U.S. Department of the Interior

U.S. Geological Survey

Prepared in cooperation with the Texas State Soil and Water Conservation Board

Linkage of the Soil and Water Assessment Tool and the Texas 

Water Availability Model to Simulate the Effects of Brush 

Management on Monthly Storage of Canyon Lake, SouthCentral Texas, 1995–2010

Scientific Investigations Report 2013–5239
Cover, Upstream from bridge at U.S. Geological Survey streamflow-gaging station 08167500 Guadalupe 

River near Spring Branch, Texas, dated July 11, 2011, provided by USGS staff.
Linkage of the Soil and Water Assessment 

Tool and the Texas Water Availability 

Model to Simulate the Effects of Brush 

Management on Monthly Storage of 

Canyon Lake, South-Central Texas, 

1995–2010

By William H. Asquith and Johnathan R. Bumgarner

Prepared in cooperation with the Texas State Soil and Water Conservation Board

Scientific Investigations Report 2013–5239

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

SALLY JEWELL, Secretary

U.S. Geological Survey

Suzette M. Kimball, Acting Director

U.S. Geological Survey, Reston, Virginia: 2014

Suggested citation:

Asquith, W.H., and Bumgarner, J.R., 2014, Linkage of the Soil and Water Assessment Tool and the Texas Water 

Availability Model to simulate the effects of brush management on monthly storage of Canyon Lake, southcentral Texas, 1995–2010: U.S. Geological Survey Scientific Investigations Report 2013–5239, 25 p., http://dx.doi.

org/10.3133/sir20135239. 

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U.S. Government.

Although this information product, for the most part, is in the public domain, it also may contain copyrighted materials 

as noted in the text. Permission to reproduce copyrighted items must be secured from the copyright owner.

ISSN 2328-031X (print)

ISSN 2328-0328 (online)

ISBN 978-1-4113-3749-7
iii

Contents

Abstract ..........................................................................................................................................................1

Introduction ....................................................................................................................................................2

Purpose and Scope .............................................................................................................................3

Study Area Description .......................................................................................................................4

Select Features and History of Canyon Lake ..................................................................................4

Linkage Between the Soil and Water Assessment Tool and Water Availability Model ...................7

Functional Description of the Soil and Water Assessment Tool ..................................................7

Functional Description of the Texas Water Availability Model ....................................................8

Linkage of the Soil and Water Assessment Tool to the Water Availability Model for 

the Upper Guadalupe River Watershed ............................................................................10

Conceptual Depiction of the Soil and Water Assessment Tool-Water Availability 

Model Linkage ..............................................................................................................10

Implemented Soil and Water Assessment Tool-Water Availability Model 

Linkage ..........................................................................................................................10

Linkage of the Upper Guadalupe River Soil and Water Assessment Tool and the Texas 

Water Availability Model to Simulate the Effects of Brush Management ...........................13

Extensive Brush-Management Scenarios (Treatable Ashe Juniper) .......................................13

Relative (Between Scenario to Baseline) Effects of Extensive Brush-Management 

Scenarios ...............................................................................................................................15

Total Inflow to Canyon Lake, 1995–2010 ................................................................................18

Monthly Storage of Canyon Lake, 1974–89 (synthetic) from Extensive BrushManagement Scenarios .............................................................................................18

Discussion of Result Sensitivity ......................................................................................................20

Summary .......................................................................................................................................................20

References ...................................................................................................................................................23

Appendixes (available online only at http://pubs.usgs.gov/sir/2013/5239/)

1. Supplemental Information and External Data Files of Total Monthly Inflow to 

Canyon Lake from Six Soil and Water Assessment Tool Scenarios of Extensive 

Brush Management for the Upper Guadalupe River Watershed, South-Central 

Texas, 1995–2010

2. Supplemental Information and External Data Files of Monthly Storage from 

the Guadalupe River Water Availability Model for Canyon Lake, South-Central 

Texas, 1974–89 (synthetic)

3. Supplemental Information and Computations for Select Comparisons to Results 

of U.S. Geological Survey Scientific Investigations Report 2012–5051
iv

Figures

1. Map showing location of the Guadalupe River Basin, including the upper 

Guadalupe River watershed study area, south-central Texas .............................................5

2. Map showing location of U.S. Geological Survey streamflow-gaging station

 08167500 Guadalupe River near Spring Branch, Texas, and other geographic 

features of the upper Guadalupe River watershed, south-central Texas ..........................6

3. Map showing subbasin delineation of the upper Guadalupe River watershed 

by Bumgarner and Thompson (2012) with subbasin identified by number used 

for the Soil and Water Availability Tool and Water Availability Model linkage .................9

4. Glossary/Nomenclature/Description of the aggregation of the Soil and Water 

Assessment Tool for the upper Guadalupe River watershed to create total 

monthly inflow to Canyon Lake, Comal County, Texas .........................................................11

5. Glossary/Nomenclature/Description of the linkage between the upper 

Guadalupe River Soil and Water Assessment Tool and Guadalupe River Water 

Availability Model (WAM) to create total monthly inflow to Canyon Lake, Comal 

County, Texas, suitable for substitution into the input-flow file of the Guadalupe 

River WAM ..................................................................................................................................12

6. National Land Cover Database 2006 land-cover categories in the upper 

Guadalupe River watershed, south-central Texas................................................................14

7. Graph showing relation between cumulative volume and time for total monthly 

inflow to Canyon Lake as simulated by Soil and Water Assessment Tool (SWAT), 

which includes main stem of Guadalupe River and peripheral drainage to 

Canyon Lake ...............................................................................................................................16

8. Graph showing relation between monthly storage and time of Canyon Lake 

determined by using Soil and Water Assessment Tool (SWAT) output shown in 

figure 7 as (1974–89, synthetic) input to the Guadalupe River Water Availability 

Model (WAM) at control point 2 (CP02, U.S. Geological Survey streamflowgaging station 08167500 Guadalupe River near Spring Branch, Texas, figs. 2 

and 3) for the period 1995–2010 ...............................................................................................17
v

Conversion Factors

Inch/Pound to SI

Multiply By To obtain

Length

inch (in.) 2.54 centimeter (cm)

foot (ft) 0.3048 meter (m)

mile (mi) 1.609 kilometer (km)

Area

acre 0.4047 hectare (ha)

square mile (square miles) 2.590 square kilometer (km2) 

Volume

gallon (gal) 3.785 liter (L) 

gallon (gal) 3.0689 × 10-6 acre-foot (acre-ft)

cubic foot (ft3) 0.02832 cubic meter (m3) 

acre-foot (acre-ft) 0.001233 cubic hectometer (hm3) 

Flow rate

acre-foot per year (acre-ft/year) 1,233 cubic meter per year (m3/yr)

cubic foot per second (ft3/s) 0.02832 cubic meter per second (m3/s)

gallon per day (gal/d) 0.003785 cubic meter per day (m3/d)

SI to Inch/Pound

Multiply By To obtain

Length

millimeter (mm) 0.03937 inch (in.)

meter (m) 3.281 foot (ft) 

Temperature in degrees Celsius (°C) may be converted to degrees Fahrenheit (°F) as follows:

°F=(1.8×°C)+32

Temperature in degrees Fahrenheit (°F) may be converted to degrees Celsius (°C) as follows:

°C=(°F-32)/1.8

Vertical coordinate information is referenced to the North American Vertical Datum of 1988 

(NAVD 88).

Horizontal coordinate information is referenced to the Texas Centric Mapping System–Albers 

Equal Area Projection, North American Datum of 1983 (NAD 83). 

Altitude, as used in this report, refers to distance above the vertical datum.

Linkage of the Soil and Water Assessment Tool and the 

Texas Water Availability Model to Simulate the Effects of 

Brush Management on Monthly Storage of Canyon Lake, 

South-Central Texas, 1995–2010

By William H. Asquith and Johnathan R. Bumgarner

Abstract 

The U.S. Geological Survey (USGS), in cooperation with 

the Texas State Soil and Water Conservation Board, developed 

and applied an approach to create a linkage between the 

published upper Guadalupe River Soil Water Assessment 

Tool (SWAT) brush-management (ashe juniper [Juniperus 

ashei]) model and the full authorization version Guadalupe 

River Water Availability Model (WAM). The SWAT model 

was published by the USGS, and the Guadalupe River WAM 

is available from the Texas Commission on Environmental 

Quality (TCEQ). The upper Guadalupe River watershed is a 

substantial component of the Guadalupe River WAM. This 

report serves in part as documentation of a proof of concept on 

the feasibility of linking these two water-resources planning 

models for the purpose of simulating possible increases in 

water storage in Canyon Lake as a result of different brushmanagement scenarios.

The SWAT-WAM linkage for the upper Guadalupe 

River is documented with a principal objective to evaluate 

the distributional characteristics of the monthly water storage 

of Canyon Lake during selected drought conditions. Focus is 

on the relative evaluation of select scenarios of large-scale or 

“extensive” brush management within the upper Guadalupe 

River watershed. There are six SWAT simulations for the 

upper Guadalupe River watershed that include a baseline 

(0-percent management of treatable ashe juniper, the baseline 

scenario from a previous study in which no percentage of 

ashe juniper is numerically replaced with grassland) along 

with five scenarios (extensions of SWAT simulations from 

a previous study) of 20-, 40-, 60-, 80-, and 100-percent 

random (numerical) replacement of treatable ashe juniper with 

grasslands throughout the upper Guadalupe River watershed in 

south-central Texas.

SWAT is a process-based, semidistributed, waterbalance model designed to predict the effects of landscape 

management decisions on water yields. A watershed is 

subdivided into subbasins, and each subbasin is associated 

with a single reach on the stream network. In general a WAM, 

such as the Guadalupe River WAM, provides analysis of 

generalized water rights in a river and reservoir framework. 

A WAM accommodates hydrology and water usage through 

several input files containing water rights, watershed 

parameters, and naturalized streamflow time series. A WAM 

is generalized for application to rivers and reservoir systems, 

and input datasets are uniquely developed for a river basin of 

concern.

The extractions of SWAT output for the five extensive 

brush-management and baseline scenarios were offset by 

−21 years and, in general, the results were then mapped to 

the WAM input-flow file. The offset of −21 years was chosen 

arbitrarily for technical reasons and means that the period 

of monthly record 1995–2010 of the upper Guadalupe River 

SWAT became the synthetic period of monthly record 1974–

89, hereinafter 1974–89 (synthetic) period, of the Guadalupe 

River WAM.

The relative (between scenario to baseline) effects of 

extensive brush-management scenarios by using the SWATWAM linkage were evaluated, and two critical intermediate 

results were total inflow to Canyon Lake from 1995 to 2010 

and the monthly storage of Canyon Lake from 1974 to 1989 

(synthetic). The first quartile or lower 25th percentile of 

monthly storage of Canyon Lake for the baseline scenario 

is 381,000 acre-feet (acre-ft) for the hereinafter 1974–89 

(synthetic) period. This lower quartile was chosen for analysis 

for two critical purposes. First, Canyon Lake is managed 

with a conservation pool of about 386,200 acre-ft capacity 

(as recognized by the WAM) and is at or near conservation 

capacity about 50 percent or more of the time; further, there 

is intrinsic data censoring that occurs for the monthly storage 

distribution because Canyon Lake is at or near conservation 

pool elevation the majority of the time. This intrinsic 

censoring has the effect of creating a bounded distribution 

with a left or low-volume tail. Statistical assessment of the 

brush-management scenarios beginning with the 381,000 

acre-ft censoring threshold provides readily interpretable 

results. Second, the quantification of brush management 

during periods lacking abundant rainfall, which were 

defined in this study as months for which Canyon Lake 
2 Linkage of SWAT and Texas WAM to Simulate the Effects of Brush Management on Monthly Storage

storage was below the 25th percentile for the simulation 

period, are of substantial interest to water-resource 

managers and stakeholders in the context of water-supply 

enhancement.

A statistical assessment of the SWAT-WAM linkage for 

the low-volume tail of the distribution of monthly storage 

of Canyon Lake is the focus of analysis and interpretation. 

