U.S. Department of the Interior

U.S. Geological Survey

Open-File Report 2012–1077

Prepared in cooperation with the Texas Commission on Environmental Quality

Automated Delineation and Characterization of Watersheds 

for more than 3,000 Surface-Water-Quality Monitoring 

Stations Active in 2010 in Texas
Cover: Cover depicts an example of the delineation and characterization of watersheds (along with their 

elevations) for the Brazos River Basin.
Automated Delineation and Characterization 

of Watersheds for more than 3,000 SurfaceWater-Quality Monitoring Stations Active in 

2010 in Texas

By Christy-Ann M. Archuleta, Sophia L. Gonzales, and David R. Maltby II

Prepared in cooperation with the Texas Commission on Environmental Quality

Open-File Report 2012–1077

U.S. Department of the Interior

U.S. Geological Survey
Although this report is in the public domain, permission must be secured from the individual copyright owners to 

reproduce any copyrighted materials contained within this report.

Suggested citation:

Archuleta, C.M., Gonzales, S.L., and Maltby, D.R., II, 2012, Automated delineation and characterization of watersheds 

for more than 3,000 surface-water-quality monitoring stations active in 2010 in Texas: U.S. Geological Survey OpenFile Report 2012–1077, 33 p.

U.S. Department of the Interior

KEN SALAZAR, Secretary

U.S. Geological Survey

Marcia K. McNutt, Director

U.S. Geological Survey, Reston, Virginia: 2012

This and other USGS information products are available at http://store.usgs.gov/

U.S. Geological Survey

Box 25286, Denver Federal Center

Denver, CO 80225

To learn about the USGS and its information products visit http://www.usgs.gov/

1-888-ASK-USGS

Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the 

U.S. Government.
iii

Contents

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

Introduction ....................................................................................................................................................1

Purpose and Scope .............................................................................................................................1

Previous Studies ..................................................................................................................................1

Description of Study Area ..................................................................................................................2

Methods ..........................................................................................................................................................2

Source Input Data ................................................................................................................................2

Automated Elevation Data Processing and Organization .............................................................4

Automated Watershed Boundary Delineation ................................................................................8

Web-Based Review System and Additional Quality-Control Processes ....................................8

Computing Watershed Characteristics ............................................................................................9

Limitations to the Delineated Watershed Boundary Accuracy ...................................................9

Summary .......................................................................................................................................................10

References Cited .........................................................................................................................................11

Glossary ........................................................................................................................................................13

Appendixes 

1. Watershed and Characteristics Scripts and Programs ......................................................17

2. Watershed and Characteristics, Methods or Processes ...................................................20

Figures

1. Map showing Texas Commission on Environmental Quality surface-water-quality 

monitoring stations active in 2010, Watershed Boundary Dataset Regions 11, 12, 

and 13 .............................................................................................................................................3

2. Map showing hierarchy and areas for the six nested levels of hydrologic units .............5

3. Map showing digital elevation models (DEMs) for Texas: A, 10-meter DEMs 

mosaicked to cover Watershed Boundary Dataset Regions 11, 12, and 13. 

B, 3-meter DEMs, where available, mosaicked to cover the Texas coastline ..................6

4. Diagram showing conceptual hydrologic flow model of elevation data derivatives. 

A, Example Digital Elevation model (DEM) with elevation values in each cell. 

B, Direction codes (integer numbers) assigned to cells in flow direction grids in part 

A. C, Flow direction grid created from the example DEM in part A; D, Flow direction 

arrows created from the flow direction grid in part C. E, Flow accumulation grid 

created from flow direction grid in part C where the larger numbers and darker 

colors represent greater accumulated flow ...........................................................................7

5. Map showing example of watershed boundaries delineated to the extent of the 

Subbasin boundary defined by the Watershed Boundary Dataset 8-digit hydrologic 

unit code ......................................................................................................................................10

Table

1. Primary input datasets, resolution, and scale used for delineating watersheds of 

active Texas Commission on Environmental Quality surface-water-quality 

monitoring stations, 2010 ............................................................................................................4
iv

Conversion Factors

SI to Inch/Pound

Multiply By To obtain

Length

centimeter (cm) 0.3937 inch (in.)

millimeter (mm) 0.03937 inch (in.)

meter (m) 3.281 foot (ft) 

kilometer (km) 0.6214 mile (mi)

Area

square meter (m2) 10.76 square foot (ft2) 

square kilometer (km2) 0.3861 square mile (mi2)

Volume

cubic meter (m3) 264.2 gallon (gal) 

cubic meter (m3) 0.0002642 million gallons (Mgal) 

cubic hectometer (hm3) 810.7 acre-foot (acre-ft) 

Flow rate

cubic meter per second (m3/s) 35.31 cubic foot per second (ft3/s)

cubic meter per day (m3/d) 35.31 cubic foot per day (ft3/d) 

cubic meter per second (m3/s) 22.83 million gallons per day (Mgal/d) 

Hydraulic gradient

meter per kilometer (m/km) 5.27983 foot per mile (ft/mi) 

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

(NAVD 88).

Horizontal coordinate information is referenced to the North American Datum of 1983 (NAD 83).
v

Acronyms

DEM Digital Elevation Model

DBF Database file format extension (.DBF) 

GIS Geographic Information System

HUC Hydrologic Unit Code

ID Identification number

NHD National Hydrography Dataset

PRISM Parameter-elevation Regressions on Independent Slopes Model

StratMap Strategic Mapping Program

TCEQ Texas Commission on Environmental Quality

TNRIS Texas Natural Resources Information System

USEPA U.S. Environmental Protection Agency

USGS U.S. Geological Survey

VB Visual Basic

WBD Watershed Boundary Dataset

Abstract

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

the Texas Commission on Environmental Quality, developed 

computer scripts and applications to automate the delineation 

of watershed boundaries and compute watershed characteristics for more than 3,000 surface-water-quality monitoring stations in Texas that were active during 2010. Microsoft Visual 

Basic applications were developed using ArcGIS ArcObjects 

to format the source input data required to delineate watershed boundaries. Several automated scripts and tools were 

developed or used to calculate watershed characteristics using 

Python, Microsoft Visual Basic, and the RivEX tool. Automated methods were augmented by the use of manual methods, including those done using ArcMap software. Watershed 

boundaries delineated for the monitoring stations are limited to 

the extent of the Subbasin boundaries in the USGS Watershed 

Boundary Dataset, which may not include the total watershed 

boundary from the monitoring station to the headwaters.

Introduction

The Texas Commission on Environmental Quality 

(TCEQ) Surface Water Quality Monitoring Program maintains 

a database of more than 8,000 surface-water-quality monitoring stations to evaluate physical, chemical, and biological 

characteristics of the State’s surface water. In 2010, more 

than 3,000 of these monitoring stations were actively being 

used. The data collected at each monitoring station are used to 

characterize water quality in Texas surface waters for ongoing 

regulatory activities, such as permitting actions, development 

of water-quality standards, and aquatic-habitat assessments. 

This information is reported to the U.S. Environmental Protection Agency (USEPA) in the Texas Integrated Report for Clean 

Water Act Sections 305(b) (Texas Commission on Environmental Quality, 2010). 

When water quality at a given monitoring station does 

not meet water-quality standards, a plan for remediation is 

developed. Watershed characteristics, such as precipitation, 

elevation, slope, land use, and total drainage area statistics 

are critical components of such plans; these types of data are 

needed for accurate water-quality assessments and can be used 

by the State in the assessment of water-quality-monitoring 

data collected at TCEQ stations. Accordingly, the USGS, in 

cooperation with the TCEQ, delineated high-resolution watershed boundaries and computed selected watershed characteristics for more than 3,000 surface-water-quality monitoring 

stations that were active in Texas during 2010.

Purpose and Scope

This report documents the computer scripts and applications developed to automate the delineation of watershed 

boundaries and compute selected watershed characteristics for 

more than 3,000 surface-water-quality monitoring stations in 

Texas that were active in 2010. The input source data and the 

automated methods used to delineate watershed boundaries 

are described, along with the methods used to compute the 

selected watershed characteristics. Limitations of the watershed boundaries and characteristics are described.

Previous Studies

In 2000, the USGS in cooperation with TCEQ (then 

known as the Texas Natural Resource Conservation Commission) developed a geodatabase of 1:24,000-scale watershed 

boundaries and characteristics in the lower Rio Grande/Rio 

Bravo Basin in Texas. The study area encompassed TCEQ surface-water-quality monitoring stations along the 3,220 kilometers (about 2,000 miles) of streams in the lower Rio Grande/

Rio Bravo Basin in Texas; the watershed database included 

data for watershed boundaries delineated to a 1:24,000-scale, 

selected watershed characteristics, and hydrologic derivative 

datasets (Brown and others, 2000). Brown and others (2000, 

p. 1) stated that “issues such as water quality, water allocation, 

drought, flood management, as well as aquatic habitat protection and management all depend on watershed-level data, and 

watershed boundaries frequently are used in studies dealing 

with these types of issues.” 

Automated Delineation and Characterization of 

Watersheds for more than 3,000 Surface-Water-Quality 

Monitoring Stations Active in 2010 in Texas

By Christy-Ann M. Archuleta, Sophia L. Gonzales, and David R. Maltby II
2 Automated Delineation and Characterization of Watersheds

Brown and others (2000) used an automated watershed 

boundary delineation procedure to create hydrologic datasets 

from 30-meter digital elevation data using Arc/Info software 

version 7.2.1. The automated routines were reviewed by 

Brown and others (2000) using 3.75-minute (1:12,000-scale) 

digital orthophoto quadrangles (DOQs), existing watershed 

boundary maps, and USGS topographic maps, and they found 

the resolution of the elevation datasets at that time did not 

reflect the most recent changes in the landscape and, therefore, 

did not always match the current hydrography as interpreted 

from digital orthoimagery. For watersheds near the Gulf of 

Mexico, where there is little relief, manual methods were used 

to correct the watershed boundaries, as the hydrologic datasets 

did not accurately represent drainage patterns near the coast. 

