Estimating the Susceptibility of
Surface Water in
Texas to Nonpoint-Source Contamination
by Use of Logistic Regression Modeling
By William A. Battaglin, Randy L. Ulery, Thomas Winterstein, and Toby
Welborn
Available from the U.S. Geological Survey, Branch of Information Services,
Box 25286, Denver Federal Center, Denver, CO 80225, USGS Water-Resources
Investigations Report 03-4205, 24 p., 2 figs.
This document also is available in pdf format:
WRIR 03-4205.pdf (1.7 MB)
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Acrobat Reader)
The citation for this report, in USGS format, is as follows:
Battaglin, W.A., Ulery, R.L., Winterstein, T., and Welborn, T., 2003,
Estimating the Susceptibility of Surface Water in Texas to Nonpoint-Source
Contamination by Use of Logistic Regression Modeling: U.S. Geological
Survey Water-Resources Investigations Report 03-4205, 24 p.
Abstract
In the State of Texas, surface water (streams, canals, and
reservoirs) and ground water are used as sources of public water
supply. Surface-water sources of public water supply are susceptible
to contamination from point and nonpoint sources. To
help protect sources of drinking water and to aid water managers
in designing protective yet cost-effective and risk-mitigated
monitoring strategies, the Texas Commission on Environmental
Quality and the U.S. Geological Survey developed procedures
to assess the susceptibility of public water-supply source waters
in Texas to the occurrence of 227 contaminants. One component
of the assessments is the determination of susceptibility of
surface-water sources to nonpoint-source contamination. To
accomplish this, water-quality data at 323 monitoring sites were
matched with geographic information system-derived watershed-
characteristic data for the watersheds upstream from the
sites. Logistic regression models then were developed to estimate
the probability that a particular contaminant will exceed a
threshold concentration specified by the Texas Commission on
Environmental Quality. Logistic regression models were developed
for 63 of the 227 contaminants. Of the remaining contaminants,
106 were not modeled because monitoring data were
available at less than 10 percent of the monitoring sites; 29 were
not modeled because there were less than 15 percent detections
of the contaminant in the monitoring data; 27 were not modeled
because of the lack of any monitoring data; and 2 were not modeled
because threshold values were not specified.
Contents
Abstract
Introduction
Texas Source Water Assessment Project
Purpose and Scope
Surface-Water Nonpoint-Source Component
Surface-Water Sites
Water-Quality Data
Watershed-Characteristics Data
Logistic Regression Models
Estimating the Susceptibility of Surface Water to Nonpoint-Source Contamination
Summary of Modeled Contaminants
Examples of Modeling Results
Summary
References
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