Drought periods for the analysis are defined as the months 

(consecutive or not) during which Canyon Lake is below the 

25th percentile of storage (381,000 acre-ft) for the baseline 

scenario. Such months are referred to as being within the 

“Drought Quartile.” The Drought Quartile is a conceptual 

and heuristically determined waypoint for the analysis and 

is not related to any administrative definition of drought by 

stakeholders or policy makers.

The five scenarios and the baseline scenario simulated in 

the upper Guadalupe River SWAT were all passed through the 

Guadalupe River WAM by the SWAT-WAM linkage described 

in this report. A comparison of the mean increase per month in 

reservoir storage for Canyon Lake conditioned for the Drought 

Quartile was made. For each of the five brush-management 

and baseline scenarios, the months with storage below 381,000 

acre-ft were extracted. The mean monthly storages during the 

Drought Quartile were computed for each of the five scenarios 

and the baseline scenario. The mean of the baseline scenario 

was 376,458 acre-ft and subsequently was subtracted from the 

mean monthly storage during the Drought Quartile for each of 

the five scenarios.

The mean monthly offset storages of Canyon Lake 

during the Drought Quartile were 110 acre-ft (20 percent); 

448 acre-ft (40 percent); 754 acre-ft (60 percent); 1,080 acre-ft 

(80 percent); and 1,090 acre-ft (100 percent). A particular 

mean was interpreted as follows: the value of 754 acre-ft 

for the 60-percent brush-management scenario implies that, 

on average, this scenario indicates an additional 754 acre-ft 

per month of storage in Canyon Lake relative to the baseline 

during the Drought Quartile. All of the five scenarios resulted 

in an increase on average to water supply relative to the 

baseline scenario during the Drought Quartile through the 

SWAT-WAM linkage.

Introduction

The selective or managed removal of woody plants 

(brush management of nonherbaceous and nonsucculent 

plants) in an effort to potentially increase or enhance water 

availability for downstream water bodies is a conservation 

practice being used in Texas (Natural Resources Conservation 

Service, 2009; Texas State Soil and Water Conservation 

Board, 2013). Brush management efforts attempt to enhance 

landscape and watershed function for purposes that include 

(1) creation of desirable (native) plant communities, 

(2) control of erosion, (3) improvements to water quality, 

(4) enhancement of streamflow, (5) improvement of fish and 

wildlife habitats, (6) enhancement of forage accessibility, and 

(7) management of the loading of vegetative fuel attributable 

to wildfire generation and propagation (Natural Resources 

Conservation Service, 2009). Certain species of woody plants 

have encroached into semiarid grasslands and savannas 

throughout Texas (Humphrey, 1958; Archer and others, 1988; 

Archer, 1989). Woody plant encroachment can decrease 

groundwater recharge and streamflow through processes such 

as increases in evapotranspiration and canopy interception of 

rainfall. Evapotranspiration enhances soil-moisture depletion 

and can reduce deeper infiltration to water tables. Canopy 

interception of rainfall provides less water for soil moisture by 

enhancing evaporation (Archer and others, 1995; Dugas and 

others, 1998; Van Auken, 2000; Wilcox, 2002; Huxman and 

others, 2005; Wilcox and Thurow, 2006; Musgrove and others, 

2010; Banta and Slattery, 2011).

Ashe juniper (Juniperus ashei) is a species of woody 

plant that has spread beyond its historical range within the 

understories of prairie oak motte (small stands) and within 

sheltered canyons in south-central Texas. Primary reasons 

for ashe juniper encroachment into nonhistorical landscape 

settings include overgrazing and fire suppression (Smeins, 

1980; Fuhlendorf and others, 1996; Fuhlendorf and others, 

1997). Studies of the water use of ashe juniper indicated 

that the species might intercept and subsequently enhance 

evaporation as well as generally use more water than native 

grasses use (Young and others, 1984; Owens, 1996; Baxter, 

2009; Saleh and others, 2009; Banta and Slattery, 2011).

Brush management is primarily intended to increase 

water yields from managed land parcels (Natural Resources 

Conservation Service, 2009; Texas State Soil and Water 

Conservation Board, 2013). The Texas State Soil and 

Water Conservation Board (TSSWCB) Water Supply 

Enhancement Program supports brush management in Texas 

with a primary objective to increase streamflow delivery to 

downstream water-supply sources (Texas State Soil and Water 

Conservation Board, 2013). Brush-management feasibility 

studies using numerical watershed models can help identify 

locations of especially efficacious brush-management potential 

in a particular watershed.

Bumgarner and Thompson (2012) conducted a feasibility 

study for brush management in the upper Guadalupe River 

watershed by using the Soil and Water Assessment Tool 

(SWAT) (Arnold and others, 1998), which is a type of 

numerical watershed model. The study documented by 

Bumgarner and Thompson (2012) was done in cooperation 

with the TSSWCB and the Upper Guadalupe River Authority. 

SWAT simulations by Bumgarner and Thompson (2012) 

were made by using select scenarios of treatable brush 

management (the numerical replacement of ashe juniper with 

grasslands), and the possible effects of brush management on 

streamflow for the lower part of the upper Guadalupe River 

watershed were computed. Bumgarner and Thompson (2012) 

simulated changes in streamflow as a result of treatable brush 

management for 23 scenarios.
Introduction 3

The Water for Texas 2012 State Water Plan (Texas 

Water Development Board, 2011, p. 196, section 7.2.5 “Other 

Strategies”) states that:

Brush control and other land stewardship techniques 

have been recommended for many areas in the 

western half of the state. Removing [ashe] juniper 

and other water consuming species has been shown 

in studies to restore springflow and improve surface 

water runoff in some cases. However, [because] 

water produced by this strategy during a drought 

when little rainfall occurs is difficult to quantify, 

it is not often recommended as a strategy to meet 

municipal needs. Brush control is recommended to 

supply approximately 19,000 acre-feet per year in 

all decades between 2010 and 2060.

The volume of water produced by statewide brush 

management in Texas can be roughly estimated at about 

19,000 acre-feet per year (acre-ft/year). This value is crudely 

derived from generalization and scaling-up of results 

from small-scale investigations (for example, Banta and 

Slattery, 2011). The 19,000 acre-ft/year volume represents 

only 0.2 percent of the total water volume gained by the 

implementation of other recommended strategies (Texas 

Water Development Board, 2011, p. 189 and 191, table 7.2), 

compared to, for example, 33.9 percent from other surface 

water resources and (or) projects, 16.7 percent from irrigation 

conservation, and 2.0 percent from groundwater desalination.

In an effort to refine estimates of water-supply 

enhancement potential by ashe juniper management in the 

upper Guadalupe River watershed, the USGS, in cooperation 

with the TSSWCB, developed and applied an approach to 

create a linkage between straightforward extensions of the 

upper Guadalupe River SWAT feasibility study by Bumgarner 

and Thompson (2012) and the Guadalupe River Water 

Availability Model (WAM). The Guadalupe River WAM 

is available from the Texas Commission on Environmental 

Quality (2013). The Guadalupe River WAM term used here 

refers to the WAM for both the Guadalupe River Basin (lower 

and upper basins split at Canyon Lake) and San Antonio River 

Basin. The upper Guadalupe River watershed is a substantial 

component of the Guadalupe River WAM. The primary 

purpose of a WAM (Wurbs, 2011) is to make predictions about 

the amount of water available in a stream (or lake or reservoir) 

at a specific control point for specific points in time. A WAM 

operates under a specified set of voluminous time series data 

and suite of parameters. In 2013, water-resource regulators 

and availability planners often used WAMs along with the 

contributions of the water-resources engineering and scientific 

community in Texas to evaluate the suitability of requested 

water rights or amendments to existing water rights.

Purpose and Scope

The primary purpose of this report is to document upper 

Guadalupe River watershed streamflow and Canyon Lake 

storage simulations obtained by linking the SWAT model 

documented by Bumgarner and Thompson (2012) with the 

Guadalupe River WAM documented by the Texas Commission 

on Environmental Quality (2013) (hereinafter the SWATWAM linkage). This report serves in part as documentation 

of a proof of concept on the feasibility of linking these 

two water-resources planning models to simulate possible 

increases in water storage in Canyon Lake as a result of 

different brush-management scenarios. The distributional 

characteristics (mean, median, lower quartile) of 16 years of 

simulated monthly storage of Canyon Lake were evaluated 

for different scenarios of large-scale or extensive brush 

management within the upper Guadalupe River watershed. 

There are six SWAT simulations including a baseline scenario 

and five alternative scenarios. In the baseline scenario, none 

of the treatable ashe juniper is replaced with grasslands (that 

is, 0-percent management of treatable ashe juniper, the same 

baseline scenario used by Bumgarner and Thompson [2012]). 

The five alternative scenarios replicate the SWAT simulations 

by Bumgarner and Thompson (2012) of 20-, 40-, 60-, 80-, and 

100-percent random (numerical) replacement of treatable ashe 

juniper with grasslands throughout the upper Guadalupe River 

watershed. Text files of (1) the total monthly inflow to Canyon 

Lake from the baseline and five extensive brush-management 

scenarios emanating from the upper Guadalupe River SWAT 

(app. 1) and (2) the resultant monthly reservoir storage of 

Canyon Lake computed by the Guadalupe River WAM 

(app. 2) are included with the report.

The upper Guadalupe River SWAT by Bumgarner 

and Thompson (2012) has a period of monthly record of 

1995–2010 (January through December), whereas the official 

Guadalupe River WAM has a period of monthly record of 

1934–89 (January through December), so the time periods 

of the two models do not overlap. To force a time overlap 

(artificially link in time) in SWAT and WAM, an ad hoc 

postsimulation offset was chosen to move SWAT output back 

21 years to temporally align the upper Guadalupe River SWAT 

output by respective months with the period 1974–89 of the 

Guadalupe River WAM. A mitigating factor for concerns of 

time-offset sensitivity to the results herein is that the analysis 

is oriented around relative as opposed to absolute magnitude 

numerical assessment of extensive brush-management 

scenarios in the upper Guadalupe River watershed.

The scope of this investigation is restricted to the full 

authorization version Guadalupe River WAM, which reflects 

specific details of water-rights allocations, permits, and other 

subtle circumstances by TCEQ and the water management 

community in Texas. In perhaps simplest terms, full 

authorization means that the full authorization of water rights 

(use) has been enabled by staff of the TCEQ. The baseline 

and five extensive brush-management scenarios for the upper 

Guadalupe River SWAT were passed into a slightly modified 

version of the full authorization Guadalupe River WAM. Only 

Canyon Lake storage was extracted from the voluminous 

WAM output file for the period 1974–89 (synthetic) and 

evaluated. The adjective synthetic will be explained in detail 

in the “Functional Description of the Texas Water Availability 

Model” section of this report. 
4 Linkage of SWAT and Texas WAM to Simulate the Effects of Brush Management on Monthly Storage

Study Area Description

The Guadalupe River Basin extends about 230 miles 

(mi) from its headwaters in the Edwards Plateau in southcentral Texas to San Antonio Bay near Tivoli, Tex., and has 

a total drainage area of about 10,200 square miles (mi2). The 

Guadalupe River Basin and surrounding geographic features 

are shown in figure 1. The study area for this investigation is 

the upper Guadalupe River watershed and represents about 

1,432 mi2 of the Guadalupe River Basin upstream from the 

Canyon Lake dam.

The study area encompasses parts of Bandera, Blanco, 

Comal, Gillespie, Kendall, Kerr, and Real Counties in southcentral Texas. The largest city in the study area is Kerrville, 

Tex., which had a population of 22,347 in 2010 (U.S. Census 

Bureau, 2011). The study area is depicted in further detail in 

figure 2. The study area has a subtropical, subhumid climate 

characterized by hot summers and mild winters (Larkin and 

Bomar, 1983).

The study area is located in a karst topographic region 

formed by the dissolution of Cretaceous-age carbonate rocks 

(U.S. Geological Survey, 2006). Karst regions generally are 

characterized by complex and prolific groundwater-to-surfacewater interconnections, such as rapidly losing or gaining 

streams, sinkholes, and springs (Katz and others, 1997; Winter 

and others, 1998). Land cover in the upper Guadalupe River 

watershed is dominated by shrubland and evergreen forest 

(Texas Parks and Wildlife Department, 2013). Soils generally 

are shallow, calcareous clay and clay loam with rocky 

outcrops (Natural Resources Conservation Service, 2011). 