Brown and others (2000, p. 1) concluded that “the creation of 

a computer-generated, standardized, watershed dataset that is 

vertically integrated with existing hydrography will continue 

to be difficult until revisions can be made to existing source 

datasets. Until such time, manual delineation will be necessary 

to make adjustments to watersheds delineated with automated 

techniques [because of] man-made features and changes in 

the natural landscape that are not reflected in the digital 

elevation data.” Finer scale data (10-meter, and in some 

cases, 3-meter data) has become available for watersheds 

throughout the United States since 2000, facilitating the use 

of automated methods for delineating watersheds and their 

characteristics. 

Description of Study Area

The TCEQ surface-water-quality monitoring stations are 

located in Texas along an approximately 307,700-kilometer 

(about 191,196 miles) stream network. The watershed boundaries and watershed characteristics are described in the context 

of the USGS Watershed Boundary Dataset. All of the streams 

in Texas are located within Regions 11, 12, and 13 of the 

Watershed Boundary Dataset (U.S. Geological Survey, 2011). 

Regions 11, 12, and 13 correspond to the Watershed Boundary 

Dataset 2-digit hydrologic unit codes (fig. 1). 

Methods

Methods for delineating watershed boundaries can be 

categorized as either manual or automated. Manual methods 

include drawing watershed boundaries by hand using a USGS 

topographic paper map and a pencil, or by viewing a digitized 

USGS topographic map on a computer screen while digitally 

drawing watershed boundaries. Another manual watershed 

boundary delineation method uses software packages, such 

as ESRI ArcMap (Environmental Systems Research Institute, 

2012), which delineate watershed boundaries individually 

by using a variety of input datasets and algorithms. Manual 

methods of delineating watershed boundaries are timeconsuming, requiring many hours of interpretation. Automated 

watershed boundary delineation methods use computer scripts, 

custom-programmed computer applications, or both, to automatically apply and repeat the manual methods iteratively. 

Automated methods greatly decrease the time required to 

delineate watershed boundaries. 

In this study, more than 3,000 watershed boundaries 

required delineation. Automated watershed boundary delineation methods were developed to decrease the time required to 

delineate watershed boundaries compared to manual methods. 

The use of automated methods also helps ensure that consistent results are produced efficiently. Automated computer 

methods were developed by using scripts written in the Python 

programming language (Python Software Foundation, 2011) 

and by using scripts and applications written in Microsoft 

Visual Basic. These scripts and applications work with Environmental Systems Research Institute (ESRI) ArcGIS applications (Environmental Systems Research Institute, Inc., 2008a) 

to facilitate completion of the delineation and characterization tasks. While the emphasis of this report is the automated 

methods that were developed, manual methods (when used) 

are described. 

Source Input Data

Source input data were acquired to delineate the watershed boundaries and compute watershed characteristics. 

Table 1 lists the primary input datasets used in this study, 

along with scale and resolution of the data.

The USGS National Elevation Dataset (NED) digital 

elevation models (DEMs) (U.S. Geological Survey, 2009) 

were used to derive the elevation-derivative datasets and 

other terrain information necessary to delineate watershed 

boundaries. Elevation is of particular interest during watershed 

delineation because areas with relatively large amounts of 

topographic relief have well-defined ridges that define watershed boundaries, whereas areas with relatively small amounts 

of relief have poorly defined ridges, making it difficult to 

delineate watershed boundaries. A DEM is a digital data representation of cartographic information in a raster form, consisting of terrain elevation values for ground positions at regularly 

spaced horizontal intervals (U.S. Geological Survey, 2009). 

In geographic information systems (GIS), a raster is a type of 

geospatial data. Rasters are essentially digital images made 

of equal-sized cells organized in rows and columns. Cells in a 

raster can be compared to pixels in a digital picture; each cell 

or pixel in a raster represents information for a specific area of 

a specific size on the surface of the earth. The size of the area 

represented by the cells in a raster is referred to as resolution 

and can vary greatly in size from 1-meter by 1-meter cells 

to 4-kilometer by 4-kilometer cells. Rasters can represent 

discrete data such as land use, or continuous data such as 

temperature or elevation. The USGS National Map Program 

produces the NED DEMs in 30-meter, 10-meter, and 3-meter 

resolution for the conterminous United States (U.S. Geological 

Survey, 2012). 
Methods 3

In addition to the DEMs, other source input data used 

to delineate watershed boundaries were the standardized 

watershed boundaries in the Watershed Boundary Dataset 

(WBD). The WBD divides the United States into 21 Regions 

(U.S. Department of Agriculture, Natural Resources Conservation Service, 2011) and establishes a standardized 

base-line watershed boundary framework, accounting for 

all land and surface areas in the United States (U.S. Department of Agriculture, Natural Resources Conservation Service, 2008). The 21 Regions are divided and subdivided 

into successively smaller hydrologic units forming a hierarchy of surface-water drainage. This hierarchy is classified 

into six levels: Regions, Subregions, Basins, Subbasins, 

Watersheds, and Subwatersheds. Each hydrologic unit in 

the WBD is assigned a unique identifier called a Hydrologic Unit Code (HUC) that correlates to its position 

within the six nested levels of the dataset hierarchy: 2-digit 

codes for Regions; 4-digit codes for Subregions; 6-digit 

codes for Basins; 8-digit codes for Subbasins; 10-digit 

codes for Watersheds, and 12-digit codes for Subwatersheds 

(fig. 2). 

Other source input datasets used were the National 

Land Cover Dataset of 2001 (U.S. Geological Survey, 2008), 

Parameter-elevation Regression on Independent Slopes 

Models (PRISM) (Parameter-elevation Regressions on Independent Slopes Model (PRISM) Climate Group, 2004), the 

Texas Natural Resources Information Service StratMap dataset 

(Texas Water Development Board, Texas Natural Resources 

Information System, 2008), and the National Hydrography 

Dataset (NHD) (U.S. Geological Survey, 2011). The data in 

these datasets were extracted and used to compute the predefined watershed characteristics.

Figure 1. Texas Commission on Environmental Quality surface-water-quality monitoring stations active in 2010, Watershed Boundary 

Dataset Regions 11, 12, and 13.

Region 11 

Arkansas-White-Red

Region 13

Rio Grande

Region 12

Texas Gulf

COLORADO

NEW MEXICO

KANSAS MISSOURI

ARKANSAS

LOUISIANA

OKLAHOMA

TEXAS

0 250 500 KILOMETERS

0 250 500 MILES

Gulf of Mexico

Base from U.S. Geological Survey 1:10,000,000-scale digital data

U.S. Department of Agriculture Natural Resources Conservation

Service Watershed Boundary Dataset, 2011

Texas Centric Mapping System Albers–Equal Area projection

North American Datum of 1983

EXPLANATION

Watershed Boundary Dataset Region, 

 2-digit hydrologic unit code

Texas Commission on Environmental Quality 

 surface-water-quality monitoring station

#

40°

35°

105°

100°

95°

30°

90°

STATES

UNITED

 MEXICO
4 Automated Delineation and Characterization of Watersheds

Automated Elevation Data Processing and 

Organization

The steps used to derive elevation-derivative datasets and 

terrain information necessary to delineate watershed boundaries are as follows:

1. Create a seamless DEM dataset,

2. Extract DEM data by Subbasins,

3. Fill DEMs,

4. Create flow direction grids, and

5. Create flow accumulation grids.

DEM data in 10-meter resolution covering the extent of 

WBD Regions 11, 12 and 13 were mosaicked (electronically 

pieced together) into one seamless dataset for the composite 

area represented by these Regions (fig. 3A); 3-meter DEMs 

were acquired where available (primarily along the Texas 

coast of the Gulf of Mexico) and mosaicked into a seamless 

dataset (fig. 3B). 

A Microsoft Visual Basic Application (hereinafter 

referred to as the “elevation processing application”) was 

developed using ESRI ArcGIS ArcObjects software (hereinafter referred to ArcObjects) to prepare a seamless DEM dataset. 

This DEM dataset was used to create the elevation derivative datasets necessary for delineating watershed boundaries 

as well as to create necessary derivative datasets. For each 

Subbasin in Regions 11, 12 and 13, the elevation processing 

application selects an individual Subbasin and applies a 100-

meter buffer (Environmental Systems Research Institute, Inc., 

2008b) creating a new buffered polygon feature class of the 

Subbasin. The buffered Subbasin feature class is then used to 

extract, or clip the seamless DEM dataset. After the DEM data 

is extracted to match the spatial extent of the buffered Subbasin feature class, the elevation processing application identifies 

sinks in the extracted DEM. 

A sink (also known as a depression or pit) is a cell or 

group of cells in a DEM surrounded by cells with appreciably 

higher elevation values. Sinks may be natural features of the 

landscape represented by the DEM, but many sinks found in 

DEMs are produced from erroneous data. Sinks should be 

accounted for before attempting to delineate watershed boundaries because sinks prevent downslope flow routing of water, 

and the presence of sinks may result in an erroneous flowdirection raster (Environmental Systems Research Institute, 

Inc., 2009a). To account for sinks in the DEMs, the elevation 

processing application initiates the “Fill” function included in 

the ArcGIS Spatial Analyst extension to create filled (sinkless) DEMs for each of the Subbasins for use in creating the 

elevation derivative datasets necessary to delineate watershed 

boundaries. 

Flow direction and flow accumulation grids are elevation 

derivative datasets necessary to delineate watershed boundaries. To create flow direction grids, the elevation processing 

application initiates the “Flow Direction” function in the 

ArcGIS Spatial Analyst extension using the filled DEMs as 

data inputs (fig. 4A). Flow direction grids are rasters where 

cell values are integer numbers (1, 2, 4, 8, 16, 32, 64 or 128) 

representing flow direction codes in 45-degree increments 

of a drop of water from one cell to the next (fig. 4B). Flow 

direction is determined by identifying the neighboring cell 

with the highest positive distance weighted drop (steepest 

descent or maximum drop) (Venkatachalam and others, 2001). 

The direction code assigned to each cell depends on the eight 

neighboring cells; the cell with the steepest descent receives 

the flow and defines the direction of flow from the source 

Table 1. Primary input datasets, resolution, and scale used for delineating watersheds of active Texas Commission on Environmental 

Quality surface-water-quality monitoring stations, 2010.

