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GIS-based spatial regression and prediction of water quality in river networks: A case study in Iowa
Nonpoint source pollution is the leading cause of the U.S.’s water quality problems. One important component of nonpoint source pollution control is an understanding of what and how watershed-scale conditions influence ambient water quality. This paper investigated the use of spatial regression to evaluate the impacts of watershed characteristics on stream NO3NO2-N concentration in the Cedar River Watershed, Iowa. An Arc Hydro geodatabase was constructed to organize various datasets on the watershed. Spatial regression models were developed to evaluate the impacts of watershed characteristics on stream NO3NO2-N concentration and predict NO3NO2-N concentration at unmonitored locations. Unlike the traditional ordinary...
Categories: Publication;
Types: Citation;
Tags: Data Visualization & Tools,
GIS,
Kriging,
Landscapes,
Nitrogen,
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