Elevation in the watershed ranges from about 900 to 2,400 feet 

(Gesch, 2007), and land slopes vary from 0 to greater than 60 

percent.

Particularly pertinent to this investigation is USGS 

streamflow-gaging station 08167500 Guadalupe River 

near Spring Branch, Tex. (hereinafter the Spring Branch 

streamgage; see figs. 1 and 2). Three major tributaries of 

the Guadalupe River—Rebecca Creek, Jentsch Creek, and 

Tom Creek—are each downstream from the Spring Branch 

streamgage and are either near-upstream or direct tributaries 

to Canyon Lake (figs. 1 and 2). The watersheds for the three 

creeks are named within the Guadalupe River WAM and 

represent specific control points. Adjustments to parameters 

within the WAM for these watersheds and unnamed drainages 

were needed for computational consistency of water-budget 

equations to implement the SWAT-WAM linkage.

Select Features and History of Canyon Lake

Because Canyon Lake is the water-supply reservoir in 

the study area, the monthly storage of Canyon Lake and select 

statistical characteristics thereof are analytical endpoints of 

this investigation. Canyon Lake is a run-of-river reservoir 

formed by Canyon Dam. The impounded reservoir supplies 

water for municipal water supply, irrigation, and industrial 

uses as well as for operation of several small hydroelectric 

plants. At conservation pool, Canyon Lake has a published 

capacity of about 382,000 acre-feet (acre-ft) (Texas Water 

Development Board, 2001), a surface area of about 13 mi2, 

and a shoreline of about 80 mi (U.S. Army Corps of 

Engineers, 2013). Data tables for Canyon Lake within the 

WAM numerically recognize the conservation storage as 

386,200 acre-ft (Texas Commission on Environmental Quality, 

2013) as opposed to 382,000 acre-ft, and this larger value is 

used to minimize the number of parameters in the WAM that 

needed to be modified.

The U.S. Army Corps of Engineers (2013) provide an 

informative and relevant history of Canyon Lake,

In the early part of the 20th century, the lower 

Guadalupe River Basin [downstream from] the 

current location of Canyon Lake had been especially 

subject to serious flooding. [Because of] the need to 

lower the flooding issues, Congress authorized the 

construction of Canyon Lake Dam. The dam and 

lake [were] to serve two purposes: flood control and 

water conservation.

Construction of Canyon Dam began in 1958 on mile 

303 of the Guadalupe River [upstream from the 

mouth]. The dam was finish[ed] in 1964 and water 

impoundment began. The lake was dedicated in 

1966. The lake filled to conservation pool level by 

1968. Canyon Dam controls floods originating on 

the [approximately] 1,432 square miles of drainage 

above the dam. Flood protection is provided to 

[approximately] 157,250 acres of land downstream 

from the dam.

The high canyons of the upper Guadalupe have a 

channel capacity of 40,000–50,000 cubic feet per 

second. The channel on the lower Guadalupe River 

has a capacity of only 13,000–30,000 cubic feet per 

second. [The lowering of channel capacity by the 

geomorphic features of the channel in the upper and 

lower watersheds is] the cause of prior flood events 

before the dam construction. 

At conservation pool level Canyon Lake has a 

capacity of 382,000 acre-feet. At flood control 

pool level[,] the lake has an additional capacity 

of 346,000 acre-feet making total storage 

[approximately] 728,400 acre-feet.
Figure 1. Location of the Guadalupe River Basin, including the upper Guadalupe River watershed study area, south-central Texas (Bumgarner and T

Fredericksburg

San

Antonio

Austin

Kerrville

San

Marcos

New

Braunfels

Seguin

Victoria

§ ̈¦10

§ ̈¦35

§ ̈¦35

§ ̈¦10

§ ̈¦37

97°

98°

99°

100°

30°

29°

TRAVIS

BLANCO COUNTY

COUNTY

GILLESPIE

COUNTY

BASTROP

COUNTY

HAYS

COUNTY

KERR

COUNTY

FAYETTE

COUNTY

KENDALL

COUNTY

CALDWELL

COUNTY

REAL

COUNTY

BANDERA

COUNTY

GUADALUPE

COUNTY

GONZALES

COUNTY

LAVACA

COUNTY

WILSON

COUNTY

DEWITT

COUNTY

ARANSAS COUNTY

BEXAR

COUNTY

KARNES

COUNTY

GOLIAD

COUNTY

VICTORIA COUNTY

REFUGIO COUNTY

COMAL

 COUNTY

Blanco River

Guadalupe

River

River

Gulf of Mexico San Antonio Bay Antonio Bay

Canyon

Lake

San Marcos

Tivoli

CALHOUN

COUNTY

Guadalupe River

Guadalupe River C

TE

Study area 

Edwards 

Plateau

Base modified from U.S. Geological Survey 1:100,000-scale digital dataTexas Centric Mapping System–Albers Equal Area projection North American Datum of 1983

EXPLANATION

Upper Guadalupe River watershedGuadalupe River watershed boundary (Natural  Resources Conservation Service, 2012)City boundaryU.S. Geological Survey streamflow-gaging station 08167500 Guadalupe River near Spring Branch, Texas

C

0 35 70 MILE

0 35 70 KILOMETERS
Figure 2. Location of U.S. Geological Survey streamflow-gaging station 08167500 Guadalupe River near Spring Branch, Texas, and other geographic Guadalupe River watershed, south-central Texas (modified from Bumgarner and Thompson, 2012, fig. 2).

§ ̈¦10

£¤27

£¤16

£¤27

£¤16

£¤281

£¤290

98°30'

99°

99°30'

30°10'

30°

29°50'

C

Guadalupe

River

Guadalupe

River

C

EXPLANATION

Upper Guadalupe River watershed U.S. Geological Survey streamflow- 08167500 Guadalupe River near S

00

10 20 MILES

10 20 KILOMETERS

Base modified from U.S. Geological Survey 1:100,000-scale digital dataTexas Centric Mapping System–Albers Equal Area projection North American Datum of 1983

North Fork Guadalupe River North Fork Guadalupe River

South Fork Guadalupe

River

South Fork Guadalupe

River

GILLESPIE COUNTY 

KERR COUNTY

KENDALL COUNTY

BANDERA COUNTY

BEXAR COUNTY

REAL

COUNTY

Fredericksburg

Kerrville

Ingram

Boerne

Bulverd

Blanco

Comfort

Spring

Branch

Hunt

Center

Point

Bandera

Medina

Harper

Sisterdale

Kendalia

Camp Verde

Cottonwood

Fredericksburg

Kerrville

Ingram

Boerne

Bulverd

Blanco

Comfort

Spring

Branch

Hunt

Center

Point

Bandera

Medina

Harper

Sisterdale

Kendalia

Camp Verde

Cottonwood Ranch

Bankersmith

RebeccRebecc C 

reek
Linkage Between the Soil and Water Assessment Tool and Water Availability Model 7

The Texas Water Development Board (2001, table 1) 

performed a volumetric survey for Canyon Lake. The 

conservation storage values by year reported by the Texas 

Water Development Board (2001, table 1) were 386,200 

acre-ft in 1952, prior to dam construction; 382,000 acre-ft 

in 1972; and 378,852 acre-ft in 2000. The general decrease 

in storage can be attributed to sedimentation. The 2001 

volumetric survey of Canyon Lake reports that a 0.1-foot 

change in elevation of the water surface is associated with 

a change of storage of about 828 acre-ft (381,329–380,501 

acre-ft) at storage conditions around 381,000 acre-ft, and 

these storage conditions represent an approximate 13-mi2

surface area (Texas Water Development Board, 2001, p. 18, 

appendix A). The 381,000-acre-ft storage condition and 

the 828 acre-ft per 0.1-foot change have prominence for 

interpretation of results herein. 

Linkage Between the Soil and 

Water Assessment Tool and Water 

Availability Model 

This section is divided into two parts: (1) the previously 

developed SWAT and WAM models are described, and (2) the 

linkage between SWAT and WAM is described. Each part 

provides a functional description of the independent and 

application-specific models (SWAT and WAM) germane to 

this investigation. Background information and a functional 

description of SWAT are provided based on the description by 

Bumgarner and Thompson (2012) followed by a functional 

description of the Guadalupe River WAM. Specific input and 

output files of the Guadalupe River WAM are identified along 

with a description of the functional purpose of each file of 

the WAM.

Functional Description of the Soil and Water 

Assessment Tool

This section is modified from Bumgarner and Thompson 

(2012, p. 6). SWAT (Arnold and others, 1998) is a processbased, semidistributed water-balance model designed to 

predict the effects of landscape management decisions on 

water, sediment, and agricultural chemical yields. Within 

SWAT, a watershed is subdivided into subbasins, and each 

subbasin is associated with a single reach on the stream 

network. As summarized by Garcia (2009), each subbasin 

is further divided into hydrologic response units (HRUs) 

that consist of unique combinations of land cover, soil 

characteristics, land slope, and land-management criteria. 

Processes including but not limited to surface runoff, 

evapotranspiration, base flow, channel transmission losses, 

plant life cycles, nutrient cycling, and constituent transport can 

be simulated for each HRU. The numerical aspects of these 

processes are determined by the process-related parameter 

values uniquely defined for each HRU (Arnold and others, 

1998; Garcia, 2009; Neitsch and others, 2011a). 

During model development, default values are assigned 

to the model parameters by the modeling software based on 

the unique HRU characteristics. The simulated water volumes 

are aggregated within their corresponding subbasins, are 

allocated to the subbasin reach, and exit a subbasin through 

outlets along the stream network. Algorithms in SWAT 

account for watershed and in-stream processes and include 

routing of streamflows from upstream subbasins downstream 

to watershed outlets (Arnold and others, 1998; Garcia, 2009; 

Neitsch and others, 2011a).

Model output includes streamflow for any subbasin outlet 

and specific aggregations thereof. The HRUs are delineated 

in the SWAT model from the input data and user-specified 

parameters. The analyst assigns default parameter values and 

then completes the calibration process by adjusting selected 

parameters to achieve a level of quantified uncertainty and 

sensitivity (Bumgarner and Thompson, 2012). A complete 

description of SWAT and simulated processes are identified in 

Neitsch and others (2011a).

The hydrologic component of SWAT uses a runoff curvenumber (CN) equation described by the Natural Resources 

Conservation Service (Soil Conservation Service, 1986). The 

CN equation is heuristically based and relates runoff potential 

to land-cover and soil-type characteristics. A high CN near the 

upper limit of 100 translates into substantial runoff, whereas 

a low CN near the lower limit of 0 translates into almost no 

runoff. For example, forested land cover, such as ashe juniper, 

has a lower CN than grasslands and produces less runoff (Soil 

Conservation Service, 1986).

In an empirical study of rainfall and runoff for small 

watersheds in Texas, Thompson and others (2003) provided 

a critical review of CN applications for high-magnitude 

streamflow computations that are oriented around the needs 

of transportation infrastructure design engineers. The CNs 

are used within regression equations by Asquith and Roussel 

(2007) for estimation of initial abstraction and constant loss 

parameters for rainfall-runoff modeling involving the unit 

hydrograph in applicable areas of Texas.

Daily CN values for SWAT application in Bumgarner and 

Thompson (2012) and in this investigation were calculated 

in the model as a function of plant evapotranspiration instead 

of the standard or default computation in SWAT. The default 

computation is a function of soil moisture (Neitsch and others, 

2011b). Daily CNs, when calculated as a function of soil 

moisture, have a tendency to overestimate runoff (Neitsch 

and others, 2011b) in watersheds with shallow soils. The 

watershed of the upper Guadalupe River watershed generally 

has shallow soils (Natural Resources Conservation Service, 

2011) and substantial spatial and temporal variation in soil 

moisture.
8 Linkage of SWAT and Texas WAM to Simulate the Effects of Brush Management on Monthly Storage

The variation of SWAT used for this investigation 

was the program SWAT2009.exe (revision 445). The 

upper Guadalupe River SWAT encompasses the period of 

monthly record 1995–2010 (January through December). In 

general, the SWAT program can be executed from within a 

geographic information system (GIS), which incorporates 

spatially distributed data. For this investigation, ArcGIS 9.3.1 

(Environmental Systems Research Institute, Inc., 2009) and 

the ArcGIS extension ArcSWAT (version 2009.93.5) (Winchell 

and others, 2010) were used to execute SWAT. Description 

of SWAT and simulations presented in this report can be 

conceptually replicated by following the model-development 

steps described in the user manual of ArcSWAT (Winchell and 

others, 2010).