Dataset Resolution or scale

USGS Digital Elevation Model (DEM)1 3, 10 or 30 meter

Watershed Boundary Dataset (WBD)2 1:24,000 

National Land Cover Database 2001 (NLCD)3 30 meter

Parameter-elevation Regressions on Independent Slopes Model (PRISM)4 4 kilometer

Texas Natural Resources Information Service StratMap Version 2 - 

Transportation5

Accuracy is dependent on geographic area and sources 

used to update those areas

National Hydrography Dataset (NHD)6 1:24,000 

1

U.S. Geological Survey, 2009.

2

U.S. Department of Agriculture, Natural Resources Conservation Service, 2011.

3

U.S. Geological Survey, 2008.

4

PRISM Climate Group, 2004.

5

Texas Water Development Board, Texas Natural Resources Information System, 2006–08.

6

U.S. Geological Survey, 2011.
Methods 5

Figure 2. Hierarchy and areas for the six nested levels of hydrologic units are shown in the above example. Beginning with the Region 

level, the numbering scheme of the units increases by two digits for each subsequent level (from U.S. Geological Survey and U.S. 

Department of Agriculture Natural Resources Conservation Service, 2009, p. 8). 

Hydrologic unit boundary

 Region

 Subregion

 Basin

 Subbasin

 Watershed

 Subwatershed

EXPLANATION

Pacific Northwest

Region 17

Region

1st level, 

2-digit hydrologic unit

Subregion

2d level, 

4-digit hydrologic unit

Basin

3d level, 

6-digit hydrologic unit

Subbasin

4th level, 

8-digit hydrologic unit

Lower Snake

Subregion 1706

Lower Snake

Basin 170601

South Fork Imnaha River 

Subwatershed 170601020101

Upper Imnaha River

Watershed 1706010201

Imnaha Subbasin

Watershed

5th level, 

10-digit hydrologic unit

Subwatershed

6th level, 

12-digit hydrologic unit

17060102

Pacific

Northwest

California

Great Basin

Lower

Colorado Rio

Grande

Alaska

Hawaii

Caribbean

Texas-Gulf

Missouri

Upper

Colorado

Arkansas-White-Red

Lower

Mississippi

Upper

Mississippi

Great Lakes

Ohio

Tennessee

South

Atlantic

Gulf

Mid

Atlantic

New

England

Souris-RedRainy
6 Automated Delineation and Characterization of Watersheds

Figure 3. Digital elevation models (DEMs) for Texas: A, 10-meter DEMs mosaicked to cover Watershed Boundary Dataset Regions 11, 

12, and 13. B, 3-meter DEMs, where available, mosaicked to cover the Texas coastline.

Inset enlarged in fig. 3B

0 250 500 MILES

0 250 500 KILOMETERS

Gulf of Mexico

COLORADO

NEW MEXICO

KANSAS MISSOURI

ARKANSAS

LOUISIANA

OKLAHOMA

TEXAS

Region 12

Texas Gulf

Region 13

Rio Grande

Region 11 

Arkansas-White-Red

A

0 50 100 KILOMETERS

0 50 100 MILES

97°30' 94°30'

30°00'

27°00'

96°00'

28°30'

B

Gulf of Mexico

Base from U.S. Geological Survey 1:10,000,000-scale digital data

National Elevation Dataset 10-meter digital elevation model

U.S. Department of Agriculture Natural Resources Conservation

Service Watershed Boundary Dataset, 2011

Texas Centric Mapping System Albers–Equal Area projection

North American Datum of 1983

Relative elevation

 High

 Low

Watershed Boundary

 Dataset Region, 

 2-digit hydrologic

 unit code

EXPLANATION

40°

35°

105°

100°

95°

30°

90°

STATES

UNITED

 MEXICO
Methods 7

cell (Goodwin and Tarboton, 2004) (figs. 4C and 4D). This 

approach is referred to as an eight direction (D8) flow model 

(Jenson and Domingue, 1988). 

After the flow direction grids are created, the elevation processing application then creates the flow accumulation grids. Flow accumulation grids are the final elevation 

derivative dataset needed to delineate watershed boundaries. 

To create flow accumulation grids, the elevation processing 

application initiates the “Flow Accumulation” function in the 

ArcGIS Spatial Analyst extension using the flow direction 

grids as data inputs. Flow accumulation grids are rasters where 

cell values are floating point numbers representing the number 

of accumulated upstream cells (fig. 4E). Cells with a high flow 

accumulation value are areas of concentrated flow and may be 

used to identify stream channels. Cells with a flow accumulation value of zero are local topographic highs and may be used 

to identify ridges (Jenson and Domingue, 1988). A flow accumulation grid is the equivalent of drainage area measured in 

units of grid cells and may be used to visualize how a drainage 

area accumulates above streams (Olivera and others, 2002). 

The elevation processing application automatically creates personal geodatabases (Environmental Systems Research 

Institute, Inc., 2008a) to organize the data it creates with 

the naming convention of the Subbasin 8-digit HUC. This 

Figure 4. Conceptual hydrologic flow model of elevation data derivatives. A, Example Digital Elevation model (DEM) with elevation 

values in each cell. B, Direction codes (integer numbers) assigned to cells in flow direction grids in part A. C, Flow direction grid created 

from the example DEM in part A; D, Flow direction arrows created from the flow direction grid in part C. E, Flow accumulation grid 

created from flow direction grid in part C where the larger numbers and darker colors represent greater accumulated flow. 

2 2 4 8 0 0 0 0

2 2 4 8 0 1 3 0

1 2 4 8 0 1 7 0

128 2 2 4 0 0 13 0

1 1 1 4 0 1 3 19

This cell is assigned a

cumulative value of

3 because three cells

flow into that cell. 

72 represents land-surface

elevation and could be in

meters or feet. 

72 69 71 58

67 56 49 50

53 44 32 38

58 55 22 31

61 47 21 16

32 64 128

16 1

8 4 2

Cell values indicate direction of

flow. All cells assigned 1 indicate

flow toward the east; 2 southeast;

4 south; 8 southwest; 16 west;

32 northwest; 64 north; and 128

northeast. 

B

C D E

A
8 Automated Delineation and Characterization of Watersheds

personal geodatabase contains the selected Subbasin polygon 

feature class, the buffered Subbasin polygon feature class, the 

extracted DEM, the filled DEM, the flow direction grid, and 

the flow accumulation grid.

Automated Watershed Boundary Delineation

A second Microsoft Visual Basic Application (hereinafter 

referred to as the “watershed processing application”) was 

developed using ArcObjects to delineate watershed boundaries from the elevation derivative datasets produced by the 

elevation processing application. Since flow accumulation 

grids define drainage area, the values in the cells of the flow 

accumulation grids are transformed from a count of cells 

to units of area to define the watershed boundaries. For the 

watershed boundary delineation process, the flow accumulation grids are used to define the area of all cells flowing into 

each downslope cell. Watershed drainage area, or watershed 

boundary, is equal to all cells in a flow accumulation grid 

that drains into a specified pour point (Paybins, 2008). This 

representation of the drainage area is converted into a temporary polygon representing the completed watershed boundary. 

In the watershed processing application, the monitoring station 

location points are the specified points, commonly referred to 

as pour points.

In the watershed processing application, watershed 

boundaries for each monitoring station were delineated in 

eight steps using the monitoring station’s location points, buffered subbasin polygons, and the elevation derivative datasets 

produced by the elevation processing application. In the first 

step, the geodatabase containing the monitoring stations point 

feature class is accessed. In the second step, a monitoring 

station point feature is selected from the monitoring stations 

point feature class, and the longitude and latitude coordinates 

are extracted for the selected monitoring station’s point location. In the third step, the monitoring station’s coordinates are 

compared to the coordinates defining the Subbasin polygon 

boundaries to identify and select the Subbasin 8-digit HUC 

containing the monitoring station’s point. In the fourth step, 

the directory containing the elevation-derivative data for the 

selected Subbasin 8-digit HUC is located using the naming 

convention organization of the data described in the previous 

section. In order to delineate watershed boundaries, the monitoring station’s location must intersect a drainage line on a 

flow accumulation grid. Because the coordinates for the monitoring station’s points were determined with different methods such as topographic map interpretation, or with global 

positioning system (GPS) units with different accuracies, they 

often did not intersect the drainage lines. To rectify this, the 

fifth step of the watershed processing application “snaps” 

(digitally moves in ArcGIS) the monitoring stations’ points to 

the nearest drainage line on the flow accumulation grids using 

the “Snap Pour Point” Spatial Analyst function in ArcGIS. 

This tool searches the area around a specified point within a 

user-specified distance (in this case, 50 meters) for the cell 

of highest accumulated flow on the flow accumulation grid 

and moves the point to that cell location. After the monitoring station’s points are snapped to drainage lines on the flow 

accumulation grids, they are referred to as pour points. Once 

the monitoring station’s points are snapped into pour points, 

the sixth step of the watershed processing application initiates 

the “Calculate Watershed” function in the ArcGIS Spatial 

Analyst extension to determine the cells, or area that drains 

into the cell on the flow accumulation grid that intersects the 

pour point. The Calculate Watershed function uses the flow 

direction grids and the flow accumulation grids to determine 

the area contributing flow to a pour point (Environmental 

Systems Research Institute, Inc., 2009b). The output is a 

raster representation of the watershed boundary that is then 

converted into a temporary vector polygon and added to a 

monitoring station watershed boundary master feature class 

in the seventh step. In the eighth and final step, the pour point 

location is added to a separate monitoring station pour point 

master feature class. 

Web-Based Review System and Additional 

Quality-Control Processes

During an initial testing and quality-control phase of 

this study, a web-based review system was used to facilitate 

quality control of the watershed boundaries, track changes 

to the watershed boundaries, and facilitate TCEQ input. The 

review system included tools for adding geocoded change 

requests to the watershed boundaries. The application was 

designed to reduce the amount of time for completing reviews 

compared to alternative review processes such as routing 

paper maps between offices, or exchanging the changes using 

a geodatabase that would require a GIS Analyst to interpret. 

