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A GIS‐Based Ground Water Contamination Risk Assessment Tool for Pesticides
Author(s) -
Sinkevich Michael G.,
Walter M. Todd,
Lembo Arthur J.,
Richards Brian K.,
Peranginangin Natalia,
Aburime Sunnie A.,
Steenhuis Tammo S.
Publication year - 2005
Publication title -
groundwater monitoring and remediation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.677
H-Index - 47
eISSN - 1745-6592
pISSN - 1069-3629
DOI - 10.1111/j.1745-6592.2005.00055.x
Subject(s) - environmental science , groundwater , agrochemical , groundwater recharge , contamination , pesticide , water quality , geographic information system , surface water , risk assessment , pollution , water resource management , hydrology (agriculture) , environmental engineering , agriculture , aquifer , computer science , remote sensing , geography , engineering , ecology , agronomy , geotechnical engineering , archaeology , biology , computer security
A process‐based preferential flow transport model was implemented in a geographic information system to locate areas in the landscape with high risk of contamination by agrochemicals, especially pesticides. Protecting ground water resources necessitates a reliable ground water quality monitoring strategy. It is valuable to be able to focus monitoring on areas with the highest risk of contamination because monitoring ground water is an expensive activity, especially at the landscape scale. The objective of this project was to develop a tool that quantifiably estimates distributed ground water contamination risk in order to develop reliable, cost‐effective ground water observation networks. The tool is based on a mechanistic model of chemical movement via preferential flow and uses land cover data, information about chemical properties, and modeled recharge to estimate the concentration of chemical reaching the ground water at each point in the landscape. The distributed risk assessment tool was tested by comparing the model‐predicted risk with observed concentrations from 40 sampling wells in Cortland County, New York, for atrazine (pesticide) and nitrate, the latter assumed to be an indicator of agricultural pollution. The tool predictions agreed well with observed nitrate concentrations and pesticide detections. An Internet‐based version of this tool is currently being developed for ready application to New York State.