Using GIS and logistic regression to estimate agricultural chemical concentrations in rivers of the midwestern USA

W.A. Battaglin

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Using GIS and logistic regression to estimate agricultural chemical concentrations in rivers of the midwestern USA

W.A. Battaglin

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Abstract

Agricultural chemicals (herbicides, insecticides, other pesticides and fertilizers) in surface water may constitute a human health risk. Recent research on unregulated rivers in the midwestern USA documents that elevated concentrations of herbicides occur for 1-4 months following application in spring and early summer. In contrast, nitrate concentrations in unregulated rivers are elevated during the fall, winter and spring. Natural and anthropogenic variables of river drainage basins, such as soil permeability, the amount of agricultural chemicals applied or percentage of land planted in corn, affect agricultural chemical concentrations in rivers. Logistic regression (LGR) models are used to investigate relations between various drainage basin variables and the concentration of selected agricultural chemicals in rivers. The method is successful in contributing to the understanding of agricultural chemical concentration in rivers. Overall accuracies of the best LGR models, defined as the number of correct classifications divided by the number of attempted classifications, averaged about 66%.

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W.A. Battaglin. 1996. Using GIS and logistic regression to estimate agricultural chemical concentrations in rivers of the midwestern USA. https://pubs.usgs.gov/publication/70018053

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