Instead, the review system allowed TCEQ staff to quickly 

review the watershed boundaries and request changes. USGS 

staff reviewed the changes requested and applied them to the 

watershed boundaries. 

In addition to the web-based review system, USGS staff 

used ESRI ArcMap 9.3 software to compare all of the individual watershed boundaries that were delineated to USGS topographic maps and other base maps, to the seamless 10-meter 

DEM grid, and to aerial photographs. If a watershed boundary 

was found to be inconsistent with the surface-water drainage depicted in the reference material used for comparison, 

the boundary was manually adjusted. Additionally, random 

quality-control checks were performed manually on the pour 

points to ensure they were snapped to the correct stream. The 

names of the monitoring stations were compared to the names 

of the NHD flow lines where the monitoring stations were 

snapped for consistency. Any pour points found in an incorrect location during this quality-control process were manually 

moved to their correct location on the flow accumulation 

grids and run through the watershed processing application 

again.
Methods 9

Computing Watershed Characteristics

The monitoring station watershed boundaries delineated 

were attributed with selected characteristics specified by the 

TCEQ, including: 

• Strahler and Shreve stream order,

• road density,

• minimum, maximum, and average elevation,

• relief,

• 30-year average-annual precipitation,

• land-cover percentages for 16 land-cover classes, 

• riparian land-cover percentages for 14 land-cover 

classes, and

• channel-elevation and channel-length statistics. 

Several automated scripts and tools were developed or 

used to calculate watershed characteristics. Scripts were written using the Python programming language (Python Software 

Foundation, 2011) or Microsoft Visual Basic. Extensions to 

ArcGIS provided by the RivEX Tool (Hornby, 2010) were 

also used to calculate watershed characteristics. Tables of 

watershed characteristics information were related or joined 

to the master monitoring station watershed boundary feature 

class. An overview of the scripts and tools used to compute 

watershed characteristics is provided in appendix 1. Watershed 

characteristics including definition, source input data, and 

scripts used to compute each characteristic are provided in 

appendix 2.

Limitations to the Delineated Watershed 

Boundary Accuracy 

The delineation of watershed boundaries for the surfacewater-quality monitoring stations was limited to the extent of 

the Subbasin boundaries defined by the Watershed Boundary Dataset (WBD) 8-digit hydrologic unit code (fig. 5); the 

delineated watersheds might not include the total watershed 

boundary from the monitoring station to the headwaters. Constraining watershed boundary delineations to Subbasin boundaries relies on the standardized base-line drainage boundary 

framework found in the WBD and vastly increases the speed 

of preparing the DEMs and creating the flow accumulation 

and flow direction grids necessary to delineate watershed 

boundaries. Ensuring that the watershed boundaries delineated 

for this study were coincident with the WBD Subbasin boundaries also allows for consistency with other hydrologic units in 

the WBD discussed in the Source Input Data section. Watershed boundaries produced from the watershed processing 

application were modified, where possible, to be coincident 

to the WBD Subbasin boundary lines using scripts written in 

the Python programming language (Python Software Foundation, 2011) and in Microsoft Visual Basic. These scripts 

codify a series of steps to ensure continuity between watershed 

boundaries. 

In addition to monitoring water quality in streams, the 

TCEQ monitors the quality of water in many reservoirs 

throughout Texas. Reservoirs complicate the process of 

delineating watershed boundaries because they obscure the 

natural drainage system. The size of the pool area and the 

amount of fluctuation in the normal pool area of a reservoir 

further complicates the process of delineating watershed 

boundaries. Because of the difficulty in delineating hydrologic unit boundaries for reservoirs, as described by the 

Federal Guidelines for the Watershed Boundary Dataset 

(U.S. Geological Survey and U.S. Department of Agriculture, 

Natural Resources Conservation Service, 2009), one pour 

point per reservoir was selected to represent the entire reservoir from the most downstream surface-water-monitoring 

station on the reservoir, usually at the dam impounding the 

reservoir. Any additional surface-water-monitoring stations within the reservoir boundary or on the reservoir were 

excluded from the watershed boundary delineation process. 

The monitoring station points selected to represent the reservoir were manually moved in ArcMap 9.3 to a location on 

the flow accumulation grids directly downstream from the 

associated reservoir dam to facilitate watershed boundary 

delineation.
10 Automated Delineation and Characterization of Watersheds

Summary

The Texas Commission on Environmental Quality 

(TCEQ) Surface Water Quality Monitoring Program maintains 

a database of more than 8,000 surface-water-quality monitoring stations to evaluate physical, chemical, and biological 

characteristics of the State’s surface water. In 2010, more than 

3,000 of these monitoring stations were actively in use. The 

data collected at each monitoring station are used to characterize water quality in Texas surface waters for ongoing 

regulatory activities, such as permitting actions, development 

of water-quality standards, and aquatic-habitat assessments. 

Watershed characteristics, such as precipitation, elevation, 

slope, land use, and total drainage area statistics also are critical for ongoing regulatory activities. Accordingly, the U.S. 

Geological Survey (USGS), in cooperation with the TCEQ, 

delineated high-resolution watershed boundaries and computed selected watershed characteristics for more than 3,000 

surface-water-quality monitoring stations that were active in 

Texas during 2010. The USGS National Elevation Dataset 

(NED) digital elevation models (DEMs) were used to derive 

the elevation derivative datasets and terrain information 

necessary to delineate watershed boundaries. In addition to 

the DEMs, other source input data used to delineate watershed 

boundaries were the standardized watershed boundaries in 

the Watershed Boundary Dataset (WBD). Other source input 

datasets used were the National Land Cover Dataset of 2001, 

Parameter-elevation Regression on Independent Slopes Models, the Texas Natural Resources Information Service StratMap dataset, and the National Hydrography Dataset. The data 

in these datasets were extracted and used to compute selected 

watershed characteristics.

Figure 5. Example of watershed boundaries delineated to the extent of the Subbasin boundary defined by the Watershed Boundary 

Dataset 8-digit hydrologic unit code.

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EXPLANATION

Relative elevation

 High

 Low

Watershed boundaries for Texas

 Commission on Environmental

 Quality surface-water-quality 

 monitoring stations

Watershed Boundary Dataset Subbasin,

 8-digit hydrologic unit code

Texas Commission on Environmental Quality 

 surface-water-quality monitoring station

#*

EXPLANATION

97°30'

97°45'

32°45'

97°15'

97°00'

32°30'

33°00'

0 5 10 KILOMETERS

0 5 10 MILES

Base from U.S. Geological Survey 1:10,000,000-scale digital data

National Elevation Dataset 10-meter digital elevation model

U.S. Department of Agriculture Natural Resources Conservation

Service Watershed Boundary Dataset, 2011

Texas Centric Mapping System Albers–Equal Area projection

North American Datum of 1983
References Cited 11

Automated methods were mostly used; these methods 

relied on computer scripts and applications to automatically 

apply and repeat manual methods iteratively. Automated 

methods greatly decrease the time required to delineate watershed boundaries. A Microsoft Visual Basic Application was 

developed to create the elevation-derivative datasets used for 

delineating watershed boundaries. A second Microsoft Visual 

Basic Application was developed to delineate the watershed 

boundaries from the elevation-derivative datasets produced by 

the elevation processing application. During an initial testing 

and quality-control phase of this study, a web-based review 

system was used to facilitate quality control of the watershed 

boundaries, track changes to the watershed boundaries, and 

facilitate TCEQ input. In addition to the web-based review 

system, USGS staff used ArcMap 9.3 software to compare 

all of the individual watershed boundaries that were delineated to USGS topographic maps and other base maps, to 

the seamless 10-meter DEM grid, and to aerial photographs. 

Several automated scripts and tools were developed or used to 

calculate watershed characteristics. Scripts were written using 

the Python programming language or Microsoft Visual Basic. 

Extensions to ArcGIS provided by the RivEX Tool were also 

used to calculate watershed characteristics. The delineation of 

watershed boundaries for the surface-water-quality monitoring 

stations was limited to the extent of the Subbasin boundaries 

defined by the Watershed Boundary Dataset 8-digit hydrologic 

unit code. Watershed boundaries produced from the watershed 

processing application were modified, where possible, by 

using scripts to be coincident to the WBD Subbasin boundary 

lines. 

References Cited

Brown, J.R., Ulery, R.L., and Parcher, J.W., 2000, Creating a standardized watersheds database for the Lower Rio 

Grande/Río Bravo, Texas: U.S. Geological Survey OpenFile Report 2000–065, 17 p.

Environmental Systems Research Institute, Inc., 2008a, 

ArcGIS Desktop 9.2 Help—Types of Geodatabases: 

ArcGIS Desktop 9.2 Help, accessed April 11, 2012 

at http://webhelp.esri.com/arcgisdesktop/9.2/index.

cfm?topicname=types_of_geodatabases.

Environmental Systems Research Institute, Inc., 2008b, Arc 

GIS Desktop 9.3 Help—Creating Buffers: ArcGIS Desktop 

9.3 Help, accessed April 11, 2012 at http://webhelp.esri.

com/arcgiSDEsktop/9.3/index.cfm?TopicName=Creating_

buffers.

Environmental Systems Research Institute, Inc., 2009a, 

ArcGIS Desktop 9.3 Help—Creating a depressionless 

DEM: ArcGIS Desktop 9.3 Help, accessed January 4, 

2011, at http://webhelp.esri.com/arcgisdesktop/9.3/index.

cfm?TopicName=Creating_a_depressionless_DEM.

Environmental Systems Research Institute, Inc., 2009b, ArcGIS Desktop 9.3 Help—Snap Pour Point: ArcGIS Desktop 

9.3 Help, accessed January 4, 2011, at http://webhelp.esri.

com/arcgisdesktop/9.3/index.cfm?id=6261&pid=6253&topi

cname=Snap_Pour_Point.

Environmental Systems Research Institute, 2012, ArcGIS—Mapping and analysis for understanding our world: 

accessed April 20, 2012, at http://www.esri.com/software/

arcgis/.