A complete description of the upper Guadalupe River 

SWAT can be found in Bumgarner and Thompson (2012). 

The subbasins and their respective identification numbers 

are the same as in the Bumgarner and Thompson (2012) 

identification scheme (fig. 3). It is important to note that the 

model reaches in figure 3 represent a trimmed stream network 

compared to the streams shown in figure 2. The trimmed 

stream network reflects the conceptual reaches within SWAT. 

Each subbasin has a reach associated within it, and the reach 

has the same number as the subbasin. The subbasins including 

and downstream from the Spring Branch streamgage (fig. 3) 

require special attention for the SWAT-WAM linkage and are 

identified by a red color scheme in the figure. Two reaches 

within Subbasins 85 and 58 are pertinent.

Functional Description of the Texas Water 

Availability Model

Wurbs and Lee (2011, p. 451) provided a concise 

description of the WAM purpose and framework. Wurbs and 

Lee stated:

The Texas Commission on Environmental Quality 

(TCEQ), in collaboration with the Texas water 

management community, maintains a Water 

Availability Modeling (WAM) System used in the 

administration of the state’s water rights permit 

system, regional and statewide planning, and 

other activities (Wurbs, 2004). The TCEQ WAM 

System consists of the generalized Water Rights 

Analysis Package (WRAP) river/reservoir system 

water management simulation model and WRAP 

hydrology and water rights input files for the 23 

river basins of Texas. The WRAP modeling system 

is generalized for application to river/reservoir 

systems located anywhere in the world, with input 

datasets being developed for the particular river 

basin of concern. For WRAP simulation studies 

assessing water availability and supply reliability in 

Texas, readily available TCEQ WAM System data 

files are altered as appropriate to reflect proposed 

water management plans of interest. These plans 

could involve changes in water use or reservoir 

system operating practices, construction of new 

facilities, or other water management strategies.

The Guadalupe River WAM encompasses the period 

of January through December monthly streamflow records 

during 1934–89. For this investigation, only the monthly 

computation steps of the WAM were used; daily computations 

were not used. The entire 1934–89 period was used for 

each model run of the WAM. Three files of the WAM are 

germane to this investigation. The file names, where gsa

means Guadalupe-San Antonio River Basins and run3 has 

no special interpretation for this investigation and reflects 

nomenclature by TCEQ, are gsa_run3.inf (inflow-text 

file), gsa_run3.dis (text file containing watershed drainage 

areas and numerous other parameters that are not germane 

to this investigation), and gsa_run3.out (text file created 

by the WAM software that contains the modeled monthly 

reservoir storage of Canyon Lake). To accomplish the SWATWAM linkage objective of this investigation, only slight 

modifications to the WAM file gsa_run3.dis were made; the 

modifications were restricted to four drainage-area parameters 

of the Guadalupe River WAM as described in the section of 

this report titled “Linkage of the Soil and Water Assessment 

Tool to the Water Availability Model for the Upper Guadalupe 

River Watershed.” 

SWAT output files were extracted for five extensive 

brush-management and baseline scenarios and offset by 

−21 years. The offset of −21 years means that the period of 

monthly streamflow record during 1995–2010 of the upper 

Guadalupe River SWAT becomes the synthetic period of 

monthly streamflow record during 1974–89, hereinafter the 

1974–89 (synthetic) period, for the Guadalupe River WAM. 

The results then are “mapped to” (a term that evokes the 

mathematical notation that was used) the WAM input-flow 

file. The total monthly inflows to Canyon Lake are the most 

salient results of SWAT simulations and are available as text 

files for download as described in appendix 1 from the on-line 

version of this report. The total monthly inflow files provided 

in appendix 1 show the 1995–2010 period because this is 

the actual, or true, time period of input data, calibration, and 

simulations by the upper Guadalupe River SWAT previously 

calibrated by Bumgarner and Thompson (2012). 
Figure 3. Subbasin delineation of the upper Guadalupe River watershed by Bumgarner and Thompson (2012) with subbasin identified by number useAvailability Tool and Water Availability Model linkage (modified from Bumgarner and Thompson, 2012, fig. 3).

98°30'

99°

99°30'

30°10'

30°

29°50'

GILLESPIE COUNTY 

KERR COUNTY

KENDALL COUNTY

BANDERA COUNTY

BEXAR COUNTY

REAL

COUNTY

Base modified from U.S. Geological Survey 1:100,000-scale digital dataTexas Centric Mapping System–Albers Equal Area projection North American Datum of 1983

72

#

EXPLANATION

Model subbasin and numbers by Bumga where green numbers are not germa described in figure 4Upper Guadalupe River watershed bounBumgarner and Thompson (2012) stream U.S. Geological Survey streamflow-gag 08167500 Guadalupe River near Sprin

or 64

0 10 20 MILES

0 10 20 KILOMETERS

North Fork Guadalupe River North Fork Guadalupe River

South Fork

Guadalupe

River

South Fork

Guadalupe

River

#

72

52

1

46

56 48

8

45 28

37

29

38

44

83

6

93

24

75

35

42

3

49

22

14

31

7

16

71

53

57

60

55

5

34

12

61 47

64

92

33

50

25

89

9

88

51

10

26

23

43

39

27

32

30

54

15

11

40

41

19

20

85

5

36

76

13

21

4

18 17

2

72

52

1

46

56 48

8

45 28

37

29

38

44

83

6

93

24

75

35

42

3

49

22

14

31

7

16

71

53

57

60

55

5

34

12

61 47

64

92

33

50

25

89

9

88

51

10

26

23

43

39

27

32

30

54

15

11

40

41

19

20

85

5

36

76

13

21

4

18 17

2

Guadalupe

River

Guadalupe

River
10 Linkage of SWAT and Texas WAM to Simulate the Effects of Brush Management on Monthly Storage

Linkage of the Soil and Water Assessment Tool 

to the Water Availability Model for the Upper 

Guadalupe River Watershed

Conceptual Depiction of the Soil and Water 

Assessment Tool-Water Availability Model 

Linkage

Separate discussions of (1) the conceptual design and 

preprocessing (this section) and (2) presetup (next section 

titled “Implemented Soil and Water Assessment Tool-Water 

Availability Model Linkage”) are provided. The conceptual 

design establishes the necessary preprocessing of SWAT 

output files in the context of the hierarchical structure of 

SWAT output and the format required for WAM input. The 

principal objective of the preprocessing of SWAT output is to 

aggregate or combine the streamflows (reach files) or subbasin 

output into a total monthly inflow to Canyon Lake in acrefeet and format the streamflow aggregation into a format that 

is compatible with subsequent executions of the Guadalupe 

River WAM.

Two major plain-text output files result from a SWAT 

simulation: (1) reach streamflow (RCH) files and (2) subbasin 

output flow (SUB) files. Each output file type (RCH and 

SUB files) for the upper Guadalupe River SWAT are 

individually voluminous for a given brush-management 

scenario. The RCH and SUB nomenclature for this 

investigation parallels the watershed subdivisions by 

Bumgarner and Thompson (2012).

Monthly streamflow totals extracted from the SWAT 

model for the part of the Guadalupe River watershed 

monitored by the Spring Branch streamgage (Bumgarner and 

Thompson, 2012) were used as the initial input for calibration 

purposes. The Spring Branch streamgage is coincident with 

Reach 85 (RCH85) of the SWAT model, which resides 

in Subbasin 85 (SUB85), and RCH85 values for a single 

simulation scenario were extracted from the RCH file by using 

a script written in the Perl programming language.

The streamflow in RCH58 must equate to the streamflow 

in RCH85 (as measured at the Spring Branch streamgage) 

when RCH85 streamflow is added to the streamflows 

from subbasins SUB61, SUB64, and SUB88 of the SWAT 

(Bumgarner and Thompson, 2012). A diagram and additional 

description are shown in figure 4. The SUB values for a 

single simulation scenario for subbasins SUB61, SUB64, and 

SUB88 were extracted from the SUB file, and streamflow 

in RCH85 subsequently was summed by using a second 

Perl programming language script to process SUB files. The 

reliability of the two Perl scripts was confirmed by comparing 

the summation RCH85 + SUB61 + SUB64 + SUB88 

streamflows (results not reported here) to extracted streamflow 

in RCH58; numerical congruence was independently verified 

by using spreadsheet computations (not reported here). The 

two Perl scripts also provided for additional extractions from 

SWAT output files that combined the data to create total 

upstream inflow within the Guadalupe River into Canyon Lake 

as well as the peripheral inflow to Canyon Lake. Additional 

Perl scripts executing other Perl scripts provided for various 

batch-processing operations of SWAT output for the five 

scenarios and the baseline scenario.

The summation of streamflow in RCH58 and SUB59 

provided the total upstream inflow into Canyon Lake that 

is provided by only the Guadalupe River. The RCH58 + 

SUB59 summation was then added to the summation of 

all subbasins providing peripheral inflow to Canyon Lake 

(fig. 3). The peripheral inflow, as recognized by Bumgarner 

and Thompson (2012, fig. 8), is represented by Delineation 23 

(“brush-management subbasin” in Bumgarner and Thompson 

[2012] nomenclature) and is the summation of outflow 

from 21 peripheral subbasins. The 21 subbasins (fig. 3) are 

sequentially enumerated in the fourth bulleted item in figure 4. 

The Delineation 23 total, which is the summation of the 21 

subbasins of Bumgarner and Thompson (2012), when added 

to total upstream inflow (RCH58 + SUB59) becomes the 

total monthly inflow into Canyon Lake. The total inflow files 

(app. 1) of post-SWAT processed files are in a format that 

replicates the format required for the WAM input-flow file 

titled gsa_run3.inf, although the labels for the period 1995–

2010 (January through December) were retained for the files 

in appendix 2. Lastly, and critical for linkage to the Guadalupe 

River WAM, the total inflow by month for the period 1995–

2010 was passed into the WAM, through the WAM control 

point coincident with the Spring Branch streamgage.

Implemented Soil and Water Assessment ToolWater Availability Model Linkage

Specific notation pertaining to nomenclature of the WAM 

is required and linked to various record identifiers in the 

Guadalupe River WAM (Wurbs, 2011; Texas Commission on 

Environmental Quality, 2013) by cross-reference to figure 4. 

Visual referencing for the WAM components is available by 

using GIS data files for the Guadalupe River WAM available 

from Texas Commission on Environmental Quality (2013). 

The GIS data files were consulted to determine record 

identifiers to build the watershed and control point hierarchy 

and thus guide modifications to the gsa_run3.dis file of the 

Guadalupe River WAM.

The watershed and control hierarchy and additional 

description of the SWAT-WAM linkage are shown in figure 5. 

The parts of WAM parameters requiring slight modification 

to support linkage to SWAT are shown with an objective to 

achieve the slightest modification (only four drainage arearelated parameters altered) possible to the otherwise officially 

accepted Guadalupe River WAM. Drainage areas and their 

respective influences on WAM operation are important and 

especially noted in figure 5.
Linkage Between the Soil and Water Assessment Tool and Water Availability Model 11

Figure 4. Glossary/Nomenclature/Description of the aggregation of the Soil and Water Assessment Tool for the upper Guadalupe River 

watershed to create total monthly inflow to Canyon Lake, Comal County, Texas.

Total monthly

inflow into

Canyon Lake

(acre-feet)

Canyon Lake peripheral inflow

Delineation 23

(BT2012, fig. 8)

Total upstream inflow (Guadalupe River)

RCH58

SUB61

(BT2012, fig. 3)

SUB64

(BT2012, fig. 3)

SUB88

(BT2012, fig. 3) RCH85

Spring Branch streamgage

SUB59

(BT2012, fig. 3)

Glossary/Nomenclature/Description:

• BT2012—Bumgarner and Thompson (2012);

• Soil and Water Assessment Tool (SWAT) generates two types of output files: reach (RCH) and subwatershed (SUB). These are aggregated (summed) in the pathway of the above diagram to create total monthly inflow to Canyon Lake for substitution in the Water Availability Model input-flow file

gsa run3.inf;

• Streamflow direction is represented by arrow heads;

• Delineation 23 (Bumgarner and Thompson, 2012, fig. 8) is composed of subwatersheds (Bumgarner and

Thompson, 2012, fig. 3): SUB62, SUB63, SUB65, SUB66, SUB67, SUB68, SUB69, SUB70, SUB73,

SUB74, SUB77, SUB78, SUB79, SUB80, SUB81, SUB82, SUB84, SUB86, SUB87, SUB90, and

SUB91. Delineation 23 may be generally thought of as peripheral flow to Canyon Lake.

