Texas Source-Water Susceptibility Assessment
In many earlier USGS investigations, strong relations
between the occurrence of agricultural chemicals in streams and
their use, or land-use within the up-stream watershed have been
noted. In some investigations (Mueller et al., 1997; Battaglin and
Goolsby, 1997; 1998) statistical models are used to describe these
relations. One type of model, logistic regression, estimates the
probability that a particular chemical will be above or below a
specified concentration. Chemical use patterns, streamflow, land-use
within the up-stream watershed, physical characteristics of the
watershed, climate, soil type, and other factors are the independent
variables in these models, which are conditioned using available
water-quality data. Once developed for a region and if sufficiently
accurate, logistic regression models can be used to model the probability
of chemical occurrence at sites where water-quality data are not
available. The logistic regression models developed by RPE researchers
for Texas are one part of a tool and developed by Randy Ulery and
others at the Texas
office of the USGS to support the Texas Natural Resources Conservation
Commission (TNRCC) Source Water Assessment Program efforts to
assess the susceptibility of all Texas public-water supplies to
contamination.
In the State of Texas, both surface water (streams,
canals, and reservoirs) and ground water are used as sources of
public water supply (PWS). 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 help develop
protective yet cost-effective and risk-mitigated monitoring strategies,
the Texas Commission on Environmental Quality (TCEQ) and the U.S.
Geological Survey (USGS) developed procedures to assess the susceptibility
of PWS source waters 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 are matched with
geographic information system (GIS) derived watershed characteristic
data for the watersheds above the sites. Logistic regression models
are then developed to estimate the probability that a particular
contaminant will exceed a TCEQ-specified threshold concentration.
Logistic regression models are developed for 63 of the 227 contaminants.
Of the remaining contaminants, 106 are not modeled because monitoring
data are available at less than 10 percent of monitoring sites;
29 are not modeled because there are less than 15 percent detections
of the contaminant in the monitoring data; 27 are not modeled because
of the complete lack of monitoring data; and two are not modeled
because threshold values are not specified by TCEQ.
Results of this research are available on in two
publications. “Estimating
the susceptibility of surface water in Texas to Nonpoint-Source
Contamination by Use of Logistic Regression Modeling”, by William
Battaglin, Randy Ulery, Thomas Winterstein, and Toby Welborn was
published as U.S. Geological Survey Water Resources Investigations
Report 03-4205. “Susceptibility
of Surface water in Texas to Nonpoint source Pesticide Contamination",
by William Battaglin, Randy Ulery, Toby Welborn and Thomas Winterstein
was published as a proceeding article for the American Water Resources
Association 2003 Spring Specialty Conference, Agricultural Hydrology
and Water Quality, May 12-14, 2003 in Kansas City, MO. Maps
of monitoring data and modeling results are available for the 63
modeled contaminants and a table
of the logistic regression models are also provided on this web
site.
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