Goodwin, C.A., and Tarboton, D.G., 2004, Morphometric 

properties, in Goudie, A.S., Encyclopedia of Geomorphology v. 2: New York, Routledge, p. 697. 

Hornby, D. D., 2010, RivEX software (Version X): Available 

from http://www.rivex.co.uk.

Jenson, S.K., and Domingue, J.O., 1988, Extracting topographic structure from digital elevation data for Geographic 

Information System analysis: Photogrammetric Engineering 

and Remote Sensing, v. 54, no.11, p. 1593–1600.

Nagel, D., 2003, ArcGIS instructions for computing road 

density per watershed and identifying stream crossings: U.S. Forest Service, accessed August 25, 2010, at 

http://www.fs.fed.us/rm/boise/research/gis/documents/

ArcGISRoadDensityStreamCrossing.pdf.

Olivera, F., Furnans, J.E., Maidment, D.R., Djokic, D., and 

Ye, Z., 2002, Drainage systems. in Maidment, D.R., Arc 

hydro: GIS for water resources, v. 1: Redlands, California, 

Environmental Systems Research Institute, Inc., p. 70–72. 

Parameter-elevation Regressions on Independent Slopes 

Model (PRISM) Climate Group, 2004, Oregon State University: online at http://prism.oregonstate.edu.

Paybins, K.S., 2008, Basin characteristics for selected streamflow-gaging stations in and near West Virginia: U.S. Geological Survey Open-File Report 2008–1087, 9 p. Available 

at http://pubs.usgs.gov/of/2008/1087.

Python Software Foundation, 2011, Python software foundation home page, accessed October 11, 2011, at http://www.

python.org/psf/.

Shreve, R.L., 1966, Statistical law of stream numbers: Journal 

of Geology, v. 74, p. 17–34.

Shreve, R.L., 1967, Infinite topologically random channel 

networks: Journal of Geology, v. 75, p. 178–186.

Strahler, A.N., 1952, Hypsometric (area-altitude) analysis of 

erosional topography: Geological Society of America Bulletin, v. 63, p. 1120.
12 Automated Delineation and Characterization of Watersheds

Texas Commission on Environmental Quality, 2010, Texas 

integrated report for clean water act sections (305(b) and 

303(d): Texas Commission on Environmental Quality, 

accessed January 18, 2011, at http://www.tceq.state.tx.us/

compliance/monitoring/water/quality/data/wqm/305_303.

html.

Texas Water Development Board, Texas Natural Resources 

Information System, 2008, Strategic mapping program 

(StratMap, version 2—transportation): accessed February 2, 

2011, at http://www.tnris.org/StratMap.

U.S. Department of Agriculture, Natural Resources Conservation Service, 2008, Information about hydrologic units 

and the Watershed Boundary Dataset: Natural Resources 

Conservation Service, accessed February 2, 2011, at 

http://www.ncgc.nrcs.usda.gov/products/datasets/watershed/

datainfo.html.

U.S. Department of Agriculture, Natural Resources Conservation Service, 2011, Geospatial data gateway—Watershed 

boundary dataset–HUC 12: National Cartography and 

Geospatial Center, accessed March 21, 2012, at http://

www.nrcs.usda.gov/wps/portal/nrcs/main/national/water/

watersheds/dataset.

U.S. Environmental Protection Agency, 2006, National 

Hydrography Dataset Plus—NHDPlus, accessed April 

20, 2012, at http://www.epa.gov/waters. 

U.S. Environmental Protection Agency, 2007, MultiResolution Land Characteristics Consortium National Land 

Cover Dataset 2001 Land Cover Class Definitions: U.S. 

Environmental Protection Agency, accessed August 26, 

2010, at http://www.epa.gov/mrlc/definitions.html.

U.S. Geological Survey, 2008, National Land Cover Dataset 

2001: U.S. Geological Survey, accessed February 14, 2010, 

at http://www.mrlc.gov/nlcd2001.php.

U.S. Geological Survey, 2009, Digital Elevation Model: U.S. 

Geological Survey, accessed January 4, 2011, at http://eros.

usgs.gov/#/Guides/dem.

U.S. Geological Survey, 2011, National hydrography dataset: 

U.S. Geological Survey, available at http://nhd.usgs.gov/

index.html.

U.S. Geological Survey, 2012, Seamless data warehouse—

What is elevation?: accessed April 20, 2012, at seamless.

usgs.gov/about_elevation.php.

U.S. Geological Survey and U.S. Department of Agriculture, 

Natural Resources Conservation Service, 2009, Federal 

guidelines, requirements, and procedures for the national 

Watershed Boundary Dataset: U.S. Geological Survey Techniques and Methods 11–A3, 55 p.

Venkatachalam, P., Mohan, B.K., Kotwal, A., Mishra, V., 

Muthuramkrishna, V., and Pandya, M., 2001, Automatic 

delineation of watersheds for hydrological applications: 

Paper presented at the 22nd Asian Conference on Remote 

Sensing, Singapore, November 5–9, 2001.
Glossary 13

Glossary

Application A software program that runs on a computer. 

ArcGIS Server Javascript API An interface implemented 

by the ArcGIS Server software program to enable interaction with other software written in Javascript programming 

language.

Elevation derivatives Topographically derived data sets, 

such as flow accumulation and flow direction. 

Feature class A collection of geographic features with the 

same geometry type (such as point, line, or polygon), the same 

attributes, and the same spatial reference.

Flow accumulation In a raster-based analysis, the total number of cells, including non-neighboring cells that drain into a 

selected cell. 

Flow direction In a raster-based watershed analysis, each 

cell is assumed to drain into one of its eight neighbors (left, 

right, up, down, plus the four diagonals).

Mosaic A GIS function that combines multiple adjacent 

input rasters into a single raster dataset.

NHDPlus A suite of geospatial data products derived from 

the National Hydrography Dataset (NHD), the National Elevation Dataset (30-meter), and the National Watershed Boundary 

Dataset. 

Pour point The point at which water flows out of an area. 

This is usually the lowest point along the boundary of the 

drainage basin. 

Script A list of computer commands written for a specific 

computer program; commonly used to automate processes.

Strategic Mapping Program (StratMap) Produces, maintains, 

and enhances Texas statewide digital geographic data themes 

in partnership with geographic information systems (GIS) 

professionals from public and private organizations. 

Visual Basic (VB) A computer programming system developed and owned by Microsoft, including software tools to 

automatically create the detailed programming required by 

the Windows operating system. These software tools use the 

graphical way that Windows works by letting programmers 

“draw” their systems with a mouse on the computer. This is 

why it is called “Visual” Basic. VB includes everything that is 

necessary to write programs for Windows.

Watershed The entire geographical area drained by a stream 

and its tributaries; an area characterized by all runoff being 

conveyed to the same outlet.

Watershed boundary The ridge or crest line dividing two 

drainage areas. 

Watershed delineation The determination of the boundary 

between watersheds.

Appendixes 1–2

Appendix 1 17

Appendix 1. Watershed and Characteristics Scripts and Programs.

Script or program: CalcRdDist.vbs

Requirements: 

Shapefile of the roads contained within the watershed.

Process: 

Connects to the folder containing all shapefiles of roads per watershed. Opens the .dbf file that is part of the shapefile and sums the values in 

the length column and writes a total value out to a text file.

Output: 

A text file containing each watershed ID and length of roads in that watershed in kilometers.

Script or program: updatewsname.vbs

Requirements: 

Directory of individual shapefiles of watersheds.

Process:

Opens each individual shapefile of the watersheds, creates a column (WsId), and populates it with the watershed ID from the file name.

Output: 

A new column, WsId, in each individual watershed shapefile with the watershed ID of that file.

Script or program: pPointtoSHP.vbs

Requirements: 

Directory of raster pour points.

Process: 

Converts each pour point raster to a point shapefile.

Output: 

Shapefile of pour points. 

Script or program: SplitLayerByAttributes.py

Requirements:

A feature class or shapefile with a unique identifier in text format.

Process: 

Splits all features in a shapefile or feature class into individual feature classes or shapefiles based on a unique identifier.

Output:

Shapefiles or feature classes split from the input file.

Script or program: convert_ws2grd.vbs

Requirements:

Input directory of shapefiles.

Process: 

Converts all shapefiles in a given directory to individual raster GRIDS in an output directory.

Output: 

A directory of GRIDs, one for each shapefile in the input directory.

Appendix 1
18 Automated Delineation and Characterization of Watersheds

Script or program: Zonalstats_grd.vbs

Requirements:

Thematic raster data, input directory of rasters to process.

Process: 

Calculates zonal statistics (mean, minimum, maximum, sum, range, and standard deviation) of a raster cell values for a grid.

Output: 

Fills a directory with DBF tables of zonal statistics, one for each input.

Script or program: GNISidMatch.py

Requirements:

NHD Streams with GNIS_ID field populated, pour points.

Process: 

Creates a new feature class containing only stream segments with GNIS_ID’s matching monitoring point GNIS_IDs.

Output: 

A feature class containing NHD stream segments for water monitoring locations.

Script or program: mainchannelextration.py

Requirements:

NHD stream segments, watershed boundaries, pour points.

Process: 

Clips each set of stream segments with matching GNIS_ID’s to the boundary of a watershed. 

Output: 

A feature class containing a main channel for each monitoring point.

Script or program: mcs1km.py 

Requirements:

Main channels for pour points, pour points.

Process: 

Creates a route event from the main channel segments and a route event 1 kilometer upstream from a pour point of a main channel. Splits 

the main channel with the “to” node, calculates elevation for “FROM” and “TO” nodes, and calculates slopes for distance 1 kilometer 

from the pour point. 

Output: 

A feature class containing “FROM” and “TO” nodes for each monitoring station and the distance 1 kilometer upstream from the pour point, 

1-km stream segments, and “FROM” and “TO” nodes for monitoring point and point 1 kilometer from monitoring point.

Script or program: mcs_10_85

Requirements: 

Main channel stream segments and pour points.