• The SWAT model produces stream reach (RCH) records for the main channel within each same

numbered SUB such as RCH85. This reach represents the same location as U.S. Geological Survey

streamflow-gaging station 08167500 Guadalupe River near Spring Branch, Texas (“Spring Branch

streamgage”). RCH85 represents aggregated streamflow for all subwatersheds upstream from this

streamgage. These subwatersheds are not enumerated here nor are they shown in figure 3, but they

are represented in Bumgarner and Thompson (2012, fig. 2). RCH58 is the reach having summation of

SUB61, SUB64, SUB88, and RCH85.
12 Linkage of SWAT and Texas WAM to Simulate the Effects of Brush Management on Monthly Storage

Figure 5. Glossary/Nomenclature/Description of the linkage between the upper Guadalupe River Soil and Water Assessment Tool 

and Guadalupe River Water Availability Model (WAM) to create total monthly inflow to Canyon Lake, Comal County, Texas, suitable for 

substitution into the input-flow file of the Guadalupe River WAM.

WAM output as monthly

reservoir storage (acre-feet)

WAM output file: gsa run3.out

CP03 ← Canyon Lake

1,432.25 square miles (mi2) →

(1,314.74 mi2[SWAT → WAM])

G908 (1,314.73 mi2 [SWAT → WAM])

Tom Creek

1.98 mi2 → 0.01 mi2 G907 (1,314.72 mi2 [SWAT → WAM])

Jentsch Creek

17.17 mi2 → 0.01 mi2 G921 (1,314.71 mi2 [SWAT → WAM])

Rebecca Creek

36.95 mi2 → 0.01 mi2

CP02 ← Spring Branch streamgage

(1,314.70 mi2)

SWAT input as

monthly streamflow

(acre-feet)

WAM input-flow file: gsa run3.inf

Glossary/Nomenclature/Description:

• Water Availability Model (WAM) with output in text file gsa run3.out, Soil and Water Assessment Tool (SWAT)

output substituted into WAM input text file gsa run3.inf;

• Arrow heads represent direction of streamflow, solid lines represent the main stem of the Guadalupe River, and

dashed lines are tributaries within the WAM;

• “[SWAT → WAM]” is to read “SWAT mapped to WAM” through the drainage area (DA) modification and the DA

within parentheses are those used for the WAM application described in this report;

• WAM control points (CP) are identified with a left arrow (←) indicating that the geographic feature or place name

corresponds to the control point. CP02 is U.S. Geological Survey streamflow-gaging station 08167500 Guadalupe

River near Spring Branch, Texas (“Spring Branch streamgage”);

• Tributary confluences by WAM creek name and WAM confluence numbers are G908, G907, and G921; and

• Right arrows (→) indicate that the tributary DAs were converted to 0.01 square miles (mi2) for the purpose of linking the SWAT model output to the WAM input. The DAs are set within the WAM gsa run3.dis text file by the

subordinate “WP records.” Conceptually, there are three recognized tributaries and unnamed aggregated peripheral inflow to Canyon Lake. The small DA increase from GP908 through to CP03 hence “virtually” turns off the

ungaged watershed algorithms in the WAM without further modification of established parameters in the WAM—in

total, the DA increase from CP02 through to CP03 is 0.04 mi2.
Linkage of the Upper Guadalupe River SWAT and the Texas WAM to Simulate the Effects of Brush Management 13

The diagram in figure 5 shows that the starting point 

of the linkage is control point number 2 (CP02), which is 

coincident with the Spring Branch streamgage. SWAT total 

inflow files (app. 1) are passed through CP02. To maintain 

appropriate streamflow mass (quantity), it was necessary to 

modify the WAM for four watershed property parameter input 

values representing four locations downstream from CP02 to 

control point 3 (CP03); CP03 is the identifier for Canyon Lake 

in the WAM parameter file gsa_run3.dis.

There are three named tributaries in the Guadalupe River 

WAM encompassing most of the drainage area to Canyon 

Lake downstream of the Spring Branch streamgage—Rebecca 

Creek (G921 control point), Jentsch Creek (G907 control 

point), and Tom Creek (G908 control point)—as well as a 

remaining unnamed aggregate drainage area to Canyon Lake. 

The remaining unnamed drainages are the numerous small 

and peripheral watersheds directly flowing into Canyon Lake 

as described in the section titled “Conceptual Depiction of 

the Soil and Water Assessment Tool-Water Availability Model 

Linkage.” These four watersheds are turned off by deliberate 

adjustment of the drainage areas in the WAM parameter 

file gsa_run3.dis. The deliberate adjustment is made to 

have the WAM turn off the WAM-specific computations of 

contributing streamflow because SWAT simulations already 

account for the water. The change in drainage area, because 

each of the four watersheds is numerically encountered during 

WAM execution, was chosen as 0.01 mi2 to be vanishingly 

small for the SWAT-WAM linkage. To clarify, each of the four 

watersheds recognized by, that is, incorporated into, the WAM 

between CP02 and CP03 was adjusted to have a drainage 

area of only 0.01 mi2 instead of the real-world increase in 

drainage area because each tributary converges with the main 

stem of the Guadalupe River. To clarify, SWAT numerically 

accommodates the four ungaged watersheds, and the WAM 

uses a type of apportioning based in part on Spring Branch 

streamflow (CP02); therefore, it is critical to effectively 

turn the four watersheds off within the WAM to maintain 

appropriate streamflow mass.

Further clarification is sought to avoid potential 

confusion because the WAM uses a cumulative drainage area 

as each successive input (control point, permit [water use] 

point, or tributary) enters the Guadalupe River main stem. 

The drainage areas listed within the parentheses in figure 5 are 

the precise drainage areas used in a modified version of the 

gsa_run3.dis parameter file of the WAM. The reassignment 

of drainage areas by an increase of 0.01 mi2 per tributary was 

chosen instead of zero to guard against potential division by 

zero errors or other potential problems of WAM execution. 

When the tributaries are numerically small, as seen in the 

complex WAM water-budget accounting algorithms, the WAM 

becomes suitable for passage of total monthly inflow for 

Canyon Lake from the upper Guadalupe River SWAT through 

the Spring Branch streamgage (CP02). The modification of 

intervening drainage areas from CP02 to CP03 is conceptually 

easiest to explain as opposed to more complicated and errorprone steps to turn off ungaged watershed computations within 

WAM, such as the drainage area ratio method (Asquith and 

others, 2006) that is a form of streamflow apportionment by 

ratios of watershed areas.

Linkage of the Upper Guadalupe River 

Soil and Water Assessment Tool and 

the Texas Water Availability Model 

to Simulate the Effects of Brush 

Management

Extensive Brush-Management Scenarios 

(Treatable Ashe Juniper)

Five scenario land-cover datasets were selected 

to evaluate the relative (between scenario to baseline) 

potential for extensive brush management for water-supply 

enhancement in the upper Guadalupe River watershed. The 

baseline scenario considered for this investigation (0-percent 

ashe juniper management in which no ashe juniper is replaced 

with grassland, fig. 6) is the same as the nontreatment 

calibration scenario of Bumgarner and Thompson (2012). 

Modified datasets from Bumgarner and Thompson (2012) 

were generated by randomly replacing 20, 40, 60, 80, and 

100 percent of the treatable ashe juniper (ashe juniper that 

could potentially be replaced with grassland through extensive 

brush management). The adjective “extensive” is deliberately 

chosen because the numerical conversion of treatable ashe 

juniper to grassland is on a scale much larger than individually 

considered in any of the 23 brush-management scenarios 

considered by Bumgarner and Thompson (2012). The 

HRUs were generated for the upper Guadalupe River SWAT 

simulations for this investigation by using the modified landcover datasets. Although spanning 16 years (1995–2010) of 

simulation, SWAT scenarios of brush management did not 

consider potential ashe juniper regrowth during the simulation 

period because doing so was beyond the scope of this 

investigation. 

The National Land Cover Database (NLCD) 2006 (Fry 

and others, 2011) was modified to simulate the numerical 

replacement of 20, 40, 60, 80, and 100 percent of the 

treatable ashe juniper within the upper Guadalupe River 

watershed with grasslands. Four NLCD 2006 categories were 

chosen to represent areas that might contain ashe juniper: 

(1) Deciduous Forest, (2) Evergreen Forest, (3) Mixed Forest, 

and (4) Shrubland (fig. 6). Because the NLCD 2006 categories 

do not explicitly identify vegetation types, a second dataset 

with more detailed categories of vegetation was required 

in a defensible attempt to isolate the treatable ashe juniper. 

Bumgarner and Thompson (2012) provided extensive 

discussion leading to the phrase “treatable ashe juniper” for 

the upper Guadalupe River watershed.
Figure 6. National Land Cover Database 2006 land-cover categories in the upper Guadalupe River watershed, south-central Texas (modified from Bu2012, fig. 6).

98°30'

99°

99°30'

30°10'

30°

29°50'

0 10 20 MILES0 10 20 KILOMETERS

Land-cover categories for which ashe juniper was numerically converted to grassland are deciduousforest, evergreen forest, mixed forest, and shrubland and are shown in the explanation. A summaryof treatable ashe juniper acreages, as numerically reported to the acre by the geographic informationsystem that created the datasets of five extensive brush-management scenarios. These datasetscontributed to the Soil Water Assessment Tool (SWAT) simulations. The acreages and percent of totalupper Guadalupe River watershed area (918,793 acres) for the scenarios are: 

Baseline:

20 percent:40 percent:60 percent:80 percent:

100 percent:

( 0 percent)( 4.3 percent)( 8.6 percent)

(12.9 percent)(17.2 percent)(21.5 percent)

0 acres

39,487 acres78,981 acres

118,482 acres157,991 acres197,504 acres

GILLESPIE COUNTY 

KERR COUNTY

KENDALL COUNTY

BANDERA COUNTY

BEXAR COUNTY

REAL

COUNTY

Land-cover category Open water Developed, open space Developed, low intensity Developed, medium intensity Developed, high intensity Barren land Deciduous forest

 Evergreen  Mixed fore Shrubland Grassland/ Pasture/ha Cultivated 

Woody we

Upper Guad watershe

EXPLANATION

Base modified from U.S. Geological Survey 1:100,000-scale digital dataTexas Centric Mapping System–Albers Equal Area projectionNorth American Datum of 1983 

La
Linkage of the Upper Guadalupe River SWAT and the Texas WAM to Simulate the Effects of Brush Management 15

Replicating the SWAT simulation approach documented 

by Bumgarner and Thompson (2012), the geodatabase files 

for the Texas Parks and Wildlife Department Texas Ecological 

Systems Classification Project (TESCP) (Texas Parks and 

Wildlife Deparment, 2013). The digital files for the TESCP 

can be acquired from the Geographical Information System 

Laboratory of the Texas Parks and Wildlife Department.

Additional land-cover information was needed because 

TESCP has 43 ecological system categories in the study area, 

and ashe juniper was identified as present in 13 of the 43 

categories. The 13 categories with ashe juniper were evaluated 

on the basis of TESCP ecological-system descriptions. 

Categories in which ashe juniper was listed as one of the 

dominant vegetation types in the category description (except 

where associated with riparian zones [streamside corridors] or 

steep slopes) were selected for use in the brush-management 

scenarios described in this report. The categories dominated 

by ashe juniper that also were associated with riparian zones 

or steep slopes were not converted to grassland for the 

brush-management simulations and instead were classified 

as untreatable areas because, as explained by Afinowicz and 

others (2005), actual field applications are unlikely to replace 

ashe juniper with grasslands in these areas. Areas of steep 

slope were identified in the TESCP nomenclature as land 

cover on slopes greater than 20 percent and less than 100 

percent. 

