Vulnerability of groundwater to nitrate pollution in Walworth County, Wisconsin

Authors: Rocio R Duchesne*, University of Wisconsin - Whitewater
Topics: Environmental Science, Geographic Information Science and Systems, Water Resources and Hydrology
Keywords: groundwater, nitrate pollution, Wisconsin, GIS
Session Type: Guided Poster
Day: 4/6/2019
Start / End Time: 1:10 PM / 2:50 PM
Room: Roosevelt 3.5, Marriott, Exhibition Level
Presentation File: No File Uploaded

70% of Wisconsin residents rely on groundwater for their drinking water. These aquifers are most commonly polluted by nitrate from manure spreading, agriculture fertilizers, and septic systems. High levels of nitrate in drinking water can cause many health issues including methemoglobinemia and neural tube defects. We used the Multi-Criteria Decision Analysis model to assess the vulnerability of groundwater to nitrate contamination in Walworth County, WI, during the period 2010 - 2017. Based on literature review and the available spatial data, we selected soil texture, net recharge, depth to the water table, hydraulic conductivity, land-use, slope, and recommended nitrate application to crops, as modeling parameters. We normalized each parameter on a scale of 1 to 5, and used a pairwise comparison scale to assess the relative importance of each parameter in relation to the others. The normalized parameters and the pairwise comparison matrix were combined using the AHP extension in ArcMap to produce the vulnerability map. A robust database with nitrate records for 1,087 private wells was used to validate the quality of the vulnerability map. Wells with nitrate concentrations above the EPA's recommended maximum nitrate concentration level (10 mg/L) were considered impacted. Results show that most of Walworth County is at medium risk of nitrate pollution. The most vulnerable areas are the towns of Delavan, Spring Prairie, and south of Lake Geneva. These towns have multiple golf courses and large farm operations, which may contribute to higher nitrate inputs. We recommend including additional parameters in the model to improve performance.

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