Process:

Creates a route from the main channel segments, and routes flow from a pour point along a stream channel. Splits the main channel with the 

route events node, extracts elevation values for 10 percent and 85 percent nodes representing 10 and 85 percent of the flow in the channel, 

respectively, and calculates slopes for the distance between the 10 and 85 percent node points.

Output: 

A table with 10 to 85 percent elevation and slope values for each monitoring point. 
Appendix 1 19

Script or program: riparianbuffer.py

Requirements: 

Stream segments, “FROM” and “TO” nodes for pour points and distance 1 kilometer upstream from pour point along a stream.

Process: 

Splits stream segment 1 kilometer from a pour point, then buffers the resulting stream segment by 50 meters.

Output: 

A feature class containing 1-kilometer by 50-meter buffers along stream channel for each monitoring point.

Script or program: WatershedCalc.vbp

Requirements: 

Elevation derivatives, pour point feature class in a personal geodatabase, Subbasin feature class in a personal geodatabase.

Process: 

Opens the point feature class looping through each point; determines which HUC-8 code the point falls in; uses the corresponding elevation 

derivatives for which the point falls in; calculates a watershed boundary and pour point.

Output: 

A watershed shapefile per point and a raster pour point.
20 Automated Delineation and Characterization of Watersheds

Appendix 2. Watershed and Characteristics, Methods or Processes

Attribute: Strahler stream order

Description: 

Numerical assignment of a segment of a stream within a stream network. Stream segments at the headwaters (top) of a stream are first-order 

streams. When two first-order streams come together, they form a second-order stream. When two second-order streams come together, 

they form a third-order stream. Stream order only increases when streams of the same order intersect. Therefore, the intersection of a firstorder and second-order stream will remain a second-order stream rather than create a third-order stream (Strahler, 1952).

Method or process: 

The Strahler stream order was calculated using the RivEX Tool (Hornby, 2010).

Unit: (What unit is the attribute in?)

Integer.

Source data used: 

NHD Plus Hydrography vector data (U.S. Environmental Protection Agency, 2006).

Attribute: Shreve stream order

Description:

Numerical assignment of a segment of a stream within a stream network. Stream segments at the headwaters (top) of a stream are first-order 

streams. When two first-order streams come together, they form a second-order stream. When two second-order streams come together, 

they form a fourth-order stream. Magnitudes are additive downslope. When two streams intersect, their magnitudes are added and assigned to the downslope stream (Shreve, 1966; Shreve, 1967).

Method or process: 

The Shreve stream order was calculated using RivEX Tool (Hornby, 2010).

Unit: 

Integer.

Source data used: 

NHD Plus Hydrography vector data (U.S. Environmental Protection Agency, 2006).

Attribute: road density

Description: 

Sum of the length of roads in kilometers in a watershed (county roads and larger) divided by the watershed area in kilometers squared 

(Nagel, 2003).

Method or process: 

 CalcRdDist.vbs. 

Unit:

Kilometers squared.

Source data used: 

Stratmap Phase 2 road network (Texas Water Development Board, Texas Natural Resources Information System, 2008).

Appendix 2
Appendix 2 21

Attribute: average elevation

Description: 

Average elevation of the entire watershed.

Method or process: 

Zonal_Stats_grd.vbs.

Unit: 

Meters.

Source data used: 

National Elevation Dataset (U.S. Geological Survey, 2009).

Attribute: minimum elevation

Description: 

Minimum elevation in the watershed.

Method or process: 

Zonal_Stats_grd.vbs.

Unit: 

Meters.

Source data used: 

National Elevation Dataset DEM (U.S. Geological Survey, 2009).

Attribute: maximum elevation

Description: 

Maximum elevation in the watershed.

Method or process: 

Zonal_Stats_grd.vbs.

Unit: 

Meters.

Source data used: 

National Elevation Dataset DEM (U.S. Geological Survey, 2009).

Attribute: relief

Description: 

Relief of the entire watershed.

Method or process: 

Query calculation in ArcGIS: maximum elevation – minimum elevation.

Unit: 

Meters.

Source data used: 

National Elevation Dataset DEM (U.S. Geological Survey, 2009).
22 Automated Delineation and Characterization of Watersheds

Attribute: average 30-year precipitation

Description: 

Average annual precipitation for 1980–2009 for the entire watershed.

Method or process: 

Zonal_Stats_grd.vbs.

Unit: 

MM*100.

Source data used: 

PRISM (Parameter-elevation Regressions on Independent Slopes Model) aggregated datasets (Parameter-elevation Regressions on Independent Slopes Model (PRISM) Climate Group, 2004).

Attribute: main channel – 10 percent length

Description: 

Length of 10 percent of a main channel upstream from a monitoring station.

Method or process: 

MCS_10_85.py.

Unit: 

Meters.

Source data used: 

National Elevation Dataset DEM (U.S. Geological Survey, 2009) and National Hydrography Dataset (U.S. Geological Survey, 2011).

Attribute: main channel – 10 percent point elevation

Description: 

Elevation found at a point representing 10 percent of the length of a main channel upstream from a monitoring station.

Method or process: 

MCS_10_85.py.

Unit: 

Meters.

Source data used: 

National Elevation Dataset DEM (U.S. Geological Survey, 2009) and National Hydrography Dataset (U.S. Geological Survey, 2011).

Attribute: main channel – 10 percent to 85 percent length 

Description: 

Distance between a point 10 percent upstream from a main channel from a monitoring station and a point 85 percent upstream from a main 

channel from the same monitoring station.

Method or process: 

MCS_10_85.py

Unit:

Meters.

Source data used: 

National Elevation Dataset DEM (U.S. Geological Survey, 2009) and National Hydrography Dataset (U.S. Geological Survey, 2011).
Appendix 2 23

Attribute: main channel – 85 percent length

Description: 

Length of 85 percent of the main channel upstream from the monitoring station.

Method or process: 

MCS_10_85.py.

Unit: 

Meters.

Source data used: 

National Elevation Dataset DEM (U.S. Geological Survey, 2009) and National Hydrography Dataset (U.S. Geological Survey, 2011).

Attribute: main channel – 85 percent point elevation

Description: 

Elevation found at a point 85 percent upstream from a main channel from a monitoring station.

Method or process: 

MCS_10_85.py

Unit: 

Meters.

Source data used:

National Elevation Dataset DEM (U.S. Geological Survey, 2009) and National Hydrography Dataset (U.S. Geological Survey, 2011)

Attribute: main channel – 10 percent to 85 percent slope

Description: 

S10-85 = DE10-85/L10-85, in which DE10-85 is the difference in elevation between a point 85 percent upstream from a monitoring station 

on a main channel and a point 10 percent upstream from a monitoring station divided by the distance between those two points.

Method or process: 

MCS_10_85.py.

Unit: 

Unit-less ratio.

Source data used: 

National Elevation Dataset DEM (U.S. Geological Survey, 2009) and National Hydrography Dataset (U.S. Geological Survey, 2011).

Attribute: main channel – pour point elevation

Description: 

Elevation at a monitoring station along its main channel.

Method or process: 

ArcGIS “Extract Values to Points” tool, using DEM and pour points as input.

Unit: 

Meters.

Source data used: 

National Elevation Dataset DEM (U.S. Geological Survey, 2009) and National Hydrography Dataset (U.S. Geological Survey, 2011).
24 Automated Delineation and Characterization of Watersheds

Attribute: main channel - farthest point elevation

Description: 

Elevation at the farthest point upstream in a main channel from a monitoring station.

Method or process: 

ArcGIS “Extract Values to Points” tool, using DEM and point at end of channel upstream from monitoring station as input.

Unit: 

Meters.

Source data used: 

National Elevation Dataset DEM (U.S. Geological Survey, 2009) and National Hydrography Dataset (U.S. Geological Survey, 2011).

Attribute: main channel – farthest point length kilometers

Description: 

Distance measured along the main channel of the watershed from the pour point upstream to the intersection of the main channel and the 

HUC-08 boundary or the headwaters.

Method or process: 

Query calculation in ArcGIS: length between monitoring point and end of channel in kilometers.

Unit: 

Kilometers.

Source data used: 

National Elevation Dataset DEM (U.S. Geological Survey, 2009) and National Hydrography Dataset (U.S. Geological Survey, 2011).

Attribute: main channel – farthest point length meters

Description: 

Distance measured along the main channel of the watershed from the pour point upstream to the intersection of the main channel and the 

HUC-08 boundary or the headwaters. 

Method or process: 

Query calculation in ArcGIS: length between monitoring point and end of channel in meters.

Unit:

Meters.

Source data used: 

National Elevation Dataset DEM (U.S. Geological Survey, 2009) and National Hydrography Dataset (U.S. Geological Survey, 2011).

Attribute: slope

Description: 

Sc = DEc/Lc, In which DEc is the difference in elevation between the points defining the upper end of a channel and a monitoring station, 

and Lc is the length of the channel between the same two points.

Method or process: 

Query calculation in ArcGIS: (elevation at monitoring point – elevation at end of channel upstream from monitoring station) / length of 

channel between those points.

Unit: 

Unit-less ratio.

Source data used: 

National Elevation Dataset DEM (U.S. Geological Survey, 2009) and National Hydrography Dataset (U.S. Geological Survey, 2011).
Appendix 2 25

Attribute: main channel – sinuosity ratio

Description: 

Describes the bending or curving shape of a channel. Actual main channel length divided by straight-line distance. Computed by dividing 

the channel length by valley length (CL/VL). It is an approximate measurement of the degree to which a stream channel meanders within 

its valley (Paybins, 2008).

Method or process:

Query calculation in ArcGIS: channel length / straight line distance as inputs.

Unit: 

Unit-less ratio.

Source data used: 

National Elevation Dataset DEM (U.S. Geological Survey, 2009) and National Hydrography Dataset (U.S. Geological Survey, 2011).

Attribute: main channel slope

Description: 

Rate of elevation change along a main channel. S = DE/L, where DE is the difference in elevation between the end point of the principal 

flow path and the monitoring station, divided by the hydrologic length of the flow path (L).

Method or process: 

Query calculation in ArcGIS: (elevation at the monitoring station – the elevation at the end of the main channel) / the main channel distance.