For Bumgarner and Thompson (2012) and for this 

investigation, there were three TESCP categories chosen 

to represent the location of ashe juniper to be replaced 

with grassland for the brush-management simulations. The 

common names for the three TESCP categories are Edwards 

Plateau: Ashe Juniper Motte and Woodland; Edwards Plateau: 

Ashe Juniper and Live Oak Shrubland; and Native Invasive: 

Ashe Juniper Shrubland. The two TESCP land-cover class 

names are Juniper Forest and Juniper Shrubland, and the three 

TESCP location categories are in about 23 percent of the upper 

Guadalupe River watershed when the aspect of treatability is 

considered. The percentage of 23 nearly matches the average 

of 22 percent found in column 4 of table 6 of Bumgarner and 

Thompson (2012). The 23 percent is not be confused with the 

23 scenarios of Bumgarner and Thompson (2012). Bumgarner 

and Thompson (2012, p. 17) provided additional details on the 

simulation methods used for this 2013 investigation.

To numerically replace treatable ashe juniper with 

grassland, the raster calculator in ArcMap 9.3.1 was used 

to change the NLCD 2006 values from Deciduous Forest, 

Evergreen Forest, Mixed Forest, and Shrubland to grassland 

(technically the NLCD Grassland/Herbaceous category) if the 

cells in the NLCD 2006 raster intersected cells representing 

Juniper Forest and Juniper Shrubland in the TESCP raster. 

This method is similar to the removal methods used in the 

previous TSSWCB feasibility studies (Bednarz and others, 

2000; Bumgarner and Thompson, 2012) and the maximum 

removal scenarios used by Afinowicz and others (2005).

The five scenario land-cover datasets were created to 

represent the random removal of 20, 40, 60, 80, and 100 

percent of the treatable ashe juniper. The “Create Random 

Raster” tool of ArcMap 9.3.1 was used and created a raster of 

uniform-variate values (uniformly distributed real numbers 

on the open interval of 0 to 1) per raster cell. A default seed 

for the random-number generator was used. The raster 

cells are about 8.36 m by 8.36 m. The random raster then 

was effectively overlaid on the land-cover categories and 

applicable cells reclassified as grassland from treatable ashe 

juniper according to probability thresholds of 0.2, 0.4, 0.6, 0.8, 

and 1 that represent the five percentage scenarios of 20, 40, 

60, 80, and 100 percent, respectively. A systematic approach 

for grassland conversion was not used because it is outside 

the scope of this investigation to either ad hoc or objectively 

identify specific parcels of land (mostly privately owned) for 

conversion. 

For each of the five brush-management scenarios, the 

HRUs were generated for the upper Guadalupe River SWAT 

by using the modified land-cover dataset that corresponded 

with the percentage brush management, and model parameters 

associated with land cover were accordingly and automatically 

modified by SWAT software (Neitsch and others, 2011b). 

Lastly, figure 6 shows the land-cover categories as depicted 

for the baseline; similar figures representing the five extensive 

brush-management scenarios could be rendered but were not 

included in this report because the application of random 

replacement to grassland process could be confused with 

suggested locations of rasters or land parcels for treatment. 

A comparison of treatable ashe juniper acreage to results of 

Bumgarner and Thompson (2012) is shown in appendix 3.

Relative (Between Scenario to Baseline) Effects 

of Extensive Brush-Management Scenarios 

The relative (between scenario to baseline) effects of 

extensive brush-management scenarios were determined by 

using the SWAT-WAM linkage. Two critical, intermediate 

results were total inflow (streamflow and tributary inflow) to 

Canyon Lake for the period 1995–2010 and monthly storage 

of Canyon Lake for the period 1974–89 (synthetic). These 

intermediate results are each discussed in the sections that 

follow. Time series data of Canyon Lake inflow are shown 

in figure 7 and monthly storage data of Canyon Lake are 

shown in figure 8. There is considerable overplotting of the 

scenarios in figure 8 because the results for different scenarios 

were often similar or numerically identical (particularly in the 

earlier parts of the time series); the numerical comparisons 

described best identify generalized differences.
16 Linkage of SWAT and Texas WAM to Simulate the Effects of Brush Management on Monthly Storage

Figure 7. Relation between cumulative volume and time for total monthly inflow to Canyon Lake as simulated by Soil and Water 

Assessment Tool (SWAT), which includes main stem of Guadalupe River and peripheral drainage to Canyon Lake. Downloadable files for 

these data are described in appendix 1.

Simulation year (see text about 1995–2010 and 1974–89 [synthetic])

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Cumulative total monthly inflow (volume) into Canyon Lake, in acre-feet

0

1,000,000

2,000,000

3,000,000

4,000,000

5,000,000

6,000,000

7,000,000

8,000,000

6,860,000 acre-feet (20 percent)

6,930,000 acre-feet (40 percent)

6,990,000 acre-feet (60 percent)

7,060,000 acre-feet (80 percent)

7,090,000 acre-feet (100 percent)

6,760,000 acre-feet (baseline)

Total volumes over period

of simulation are stacked in

diminishing order of

scenario percentage

to the baseline.

Soil and Water Assessment Tool (SWAT) baseline scenario (0-percent brush management)

Cumulative inflow from SWAT 20-percent treatable brush-management scenario

Cumulative inflow from SWAT 40-percent treatable brush-management scenario

Cumulative inflow from SWAT 60-percent treatable brush-management scenario

Cumulative inflow from SWAT 80-percent treatable brush-management scenario *

Cumulative inflow from SWAT 100-percent treatable brush-management scenario

EXPLANATION

* Almost indistinguishable from 100-percent scenario.
Linkage of the Upper Guadalupe River SWAT and the Texas WAM to Simulate the Effects of Brush Management 17

Figure 8. Relation between monthly storage and time of Canyon Lake determined by using Soil and Water Assessment Tool (SWAT) 

output shown in figure 7 as (1974–89, synthetic) input to the Guadalupe River Water Availability Model (WAM) at control point 2 (CP02, 

U.S. Geological Survey streamflow-gaging station 08167500 Guadalupe River near Spring Branch, Texas, figs. 2 and 3) for the period 

1995–2010. Downloadable files for these data are described in appendix 2.

Simulation year (see text about 1995–2010 and 1974–89 [synthetic])

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Monthly storage of Canyon Lake, in acre-feet

350,000

355,000

360,000

365,000

370,000

375,000

380,000

385,000

390,000

386,200 acre-feet conservation storage 381,000 acre-feet (the Drought Quartile)

The shaded area represents Canyon Lake storage above the Drought Quartile

A drought period

Soil and Water Assessment Tool (SWAT) baseline scenario (0-percent brush management)

Cumulative inflow from SWAT 20-percent treatable brush-management scenario

Cumulative inflow from SWAT 40-percent treatable brush-management scenario

Cumulative inflow from SWAT 60-percent treatable brush-management scenario

Cumulative inflow from SWAT 80-percent treatable brush-management scenario *

Cumulative inflow from SWAT 100-percent treatable brush-management scenario

EXPLANATION

* Almost indistinguishable from 100-percent scenario.
18 Linkage of SWAT and Texas WAM to Simulate the Effects of Brush Management on Monthly Storage

Total Inflow to Canyon Lake, 1995–2010

SWAT simulated cumulative total monthly inflows to 

Canyon Lake for the period 1995–2010 (a true time period 

of SWAT simulation) for each of the five brush-management 

and the baseline scenarios are shown on figure 7, and the six 

cumulative volumes also are annotated. The mean annual 

inflow (acre-feet per year) to Canyon Lake per scenario can 

be computed (not reported here) by dividing one of the total 

volumes by 16 (for the 16 years of simulation). Differences 

between the mean annual inflows to Canyon Lake per scenario 

are indicative of the relative incremental volumetric changes 

per scenario.

The first quartile or lower 25th percentile of monthly 

storage (the Drought Quartile) of Canyon Lake for the 192 

months of the baseline scenario (1974–89, synthetic) was 

computed to be 381,000 acre-ft (fig. 8). The Drought Quartile 

is a conceptual and heuristically determined waypoint for 

the analysis herein and is not related to any administrative 

definition of drought by stakeholders or policy makers. 

The Drought Quartile of monthly storage for the baseline 

scenario was chosen for analysis for two critical purposes. 

First, Canyon Lake is managed by the U.S. Army Corps of 

Engineers (2013) with a conservation pool of about 386,200 

acre-ft capacity (fig. 8) and is at or near conservation capacity 

about 50 percent or more of the time (as provided by the 

baseline scenario executed through the Guadalupe River 

WAM); intrinsic data censoring occurs in the distribution 

of monthly storage values because of the intent to manage 

Canyon Lake at conservation pool elevation. This intrinsic 

censoring has the effect of creating a bounded distribution 

with a left or low-volume tail; thus, a normal or approximately 

normal distribution (Helsel and Hirsch, 2002) of monthly 

storage values does not occur, and the actual lower quartile of 

Canyon Lake monthly storage during SWAT calibration period 

(1995–2012) can differ from 381,000 acre-ft for the 192 

months of the baseline scenario (1974–89, synthetic). 

Statistical assessment of the brush-management scenarios 

numerically distinct or “away” from the 381,000 acre-ft 

censoring threshold provides readily interpretable results. 

The intrinsic data censoring is important to recognize because 

general increases in monthly streamflow as a result of ashe 

juniper removal are arguably mostly unavailable for water 

supply for CP03 because Canyon Lake is already at or near 

conservation capacity more than 50 percent of the time. The 

median monthly storage for the baseline scenario linked 

through the WAM is 386,200 acre-ft, which implies that any 

“excess” inflow when Canyon Lake is at conservation capacity 

exits the reservoir through processes such as evaporation or 

outflow more than 50 percent of the time for the study period. 

Second, the quantification of brush management during 

periods lacking abundant rainfall, which were defined in this 

study as months for which Canyon Lake storage is below 

the lower quartile (the Drought Quartile) for the simulation 

period, are of substantial interest to water-resource managers 

and stakeholders associated with the TSSWCB Water Supply 

Enhancement Program and the emphasis towards enhancing 

water supply (not just streamflow in and of itself) through 

brush management. The comparisons of cumulative volume 

in Canyon Lake and treated ashe juniper yields to results in 

Bumgarner and Thompson (2012) are made in appendix 3.

Monthly Storage of Canyon Lake, 1974–89 

(synthetic) from Extensive Brush-Management 

Scenarios

SWAT calibration as used for this investigation was 

oriented around minimization of “the differences between 

simulated and measured [monthly] streamflows” (Bumgarner 

and Thompson, 2012, p. 22). Canyon Lake is not in Drought 

Quartile conditions about 75 percent of the time, and because 

SWAT is not uniquely calibrated during periods lacking 

abundant rainfall such as the Drought Quartile, there are 

uncertainties in absolute values of SWAT-simulated monthly 

streamflow as well as WAM-computed monthly storage.

There are uncertainties in the SWAT-WAM linkage 

and scenarios that are difficult to quantify, such as the 

postsimulation offsetting of SWAT by −21 years to link into 

the Guadalupe WAM. Cumulative volumes and mean monthly 

offset storage values obtained from the mean of the lower 

quartile of Canyon Lake storage were used for the purpose of 

making relative comparisons between different scenarios. The 

term “offset storage” represents the subtraction of the mean 

of the lower quartile storage, and the context of the adject 

offset here is not related to the −21 year time offset previously 

described. This approach to making relative comparison helps 

mitigate interpretation complications arising from the ad hoc 

offset of the upper Guadalupe River SWAT simulations (1995–

2010) to the 1974–89 (synthetic) period of the Guadalupe 

River WAM.

Time series data of cumulative monthly inflow to Canyon 

Lake for the different treatable brush-management scenarios 

are depicted in figure 7. General similarity between the 

different scenarios is evident during the first several years of 

simulation, with cumulative differences gradually becoming 

increasingly discernible over time. The cumulative totals for 

monthly inflow to Canyon Lake for the entire 1995–2010 

simulation period range from 6,760,000 acre-ft for the baseline 

scenario to 7,090,000 acre-ft for the 100-percent removal of 

treatable brush scenario (fig. 7). 

