
  381             0.      0.10       0.1       4.0      0.55        0. 
  382           0.15      0.10      0.35       4.0      0.55       0.4 
  383            0.1      0.10       0.3       4.0      0.55       0.3 
  384            0.1      0.10       0.2       4.0      0.55       0.1 
  385           0.15      0.10      0.25       4.0      0.55       0.2 
 194
*** <PLS >     CEPSC      UZSN      NSUR     INTFW       IRC     LZETP 
*** x -  x      (in)      (in)                       (1/day) 
  386            0.1      0.10      0.05       4.0      0.55       0.4 
  391             0.      0.10       0.1       4.0      0.55        0. 
  392           0.15      0.10      0.35       4.0      0.55       0.4 
  393            0.1      0.10       0.3       4.0      0.55       0.3 
  394            0.1      0.10       0.2       4.0      0.55       0.1 
  395           0.15      0.10      0.25       4.0      0.55       0.2 
  396            0.1      0.10      0.05       4.0      0.55       0.4 
  401             0.      0.10       0.1       4.0      0.55        0. 
  402           0.15      0.10      0.35       4.0      0.55       0.4 
  403            0.1      0.10       0.3       4.0      0.55       0.3 
  404            0.1      0.10       0.2       4.0      0.55       0.1 
  405           0.15      0.10      0.25       4.0      0.55       0.2 
  406            0.1      0.10      0.05       4.0      0.55       0.4 
  412           0.15      0.10      0.35       4.0      0.55       0.4 
  413            0.1      0.10       0.3       4.0      0.55       0.3 
  414            0.1      0.10       0.2       4.0      0.55       0.1 
  415           0.15      0.10      0.25       4.0      0.55       0.2 
  416            0.1      0.10      0.05       4.0      0.55       0.4 
  421             0.      0.10       0.1       4.0      0.55        0. 
  422           0.15      0.10      0.35       4.0      0.55       0.4 
  423            0.1      0.10       0.3       4.0      0.55       0.3 
  424            0.1      0.10       0.2       4.0      0.55       0.1 
  425           0.15      0.10      0.25       4.0      0.55       0.2 
  426            0.1      0.10      0.05       4.0      0.55       0.4 
  431             0.      0.10       0.1       4.0      0.55        0. 
  432           0.15      0.10      0.35       4.0      0.55       0.4 
  433            0.1      0.10       0.3       4.0      0.55       0.3 
  434            0.1      0.10       0.2       4.0      0.55       0.1 
  435           0.15      0.10      0.25       4.0      0.55       0.2 
  436            0.1      0.10      0.05       4.0      0.55       0.4 
  441             0.      0.10       0.1       4.0      0.55        0. 
  442           0.15      0.10      0.35       4.0      0.55       0.4 
  443            0.1      0.10       0.3       4.0      0.55       0.3 
  444            0.1      0.10       0.2       4.0      0.55       0.1 
  445           0.15      0.10      0.25       4.0      0.55       0.2 
  446            0.1      0.10      0.05       4.0      0.55       0.4 
  451             0.      0.10       0.1       4.0      0.55        0. 
  452           0.15      0.10      0.35       4.0      0.55       0.4 
  453            0.1      0.10       0.3       4.0      0.55       0.3 
  454            0.1      0.10       0.2       4.0      0.55       0.1 
  455           0.15      0.10      0.25       4.0      0.55       0.2 
  456            0.1      0.10      0.05       4.0      0.55       0.4 
PWater – Parameter Set 4 
 
*** < PLS>  PWATER state variables (in) 
*** x  - x      CEPS      SURS       UZS      IFWS       LZS      AGWS      GWVS 
   11  456        0.        0.      0.10        0.       6.2      1.66        0. 
 
 195
Abbreviations 
AGWRC Active Groundwater Evapotranspiration 
ARM Agricultural Runoff Management model 
BASETP Base Evapotranspiration 
BASINS Better Assessment Science Integrating point and Nonpoint Sources 
CEPSC Rainfall Vegetation Interception 
CFS Cubic Feet per Second 
CRP Clean Rivers Program 
CWA Clean Water Act 
DAYMET DAilY METeorological 
DEEPFR Deep Recharge Fraction 
DOD Department Of Defense 
ECTF East Central Texas Forests 
EPA Environmental Protection Agency 
FTABLE Function TABLE 
GBRA Guadalupe-Blanco River Authority 
GenScn Scenario Generator 
HRAP Hydrologic Rainfall Analysis Project 
HSP HydroComp Simulation Program 
HSPF Hydrologic Simulation Program - FORTRAN 
IDW Inverse Distance Weighted 
IMPLND Impervious Land Segment 
INFEXP Infiltration Exponent 
INFILD Infiltration max to mean ratio 
 196
INFILT Index to Mean Soil Infiltration Rate 
IRC Interflow Recession Parameter 
KVARY Variable Groundwater Recession 
LSUR Length of Overland Flow Plane 
LZETP Lower Zone Evapotranspiration 
LZSN Lower Zone Numerical Soil Moisture Storage  
MGD Million Gallons per Day 
NAD27 North American Datum 1927 
NAD83 North American Datum 1983 
NCAR National Center for Atmospheric Research 
NCDC National Climate Data Center 
NCEP National Center for Environmental Prediction 
NED National Elevation Dataset 
NEXRAD Next Generation RADAR 
NGVD29 National Geodetic Vertical Datum 1929 
NHD National Hydrography Dataset 
NLCD National Land Cover Data 
NOAA National Oceanic and Atmospheric Administration 
NPS Nonpoint Source Pollutant loading model 
NSUR Manning’s n for Overland Flow Plane 
NTSG Numerical Terradynamic Simulation Group 
NWIS National Water Information System 
NWS National Weather Service 
PERLND Pervious Land Segment 
RCHRES Reach 
 197
SLSUR Slope of Overland Flow Path 
SSURGO Soil Survey Geographic 
STATSGO State Soil Geographic 
TCEQ Texas Commission for Environmental Quality 
TMDL Total Mass Daily Load 
uci User Control Input 
UGRA Upper Guadalupe River Authority 
USGS United States Geological Survey 
UZSN Nominal Upper Zone Soil Moisture Storage 
WGRFC West Gulf River Forecast Center 
 
 198
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Vita 
 
Jessica Luttrell Watts was born Jessica Lynn Luttrell to Marjorie Floyd Luttrell 
and Henry H. Luttrell on October 27, 1973 in Baton Rouge, Louisiana.  After completing 
her work at Germantown High School in Germantown, Tennessee she enrolled at 
Vanderbilt University in Nashville, Tennessee.  After two years she transferred to 
Christian Brothers University (CBU) in Memphis, Tennessee.  During her undergraduate 
college career she was chapter President of the CBU ASCE and a member of Tau Beta Pi 
honor society.  She graduated Magna Cum Laude and was awarded the Outstanding Civil 
Engineering Graduate from Christian Brothers University in May 1996.  After graduation 
she began her professional career working at Buchart-Horn, Inc. in Memphis, Tennessee.  
She also became an active member and officer of the local chapter of TSPE.  In February 
of 2000 she was awarded the chapter’s Young Engineer of the Year award.  In December 
of 2000 she married Alex B. Watts.  She began working with Cavanaugh and Associates, 
P.A. in Asheville, North Carolina in November 2001.  She received her professional 
engineer’s license from Tennessee in January 2002.  In September 2004 she began her 
graduate school career in Environmental and Water Resources at the University of Texas 
at Austin.  She and Alex have two children, Gabriel and Holly. 
 
Permanent address: 1610 Wilson Street, Bastrop, Texas 78602 
 
This thesis was typed by the author.