Unit: 

Ratio.

Source data used: 

National Elevation Dataset DEM (U.S. Geological Survey, 2009) and National Hydrography Dataset (U.S. Geological Survey, 2011).

Attribute: main channel slope – 1km point

Description: 

S = DE/L, where DE is the difference in elevation between a point 1 km from a monitoring station and the monitoring station point, divided 

by the hydrologic length of the flow path (L).

Method or process: 

MCS1KM.py.

Unit: 

Ratio.

Source data used: 

National Elevation Dataset DEM (U.S. Geological Survey, 2009) and National Hydrography Dataset (U.S. Geological Survey, 2011).

Attribute: pour point elevation

Description: 

Elevation found at a monitoring station.

Method or process: 

MCS1KM.py.

Unit: 

Meters.

Source data used: 

National Elevation Dataset DEM (U.S. Geological Survey, 2009) and National Hydrography Dataset (U.S. Geological Survey, 2011).
26 Automated Delineation and Characterization of Watersheds

Attribute: main channel straight line distance

Description:

Straight-line distance between a monitoring station and the end of the main channel upstream.

Method or process: 

ArcGIS Point to Line tool, with end nodes of main-channel segments (between monitoring station and end of channel) as inputs.

Unit: 

Meters.

Source data used: 

National Elevation Dataset DEM (U.S. Geological Survey, 2009) and National Hydrography Dataset (U.S. Geological Survey, 2011).

Attribute: land cover – percent open water

Description: 

Percent Open Water - All areas of open water, generally with less than 25 percent cover of vegetation or soil (U.S. Geological Survey, 

2008).

Method or process: 

Tabulate Area tool in the Spatial Analyst Extension of ArcGIS10 iterated in Model Builder.

Unit: 

Decimal percent of total area.

Source data used: 

National Land Cover Dataset of 2001 (U.S. Geological Survey, 2008; U.S. Environmental Protection Agency, 2007)

Attribute: land cover – percent developed, open space

Description: 

Percent Developed, Open Space - Includes areas with a mixture of some constructed materials, but mostly vegetation in the form of lawn 

grasses. Impervious surfaces account for less than 20 percent of total cover. These areas most commonly include large lot single-family 

housing units, parks, golf courses, and vegetation planted in developed settings for recreation, erosion control, or aesthetic purposes (U.S. 

Geological Survey, 2008).

Method or process: 

Tabulate Area tool in the Spatial Analyst Extension of ArcGIS10 iterated in Model Builder.

Unit:

Decimal percent of total area.

Source data used:

National Land Cover Dataset of 2001 (U.S. Geological Survey, 2008; U.S. Environmental Protection Agency, 2007)

Attribute: land cover – percent developed, low intensity

Description: 

Percent Developed, Low Intensity - Includes areas with a mixture of constructed materials and vegetation. Impervious surfaces account for 

20–49 percent of total cover. These areas most commonly include single-family housing units (U.S. Geological Survey, 2008).

Method or process: 

Tabulate Area tool in the Spatial Analyst Extension of ArcGIS10 iterated in Model Builder.

Unit: 

Decimal percent of total area.

Source data used: 

National Land Cover Dataset of 2001 (U.S. Geological Survey, 2008; U.S. Environmental Protection Agency, 2007)
Appendix 2 27

Attribute: land cover – percent developed, medium intensity 

Description: 

Percent Developed, Medium Intensity - Includes areas with a mixture of constructed materials and vegetation. Impervious surfaces account for 50–79 percent of the total cover. These areas most commonly include single-family housing units (U.S. Geological Survey, 

2008).

Method or process:

Tabulate Area tool in the Spatial Analyst Extension of ArcGIS10 iterated in Model Builder.

Unit: 

Decimal percent of total area.

Source data used:

National Land Cover Dataset of 2001 (U.S. Geological Survey, 2008; U.S. Environmental Protection Agency, 2007)

Attribute: land cover – percent developed, high intensity

Description: 

Percent Developed, High Intensity - Includes highly developed areas where people reside or work in high numbers. Examples include 

apartment complexes, row houses, and commercial/industrial. Impervious surfaces account for 80 to100 percent of the total cover (U.S. 

Geological Survey, 2008).

Method or process: 

Tabulate Area tool in the Spatial Analyst Extension of ArcGIS10 iterated in Model Builder.

Unit: (What unit is the attribute in?)

Decimal percent of total area.

Source data used: 

National Land Cover Dataset of 2001 (U.S. Geological Survey, 2008; U.S. Environmental Protection Agency, 2007)

Attribute: land cover – percent barren land

Description: 

Percent Barren Land (Rock/Sand/Clay) - Barren areas of bedrock, desert pavement, scarps, talus, slides, volcanic material, glacial debris, 

sand dunes, strip mines, gravel pits, and other accumulations of earthen material. Generally, vegetation accounts for less than 15 percent 

of total cover (U.S. Geological Survey, 2008).

Method or process: 

Tabulate Area tool in the Spatial Analyst Extension of ArcGIS10 iterated in Model Builder.

Unit: (What unit is the attribute in?)

Decimal percent of total area.

Source data used: 

National Land Cover Dataset of 2001 (U.S. Geological Survey, 2008; U.S. Environmental Protection Agency, 2007)

Attribute: land cover – percent deciduous forest

Description:

Percent Deciduous Forest - Areas dominated by trees generally greater than 5 meters tall, and greater than 20 percent of total vegetation 

cover. More than 75 percent of the tree species shed foliage simultaneously in response to seasonal change (U.S. Geological Survey, 

2008).

Method or process: 

Tabulate Area tool in the Spatial Analyst Extension of ArcGIS10 iterated in Model Builder.

Unit: 

Decimal percent of total area.

Source data used: 

National Land Cover Dataset of 2001 (U.S. Geological Survey, 2008; U.S. Environmental Protection Agency, 2007)
28 Automated Delineation and Characterization of Watersheds

Attribute: land cover – percent evergreen forest

Description: 

Percent Evergreen Forest - Areas dominated by trees generally greater than 5 meters tall, and greater than 20 percent of total vegetation 

cover. More than 75 percent of the tree species maintain their leaves all year. Canopy is never without green foliage (U.S. Geological 

Survey, 2008).

Method or process: 

Tabulate Area tool in the Spatial Analyst Extension of ArcGIS10 iterated in Model Builder.

Unit:

Decimal percent of total area.

Source data used: 

National Land Cover Dataset of 2001 (U.S. Geological Survey, 2008; U.S. Environmental Protection Agency, 2007)

Attribute: Land cover – percent mixed forest

Description: 

Percent Mixed Forest - Areas dominated by trees generally greater than 5 meters tall, and greater than 20 percent of total vegetation cover. 

Neither deciduous nor evergreen species are greater than 75 percent of total tree cover (U.S. Geological Survey, 2008).

Method or process:

Tabulate Area tool in the Spatial Analyst Extension of ArcGIS10 iterated in Model Builder.

Unit: 

Decimal percent of total area.

Source data used: 

National Land Cover Dataset of 2001 (U.S. Geological Survey, 2008; U.S. Environmental Protection Agency, 2007)

Attribute: land cover – percent shrub scrub

Description: 

Percent Shrub/Scrub - Areas dominated by shrubs less than 5 meters tall with shrub canopy typically greater than 20 percent of total 

vegetation. This class includes true shrubs, young trees in an early successional stage, or trees stunted by environmental conditions (U.S. 

Geological Survey, 2008).

Method or process: 

Tabulate Area tool in the Spatial Analyst Extension of ArcGIS10 iterated in Model Builder.

Unit: 

Decimal percent of total area.

Source data used: 

National Land Cover Dataset of 2001 (U.S. Geological Survey, 2008; U.S. Environmental Protection Agency, 2007)

Attribute: land cover – percent grassland/herbaceous

Description: 

Percent Grassland/Herbaceous - Areas dominated by grammanoid or herbaceous vegetation, generally greater than 80 percent of total vegetation. These areas are not subject to intensive management such as tilling but can be utilized for grazing (U.S. Geological Survey, 2008).

Method or process: 

Tabulate Area tool in the Spatial Analyst Extension of ArcGIS10 iterated in Model Builder.

Unit: 

Decimal percent of total area.

Source data used:

National Land Cover Dataset of 2001 (U.S. Geological Survey, 2008; U.S. Environmental Protection Agency, 2007)
Appendix 2 29

Attribute: land cover – percent pasture/hay

Description: 

Percent Pasture/Hay - Areas of grasses, legumes, or grass-legume mixtures planted for livestock grazing or the production of seed or hay 

crops, typically on a perennial cycle. Pasture/hay vegetation accounts for greater than 20 percent of total vegetation (U.S. Geological 

Survey, 2008).

Method or process: 

Tabulate Area tool in the Spatial Analyst Extension of ArcGIS10 iterated in Model Builder.

Unit: 

Decimal percent of total area.

Source data used: 

National Land Cover Dataset of 2001 (U.S. Geological Survey, 2008; U.S. Environmental Protection Agency, 2007)

Attribute: land cover – percent cultivated crops

Description: 

Percent Cultivated Crops - Areas used for the production of annual crops, such as corn, soybeans, vegetables, tobacco, and cotton, and also 

perennial woody crops such as orchards and vineyards. Crop vegetation accounts for greater than 20 percent of total vegetation. This class 

also includes all land being actively tilled (U.S. Geological Survey, 2008).

Method or process: 

Tabulate Area tool in the Spatial Analyst Extension of ArcGIS10 iterated in Model Builder.

Unit: 

Decimal percent of total area.

Source data used: 

National Land Cover Dataset of 2001 (U.S. Geological Survey, 2008; U.S. Environmental Protection Agency, 2007)

Attribute: land cover – percent woody wetlands

Description: 

Percent Woody Wetlands - Areas where forest or shrubland vegetation accounts for greater than 20 percent of vegetative cover and the soil 

or substrate is periodically saturated with or covered with water (U.S. Geological Survey, 2008).

Method or process:

Tabulate Area tool in the Spatial Analyst Extension of ArcGIS10 iterated in Model Builder.