Changes in simulated monthly storage in Canyon 

Lake are depicted in figure 8. The conservation storage of 

Canyon Lake is about 386,200 acre-ft and represents the 

maximum storage, which periodically occurred during periods 

of abundant rainfall from 1995 to 2010. These periods of 

maximum storage are of comparatively less interest in the 

context of brush management associated with ashe juniper 

within the upper Guadalupe River watershed than are 

the effects of ashe juniper management on water-supply 

enhancement during periods lacking abundant rainfall. An 

example drought period defined by the Drought Quartile is 
Linkage of the Upper Guadalupe River SWAT and the Texas WAM to Simulate the Effects of Brush Management 19

evident some time during 2003 (fig. 8). Discernible increases 

in the monthly storage of Canyon Lake (fig. 8) are generally 

evident during the Drought Quartile for the brush-management 

scenarios.

SWAT calibration used for the 2013 investigation was 

oriented around minimization of “the differences between 

simulated and measured [monthly] streamflows” (Bumgarner 

and Thompson, 2012, p. 22). Canyon Lake was not in Drought 

Quartile conditions about 75 percent of the time, with an 

explicit acknowledgment that the actual lower quartile of 

Canyon Lake monthly storage during SWAT calibration 

period (1995–2012) might differ from 381,000 acre-ft for the 

192 months of the baseline scenario for 1974–89 (synthetic). 

Because SWAT is not uniquely calibrated during periods 

lacking abundant rainfall such as the Drought Quartile, there 

are uncertainties in the absolute values of monthly streamflow 

simulated by SWAT as well as the monthly storage computed 

by the WAM.

There are uncertainties in the SWAT-WAM linkage and 

scenarios, such as the postsimulation offsetting of SWAT by 

−21 years, considered to link into the Guadalupe WAM that 

are difficult to quantify. The use of comparisons through the 

depiction of cumulative volumes and mean monthly offset 

storage values from the mean storage of the lower-quartile 

of Canyon Lake storage should mitigate for interpretation 

complications concerning the ad hoc offset of the upper 

Guadalupe River SWAT simulations (1995–2010) to the 

1974–89 (synthetic) period of the Guadalupe River WAM.

The five scenarios and the baseline scenario simulated 

in the upper Guadalupe River SWAT by Bumgarner and 

Thompson (2012) were passed through the Guadalupe River 

WAM by the SWAT-WAM linkage described in this report. 

A comparison of the mean increase per month in reservoir 

storage for Canyon Lake conditioned for periods lacking 

abundant rainfall (the Drought Quartile, storage less than 

381,000 acre-ft) was made.

For each of the five brush-management scenarios and 

the baseline by Bumgarner and Thompson (2012), the months 

with storage below 381,000 acre-ft were extracted. There were 

48 months below the lower quartile of the baseline scenario 

for each of the five scenarios, in which 48 divides into 192 

exactly four times as expected. The mean monthly storages 

during the Drought Quartile were computed for each of the 

five scenarios and the baseline scenario by summing the 

monthly storage for the 48 months and dividing by 48. The 

mean of the baseline scenario was 376,458 acre-ft. The mean 

value of 376,458 acre-ft for the baseline scenario subsequently 

was subtracted from the mean monthly storage during the 

Drought Quartile for each of the five scenarios. The purpose 

of the subtraction was to reduce numerical magnitude to 

make relative comparisons to the baseline easier to express 

and to mitigate for interpretation complications concerning 

the −21-year time offset.

The mean monthly offset storages of Canyon Lake 

during the Drought Quartile were 110 acre-ft (20 percent); 448 

acre-ft (40 percent); 754 acre-ft (60 percent); 1,080 acre-ft 

(80 percent); and 1,090 acre-ft (100 percent). A particular 

mean can be interpreted as follows: the 754 acre-ft for the 

60-percent brush-management scenario implies that, on 

average, this scenario indicates an additional 754 acre-ft per 

month of storage in Canyon Lake relative to the baseline 

during the Drought Quartile.

All of the scenarios resulted in an increase on average to 

water supply during the Drought Quartile through the SWATWAM linkage; however, an observation was made that any 

of the scenarios numerically resulted in at least a month of 

apparent decrease in water storage (as seen in a small fraction 

of months for the 20- [such as October 2000] and 100-percent 

[such as March 1999] scenarios dropping below the baseline 

storage time series in fig. 8). 

By inspection of the relative change in the mean 

monthly offset values per scenario, it appeared as though 

the 100-percent brush-management scenario was only 

marginally larger than the 80-percent scenario and, therefore, 

the 80-percent brush-management scenario likely provided 

for more water-supply enhancement relative to imparted 

effort than the 100-percent scenario. The 80-percent brushmanagement scenario seemingly achieved more relative 

water-supply enhancement than the 100-percent scenario did 

because it is incrementally quite similar to the 100-percent 

scenario: 1,090 acre-ft (100 percent) versus 1,080 acre-ft 

(80 percent) mean monthly offset storage. The incremental 

water-supply enhancement during the Drought Quartile from 

the 80-percent to 100-percent brush-management scenario 

was about 10 acre-ft storage per month. During Drought 

Quartile conditions, the order of storage change was about 

828 acre-ft per 0.1-foot change in water-surface elevation. The 

incremental water-supply enhancement from the 80-percent 

to the 100-percent scenario was on the order of 0.01-feet 

per month (approximately 10 acre-ft divided by 828 acre-ft 

per 0.1-foot change); therefore, the 80-percent scenario was 

reasoned to provide about as much water-supply enhancement 

as the 100-percent scenario on the basis of the methods used.

The consideration of monthly storage changes in the 

context of the storage change per change in water-surface 

elevation (made for the aforementioned 80- to 100-percent 

scenario comparison) provides alternative perspective to 

storage. The mean monthly storage change for each of the 

five scenarios was considered in terms of expected monthly 

increase in water-surface elevation of Canyon Lake. The 

mean monthly storage changes, which were based on the 

828 acre-ft per 0.1-foot change applicable for the Drought 

Quartile threshold of 381,000 acre-ft, were about 0.01 foot 

(20 percent), about 0.05 foot (40 percent), about 0.1 foot (60 

percent), about 0.13 foot (80 percent), and about 0.13 foot 

(100 percent). For example, the value of 0.05 foot for the 

40-percent scenario was computed by 448 acre-ft divided by 

828 acre-ft per 0.1-foot change. Each of the five extensive 

brush-management scenarios therefore was expected to 

produce a monthly water-supply enhancement at least equal to 

the incremental resolution of USGS measurements of watersurface elevation (0.01 foot) for Canyon Lake within the 
20 Linkage of SWAT and Texas WAM to Simulate the Effects of Brush Management on Monthly Storage

USGS National Water Information System (U.S. Geological 

Survey, 2013). Asquith and others (2007) provides additional 

details for water-surface-elevation measurements done by the 

USGS in Texas.

Discussion of Result Sensitivity

Because this report serves in part as documentation of 

a proof of concept on the feasibility of linking previously 

published models, SWAT and WAM, and for other reasons 

that follow, sensitivity analysis of the results herein would be 

inherently problematic to complete, and if it could be done, 

it would potentially subject the results to overinterpretation 

regarding the precision of the simulations generated by linking 

the models. It is difficult to identify a quantitative approach 

that would combine basic uncertainty (variation) in SWAT and 

WAM. Bumgarner and Thompson (2012) described various 

calibration biases and uncertainties. It also is difficult to 

assess the potential variability of the WAM because numerical 

uncertainty is not a component of the output files; thus, the 

authors are confronted with one model with a quantification 

of uncertainty and another with neither qualification nor 

quantification of uncertainty, specifically pertaining to Canyon 

Lake storage.

The offset of −21 years to force a temporal linkage 

between the two time periods is a large jump in logic 

that greatly increases difficulty in either quantification 

or qualification of result sensitivity. Cursory inspection 

of observed streamflow (not SWAT modeled flow) at the 

Spring Branch streamgage for January 1974 (289 cubic feet 

per second [ft3/sec]) and January 1995 (377 ft3/sec) (U.S. 

Geological Survey, 2013) indicates that hydrologic conditions 

are similar for the two periods. Canyon Lake monthly 

storage for the baseline scenario offset −21 years begins the 

1974–89 (synthetic) time series at conservation capacity, 

which replicates storage conditions for January 1974 of the 

unmodified Guadalupe River WAM.

This section provides an opportunity to discuss how 

the linkage effort could be improved. First, recalibration of 

SWAT to a 1974–89 (nonsynthetic) period might be possible, 

but it is likely that the 1970s and 1980s landscape in terms 

of treatable ashe juniper differed appreciably from treatable 

ashe juniper landscape of concern to brush-management 

stakeholders in 2013, and the fundamental quality and quantity 

of land-use data during the 1970s and 1980s is difficult to 

assess. The authors prefer circumstances of use of the current 

SWAT model or possible future derivatives. The data used in 

the WAM ended in December 1989, and through 2013 there 

was not a priority for further temporal extension of the data 

used in the WAM because the drought of the 1950s remained 

the historic drought of record for water-availability modeling 

purposes (Tommy Hill, Guadalupe-Blanco River Authority, 

oral commun., November 20, 2013). The possibility of 

completing a robust sensitivity analysis of SWAT-WAM in the 

context of the study area is dependent upon on a WAM update 

that includes data through 2010, but such an update is outside 

the scope of this investigation.

Summary

The selective or managed removal of woody plants 

(brush management of nonherbaceous and nonsucculent 

plants) in an effort to potentially increase or enhance water 

availability for downstream water bodies is a conservation 

practice used in Texas in 2013. Ashe juniper (Juniperus 

ashei) is a species of woody plant that has spread beyond its 

historical range within the understories of prairie oak motte 

(small stands) and within sheltered canyons in south-central 

Texas. Studies of the water use of ashe juniper indicated 

that the species might intercept and subsequently enhance 

evaporation as well as generally use more water than native 

grasses use. The replacement in south-central Texas of ashe 

juniper with grasslands is intended to increase water yields 

from managed land parcels.

In an effort to help constrain the potential for watersupply enhancement by ashe juniper management in the upper 

Guadalupe River watershed, the U.S. Geological Survey, in 

cooperation with the Texas State Soil and Water Conservation 

Board, developed and applied an approach to create a linkage 

between straightforward extensions from a previous upper 

Guadalupe River Soil Water Assessment Tool (SWAT) 

feasibility study and the full authorization version Guadalupe 

River Water Availability Model (WAM). The Guadalupe 

River WAM is available from the Texas Commission on 

Environmental Quality (TCEQ). The upper Guadalupe River 

watershed is a substantial component of the Guadalupe River 

WAM. This report serves in part as documentation of a proof 

of concept on the feasibility of linking these two waterresources planning models for the purpose of simulating 

possible increases in water storage in Canyon Lake as a result 

of different brush-management scenarios.

The primary purpose of this report is to document the 

SWAT-WAM linkage for the upper Guadalupe River with a 

principal objective to evaluate the distributional characteristics 

of monthly storage of Canyon Lake in the context of water 

supply during periods lacking abundant rainfall. This 

report is focused on relative (between scenario to baseline) 

evaluation of select scenarios of large-scale or extensive brush 

management within the upper Guadalupe River watershed. 

There are six SWAT simulations that include a baseline 

(0-percent management of treatable ashe juniper, the baseline 

scenario from a previous study in which no ashe juniper is 

replaced with grassland) along with five scenarios (extensions 

of SWAT simulations from a previous study) of 20-, 40-, 60-, 

80-, and 100-percent random (numerical) replacement of 

treatable ashe juniper with grasslands throughout the upper 

Guadalupe River watershed.

The Guadalupe River Basin extends about 230 miles 

from its headwaters in the Edwards Plateau in south-central 
Summary 21

Texas to San Antonio Bay near Tivoli and has a total drainage 

area of about 10,200 square miles (mi2). The study area for 

this investigation was the upper Guadalupe River watershed 

(shaded area) and represents about 1,432 mi2 of the Guadalupe 

River Basin upstream from the dam for Canyon Lake.

Particularly pertinent to this investigation is U.S. 

