An Arc/Info Geographic Information System (GIS) method has been
developed for the assessment of nonpoint source pollution in a
watershed. This method makes use of publicly available elevation,
stream network, rainfall, discharge, and land use data sets and
uses a digital discretization, or grid representation, of a watershed
for the approximation of average annual pollutant loads and concentrations.
The San Antonio-Nueces Coastal Basin in south Texas is identified
as the test site for execution of the method.
A digital grid replica of the basin stream network is first created,
employing a "burn-in " process to affix the USGS Digital
Line Graph stream network to the Digital Elevation Model of the
basin. Precipitation is then compared with historical discharge
at five gauge locations in the basin and a mathematical relationship
between rainfall and runoff is established, using a regression
analysis. Literature-based Expected Mean Concentrations (EMC's)
of pollutant constituents are associated with land uses in the
watershed. The products of these spatially distributed EMC's and
the runoff in each digital basin grid cell are calculated and
then summed in the downstream direction to establish spatially
distributed grids of average annual pollutant loads in the basin.
Finally, grids of nonpoint source pollutant concentrations are
created by dividing the average annual pollutant load grids by
a grid of total annual cumulative runoff.
In an effort to refine the process, a method of simulating suspected
nutrient point sources in the basin is investigated and an optimization
routine is used with pollutant measurement data at four major
sampling points to adjust the literature-based Expected Mean Concentration
values for phosphorus.
The GIS nonpoint source pollution assessment method is performed
for four pollutant constituents: phosphorus, nitrogen, cadmium,
and Fecal Coliform. Predicted concentrations for phosphorus and
nitrogen, when determined with the simulated point sources, match
closely with average observed concentrations in the basin. Predicted
Fecal Coliform concentrations did not match well with average
observed values, but Expected Mean Concentration values for the
pollutant were highly variable between land uses and should be
investigated further. Insufficient heavy metal measurement data
exist to make conclusive assessments of predicted cadmium concentrations.
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