Unit: 

Decimal percent of total area.

Source data used: 

National Land Cover ; (U.S. Geological Survey, 2008; U.S. Environmental Protection Agency, 2007)

Attribute: land cover – percent emergent herbaceous wetlands

Description: 

Percent Emergent Herbaceous Wetlands - Areas where perennial herbaceous vegetation accounts for greater than 80 percent of vegetative 

cover and the soil or substrate is periodically saturated with or covered with water (U.S. Geological Survey, 2008).

Method or process: 

Tabulate Area tool in the Spatial Analyst Extension of ArcGIS10 iterated in Model Builder.

Unit: 

Decimal percent of total area.

Source data used:

National Land Cover Dataset of 2001 (U.S. Geological Survey, 2008; U.S. Environmental Protection Agency, 2007)
30 Automated Delineation and Characterization of Watersheds

Attribute: land cover – percent no data

Description: 

No land cover data available (U.S. Geological Survey, 2008).

Method or process: 

Tabulate Area tool in the Spatial Analyst Extension of ArcGIS10 iterated in Model Builder.

Unit: 

Decimal percent of total area.

Source data used: 

National Land Cover Dataset of 2001 (U.S. Geological Survey, 2008; U.S. Environmental Protection Agency, 2007)

Attribute: riparian land cover – percent open water

Description: 

Percent Open Water of riparian area - All areas of open water, generally with less than 25 percent cover of vegetation or soil (U.S. Geological Survey, 2008).

Method or process:

Tabulate Area tool in the Spatial Analyst Extension of ArcGIS10 iterated in Model Builder.

Unit: 

Decimal percent of total area.

Source data used:

National Land Cover Dataset of 2001 (U.S. Geological Survey, 2008; U.S. Environmental Protection Agency, 2007)

Attribute: riparian land cover – percent developed, open space

Description: 

Percent Developed, Open Space of riparian area - Includes areas with a mixture of some constructed materials, but mostly vegetation in 

the form of lawn grasses. Impervious surfaces account for less than 20 percent of total cover. These areas most commonly include large 

lot single-family housing units, parks, golf courses, and vegetation planted in developed settings for recreation, erosion control, or aesthetic purposes (U.S. Geological Survey, 2008).

Method or process: 

Tabulate Area tool in the Spatial Analyst Extension of ArcGIS10 iterated in Model Builder.

Unit: 

Decimal percent of total area.

Source data used: 

National Land Cover Dataset of 2001 (U.S. Geological Survey, 2008; U.S. Environmental Protection Agency, 2007)

Attribute: riparian land cover – percent developed, low intensity

Description: 

Percent Developed, Low Intensity of riparian area - Includes areas with a mixture of constructed materials and vegetation. Impervious surfaces account for 20-49 percent of total cover. These areas most commonly include single-family housing units (U.S. Geological 

Survey, 2008).

Method or process: 

Tabulate Area tool in the Spatial Analyst Extension of ArcGIS10 iterated in Model Builder.

Unit: 

Decimal percent of total area.

Source data used: 

National Land Cover Dataset of 2001 (U.S. Geological Survey, 2008; U.S. Environmental Protection Agency, 2007)
Appendix 2 31

Attribute: riparian land cover – percent developed, medium intensity

Description: 

Percent Developed, Medium Intensity of riparian area - Includes areas with a mixture of constructed materials and vegetation. Impervious surfaces account for 50-79 percent of the total cover. These areas most commonly include single-family housing units (U.S. Geological Survey, 2008).

Method or process: 

Tabulate Area tool in the Spatial Analyst Extension of ArcGIS10 iterated in Model Builder.

Unit: 

Decimal percent of total area.

Source data used: 

National Land Cover ; (U.S. Geological Survey, 2008)

Attribute: riparian land cover – percent developed, high intensity

Description: 

Percent Developed, High Intensity of riparian area - Includes highly developed areas where people reside or work in high numbers. 

Examples include apartment complexes, row houses, and commercial/industrial. Impervious surfaces account for 80 to100 percent of the 

total cover (U.S. Geological Survey, 2008).

Method or process: 

Tabulate Area tool in the Spatial Analyst Extension of ArcGIS10 iterated in Model Builder.

Unit: 

Decimal percent of total area.

Source data used: 

National Land Cover Dataset of 2001 (U.S. Geological Survey, 2008)

Attribute: riparian land cover – percent barren land

Description: 

Percent Barren Land (Rock/Sand/Clay) of riparian area - Barren areas of bedrock, desert pavement, scarps, talus, slides, volcanic material, glacial debris, sand dunes, strip mines, gravel pits, and other accumulations of earthen material. Generally, vegetation accounts for 

less than 15 percent of total cover (U.S. Geological Survey, 2008).

Method or process:

Tabulate Area tool in the Spatial Analyst Extension of ArcGIS10 iterated in Model Builder.

Unit: 

Decimal percent of total area.

Source data used: 

National Land Cover Dataset of 2001 (U.S. Geological Survey, 2008)

Attribute: riparian land cover – percent deciduous forest

Description: 

Percent Deciduous Forest of riparian area - Areas dominated by trees generally greater than 5 meters tall and greater than 20 percent of 

total vegetation cover. More than 75 percent of the tree species shed foliage simultaneously in response to seasonal change (U.S. Geological Survey, 2008).

Method or process:

Tabulate Area tool in the Spatial Analyst Extension of ArcGIS10 iterated in Model Builder.

Unit: 

Decimal percent of total area.

Source data used: 

National Land Cover Dataset of 2001 (U.S. Geological Survey, 2008)
32 Automated Delineation and Characterization of Watersheds

Attribute: riparian land cover – percent evergreen forest

Description: 

Percent Evergreen Forest of riparian area - Areas dominated by trees generally greater than 5 meters tall and greater than 20 percent of 

total vegetation cover. More than 75 percent of the tree species maintain their leaves all year. Canopy is never without green foliage (U.S. 

Geological Survey, 2008).

Method or process: 

Tabulate Area tool in the Spatial Analyst Extension of ArcGIS10 iterated in Model Builder.

Unit: 

Decimal percent of total area.

Source data used: 

National Land Cover Dataset of 2001 (U.S. Geological Survey, 2008)

Attribute: riparian Land cover – percent mixed forest

Description: 

Percent Mixed Forest of riparian area - Areas dominated by trees generally greater than 5 meters tall and greater than 20 percent of total 

vegetation cover. Neither deciduous nor evergreen species are greater than 75 percent of total tree cover (U.S. Geological Survey, 2008).

Method or process: 

Tabulate Area tool in the Spatial Analyst Extension of ArcGIS10 iterated in Model Builder.

Unit: 

Decimal percent of total area.

Source data used: 

National Land Cover Dataset of 2001 (U.S. Geological Survey, 2008)

Attribute: riparian land cover – percent shrub scrub

Description: 

Percent Shrub/Scrub of riparian area - Areas dominated by shrubs less than 5 meters tall with shrub canopy typically greater than 20 

percent of total vegetation. This class includes true shrubs, young trees in an early successional stage, or trees stunted by environmental 

conditions (U.S. Geological Survey, 2008).

Method or process: 

Tabulate Area tool in the Spatial Analyst Extension of ArcGIS10 iterated in Model Builder.

Unit: 

Decimal percent of total area.

Source data used: 

National Land Cover Dataset of 2001 (U.S. Geological Survey, 2008)

Attribute: riparian land cover – percent grassland/herbaceous

Description: 

Percent grassland/herbaceous of riparian area - Areas dominated by grammanoid or herbaceous vegetation, generally greater than 80 

percent of total vegetation. These areas are not subject to intensive management such as tilling, but can be utilized for grazing (U.S. Geological Survey, 2008).

Method or process: 

Tabulate Area tool in the Spatial Analyst Extension of ArcGIS10 iterated in Model Builder.

Unit: 

Decimal percent of total area.

Source data used: 

National Land Cover Dataset of 2001 (U.S. Geological Survey, 2008)
Appendix 2 33

Attribute: riparian land cover – percent pasture/hay

Description: 

Percent Pasture/Hay of riparian area - Areas of grasses, legumes, or grass-legume mixtures planted for livestock grazing or the production of seed or hay crops, typically on a perennial cycle. Pasture/hay vegetation accounts for greater than 20 percent of total vegetation 

(U.S. Geological Survey, 2008).

Method or process: 

Tabulate Area tool in the Spatial Analyst Extension of ArcGIS10 iterated in Model Builder.

Unit: 

Decimal percent of total area.

Source data used: 

National Land Cover Dataset of 2001 (U.S. Geological Survey, 2008)

Attribute: riparian land cover – percent cultivated crops

Description: 

Percent Cultivated Crops of riparian area - Areas used for the production of annual crops, such as corn, soybeans, vegetables, tobacco, 

and cotton, and also perennial woody crops such as orchards and vineyards. Crop vegetation accounts for greater than 20 percent of total 

vegetation. This class also includes all land being actively tilled (U.S. Geological Survey, 2008).

Method or process: 

Tabulate Area tool in the Spatial Analyst Extension of ArcGIS10 iterated in Model Builder.

Unit: 

Decimal percent of total area.

Source data used: 

National Land Cover Dataset of 2001 (U.S. Geological Survey, 2008)

Attribute: riparian land cover – percent emergent herbaceous wetlands

Description: 

Percent Emergent Herbaceous Wetlands of riparian area- Areas where perennial herbaceous vegetation accounts for greater than 80 

percent of vegetative cover, and the soil or substrate is periodically saturated with or covered with water (U.S. Geological Survey, 2008).

Method or process: 

Tabulate Area tool in the Spatial Analyst Extension of ArcGIS10 iterated in Model Builder.

Unit: 

Decimal percent of total area.

Source data used: 

National Land Cover Dataset of 2001 (U.S. Geological Survey, 2008)
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Information regarding water resources in Texas is available at 

http://tx.usgs.gov/
 
Archuleta, Gonzales, and Maltby—Automated Delineation and Characterization of Watersheds—OFR 2012–1077

Printed on recycled paper

I SBN 978- 1- 4113-3409- 0

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