A PYTHON TOOL TO ESTIMATE LAND-USE IMPACTS ON GROUNDWATER NITRATE CONCENTRATIONS OBSERVED AT HIGH-CAPACITY PUMPING WELLS IN AN UNCONFINED GLACIAL AQUIFER

Shallow glacial aquifers systems are the primary source of drinking water for millions of residents in the upper Midwest and Great Lakes regions of the United States. Studies show that a significant number of municipal and private groundwater wells in these regions are impacted by high nitrate concentrations, which can have negative health impacts for humans. Reducing nitrate contamination through good land management practices will reduce the need for costly nitrate treatment systems and help mitigate other ecological concerns related to nutrient pollution of groundwater. This study presents a Python-based modelling tool that uses a local groundwater flow model and historical land use data (USDA CropScape) to estimate nitrate concentrations at a high-capacity pumping well. Nitrate concentrations predicted by this model are within 5% of median annual values observed at a study site in Waupaca, WI. The model is user-friendly and can easily be adapted to other locations, where it has the potential to help local and state agencies, landowners, and growers make cost-effective decisions about land-use and agricultural practices.