Geological Survey streamflow-gaging station 08167500 

Guadalupe River near Spring Branch, Texas (hereinafter the 

Spring Branch streamgage). Three major tributaries (Rebecca 

Creek, Jentsch Creek, and Tom Creek) are each downstream 

from the Spring Branch streamgage and are either nearupstream or direct tributaries to Canyon Lake. The watersheds 

for the three creeks are named within the Guadalupe River 

WAM and represent specific control points. Adjustments 

to these three watersheds were needed for computational 

consistency of water-budget equations to implement the 

SWAT-WAM linkage.

SWAT is a process-based, semidistributed waterbalance model designed to predict the effects of landscape 

management decisions on water, sediment, and agricultural 

chemical yields. In SWAT, a watershed is subdivided into 

subbasins, and each subbasin is associated with a single 

reach on the stream network. Each subbasin is further 

divided into hydrologic response units that consist of unique 

combinations of land cover, soil characteristics, land slope, 

and land-management criteria. The upper Guadalupe River 

SWAT encompasses the period of monthly record 1995–2010 

(January through December).

In general, a WAM, such as the Guadalupe River WAM, 

provides for generalized water-rights analysis in a river and 

reservoir framework. A WAM accommodates hydrology and 

water usage through several input files that contain water 

rights, watershed parameters, and naturalized streamflow 

sequences. A WAM is generalized for application to river and 

reservoir systems, and input datasets are uniquely developed 

for a river basin of concern.

The extractions of SWAT output for the five extensive 

brush-management and baseline scenarios were offset by 

−21 years, and in general the results were then mapped to (a 

term that evokes the mathematical notation that was used) the 

WAM input-flow file. The offset of −21 years means that the 

period of monthly record 1995–2010 of the upper Guadalupe 

River SWAT becomes a synthetic period of monthly record 

1974–89, hereinafter the 1974–89 (synthetic), of the 

Guadalupe River WAM.

For depiction of SWAT output preprocessing and 

reformatting, a diagram with attendant description through 

an embedded Glossary/Nomenclature/Description section 

is shown. The starting point of the linkage is the monthly 

streamflow emanating from SWAT that is coincident with 

the Guadalupe River watershed monitored by the Spring 

Branch streamgage. This streamgage also is coincident with 

Reach 85 (RCH85) of SWAT, and RCH85 values for a single 

simulation scenario were extracted from the RCH plain-text 

file. For depiction of WAM modification and logic, another 

diagram with attendant description through an embedded 

Glossary/Nomenclature/Description section is shown. The 

schematic and corresponding symbols were deliberately 

chosen to represent those portions of four drainage-area WAM 

parameters requiring slight modification to support linkage to 

SWAT with an objective to achieve the slightest modification 

possible (only four parameters altered) to the otherwise 

officially accepted Guadalupe River WAM. Drainage areas 

and their respective influences on WAM operation are 

important and especially noted on the diagram. There are three 

tributaries recognized in the Guadalupe River WAM as well 

as the remaining unnamed aggregate drainage into Canyon 

Lake. These four watersheds are controlled by deliberate 

adjustment of the drainage areas in a WAM parameter file. 

The three named tributaries in the WAM are Rebecca Creek 

(G921 control point), Jentsch Creek (G907 control point), 

and Tom Creek (G908 control point). Because each of the 

four watersheds is numerically encountered during WAM 

execution, the change in drainage area was chosen as 0.01 mi2

to be vanishingly small for the SWAT-WAM linkage.

Five modified land-cover datasets were selected to 

evaluate the relative potential for extensive brush management 

for water-supply enhancement in the upper Guadalupe 

River watershed. The baseline scenario considered for this 

investigation (0-percent ashe juniper management) is the same 

as the nontreatment calibration scenario in a previous study. 

Modified datasets from that study were generated by randomly 

replacing 20, 40, 60, 80, and 100 percent of the treatable ashe 

juniper (ashe juniper that could potentially be replaced with 

grassland through extensive brush management).

The five scenario land-cover datasets were created to 

represent the random removal of 20, 40, 60, 80, and 100 

percent of the treatable ashe juniper. Geographical information 

system software was used to create a raster of uniformvariate values (uniformly distributed real numbers on the 

open interval of 0 to 1) per raster cell. A default seed for the 

random-number generator was used. The raster cells were 

about 8.36 meters by 8.36 meters. The random raster then 

was effectively overlaid on the land-cover categories and 

applicable cells reclassified as grassland from treatable ashe 

juniper according to probability thresholds of 0.2, 0.4, 0.6, 0.8, 

and 1 that represent the five percentage scenarios of 20, 40, 60, 

80, and 100 percent, respectively.

The relative effects of extensive brush-management 

scenarios obtained by using the SWAT-WAM linkage were 

evaluated, and two critical intermediate results were total 

inflow to Canyon Lake for 1995–2010 and monthly storage 

of Canyon Lake for 1974–89 (synthetic). The cumulative 

total monthly inflows (streamflow and tributary inflow) to 

Canyon Lake for the baseline and for each of the five brushmanagement and baseline scenarios are presented, and this 

streamflow represents total inflow to Canyon Lake for the 

period 1995–2010 (a true period of SWAT simulation). 
22 Linkage of SWAT and Texas WAM to Simulate the Effects of Brush Management on Monthly Storage

Differences between the annual inflows to Canyon Lake per 

scenario represent the incremental volumetric changes per 

scenario.

The first quartile or lower 25th percentile of monthly 

storage of Canyon Lake for the 192 months of the baseline 

scenario for 1974–89 (synthetic) was 381,000 acre-feet 

(acre-ft). This lower quartile of monthly storage for the 

baseline time series was chosen for analysis for two 

critical purposes. First, Canyon Lake was managed with a 

conservation pool of about 386,200 acre-ft capacity and was 

at or near conservation capacity about 50 percent or more of 

the time (provided by the baseline scenario executed through 

the Guadalupe River WAM); further, there was intrinsic data 

censoring that occurred for monthly storage distribution 

because of the intent to manage Canyon Lake at conservation 

pool elevation. This intrinsic censoring has the effect of 

creating a bounded distribution with a left or low-volume tail. 

Statistical assessment of the brush-management scenarios 

away from the 381,000 acre-ft censoring threshold provided 

readily interpretable results. This data censoring is important 

to recognize because, although numerically within SWAT the 

replacement of ashe juniper with grasslands increases water 

yields, many increases in monthly streamflow as a result 

of ashe juniper removal are arguably unavailable for water 

supply because Canyon Lake is already at or near conservation 

capacity over 50 percent of the time. The median monthly 

storage for the baseline scenario linked through the WAM was 

386,200 acre-ft, which implied by logical extension that any 

“excess” inflow to Canyon Lake exited the reservoir through 

processes such as evaporation or outflow above conservation 

pool elevation. Second, the quantification of brush 

management during periods lacking abundant rainfall, which 

were defined in this study as months for which Canyon Lake 

storage below its lower quartile for the simulation period, 

are of substantial interest to water-resource managers and 

stakeholders in the context of water-supply enhancement (not 

just streamflow in and of itself) through brush management.

Time series data of monthly storage of Canyon Lake for 

the two end-member scenarios (baseline and 100 percent) 

indicate that the 100-percent scenario plots higher than 

the baseline scenario during four drought periods. General 

similarity between the different scenarios is evident during the 

first several years of simulation, with cumulative differences 

gradually becoming increasingly discernible over time. The 

cumulative totals for monthly inflow to Canyon Lake for the 

entire 1995–2010 simulation period range from 6,760,000 

acre-ft for the baseline scenario to 7,090,000 acre-ft for the 

100-percent removal of treatable brush scenario. 

The conservation storage of Canyon Lake was about 

386,200 acre-ft, represented the maximum storage, and 

was associated with typical climatic periods and periods 

of abundant rainfall. Such periods in the context of brush 

management associated with ashe juniper within the upper 

Guadalupe River watershed were of comparatively less 

interest during this study than the effects of ashe juniper 

management on water-supply enhancement during drought 

periods. A statistical assessment of the SWAT-WAM linkage 

for the left or low-volume tail of the distribution of monthly 

storage of Canyon Lake was the focus of analysis and 

interpretation. Drought periods for the analysis were defined 

as the months (consecutive or not) for which Canyon Lake is 

below the 25th percentile of storage (381,000 acre-ft) for the 

baseline scenario. Such months are referred to as within the 

“Drought Quartile.” The Drought Quartile is a conceptual and 

heuristically determined waypoint for the analysis herein and 

is not related to any administrative definition of drought by 

stakeholders or policy makers.

The five extensive brush-management and baseline 

scenarios simulated in the upper Guadalupe River SWAT were 

all passed through the Guadalupe River WAM by the SWATWAM linkage described in this report. A comparison of the 

mean increase per month in reservoir storage for Canyon Lake 

conditioned for periods lacking abundant rainfall (the Drought 

Quartile, with storage less than 381,000 acre-ft) was made.

For each of the five brush-management and baseline 

scenarios, the months with storage below 381,000 acre-ft were 

extracted. The mean monthly storages during the Drought 

Quartile were computed for each of the five scenarios and 

the baseline scenario. The mean of the baseline scenario 

was 376,458 acre-ft and subsequently was subtracted from 

the mean monthly storage during the Drought Quartile for 

each of the five scenarios. The purpose of the subtraction is 

to reduce numerical magnitude to make comparisons to the 

baseline easier to express and to mitigate for interpretation 

complications concerning the −21-year time offset.

The mean monthly offset storages of Canyon Lake 

during the Drought Quartile were 110 acre-ft (20 percent); 448 

acre-ft (40 percent); 754 acre-ft (60 percent); 1,080 acre-ft 

(80 percent); and 1,090 acre-ft (100 percent). A particular 

mean can be interpreted as follows: the 754 acre-ft for the 

60-percent brush-management scenario implies that, on 

average, this scenario indicates an additional 754 acre-ft per 

month of storage in Canyon Lake relative to the baseline 

during the Drought Quartile. All of the scenarios result in 

an increase on average to water supply during the Drought 

Quartile through the SWAT-WAM linkage.

By inspection of the relative change in the mean 

monthly offset values per scenario, it appeared as though 

the 100-percent brush-management scenario was only 

marginally larger than the 80-percent scenario and, therefore, 

the 80-percent brush-management scenario likely provided 

for more water-supply enhancement relative to imparted 

effort than the 100-percent scenario. The 80-percent brushmanagement scenario seemingly achieved more relative watersupply enhancement than the 100-percent scenario because 

it is incrementally quite similar to the 100-percent scenario: 

1,090 acre-ft (100 percent) versus 1,080 acre-ft (80 percent) 

mean monthly offset storage.

The incremental water-supply enhancement during the 

Drought Quartile from the 80-percent to 100-percent brushmanagement scenario was about 10 acre-ft storage per month. 

During Drought Quartile conditions, the order of storage 

change was about 828 acre-ft per 0.1-foot change in watersurface elevation. The incremental water-supply enhancement 
References 23

from the 80-percent to the 100-percent scenario was on the 

order of 0.01-foot per month (approximately 10 acre-ft divided 

by 828 acre-ft per 0.1-foot change). Therefore, the 80-percent 

scenario was reasoned to provide about as much water-supply 

enhancement based on the methods used.

The consideration of monthly storage changes in the 

context of the storage change per change in water-surface 

elevation provided alternative perspective. The mean monthly 

storage change for each of the five scenarios was considered in 

terms of expected monthly increase in water-surface elevation 

of Canyon Lake. The mean monthly storage changes, which 

were based on the 828 acre-ft per 0.1-foot change applicable 

for the Drought Quartile threshold of 381,000 acre-ft, were 

about 0.01 foot (20 percent), about 0.05 foot (40 percent), 

about 0.1 foot (60 percent), about 0.13 foot (80 percent), 

and about 0.13 foot (100 percent). Each of the five extensive 

brush-management scenarios therefore is expected to produce 

a monthly water-supply enhancement at least equal to the 

incremental resolution of USGS measurements of watersurface elevation (0.01 foot) for Canyon Lake within the 

USGS National Water Information System.

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Publishing support provided by

Lafayette Publishing Service Center

Information regarding water resources in Texas is available at 

http://tx.usgs.gov/
Asquith and Bumgarner—Linkage of SWAT and Texas WAM to Simulate the Effects of Brush Management on Monthly Storage—SIR 2013–5239

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ISSN 2328-0328 (online)

ISSN 2328-031X (print)

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