Abstract
Nitrate ingested from drinking water has been linked to adverse health outcomes (e.g., cancer, birth defects) at levels as low as ∼2 mg/L NO(3)-N, far below the regulatory limits of 10 mg/L. In many areas, groundwater is a common drinking water source and may contain elevated nitrate, but limited data on the patterns and concentrations are available. Using an extensive regulatory data set of over 100,000 nitrate drinking water well samples, we developed new maps of groundwater nitrate concentrations from 76,724 wells in Michigan's Lower Peninsula, USA for the 2006-2015 period. Kriging, a geostatistical method, was used to interpolate concentrations and quantify probability of exceeding relevant thresholds (>0.4 [common detection limit], >2 mg/L NO(3)-N). We summarized this probability in small watersheds (∼80 km(2)) to identify correlated variables using the machine learning method classification and regression trees (CARTs). We found 79% of wells had concentrations below the detection limit in this analysis (<0.4 mg/L NO(3)-N). In the shallow aquifer (focus of study), 13% of wells exceeded 2 mg/L NO(3)-N and 2% exceeded the EPA maximum contaminant level of 10 mg/L. CART explained 40%-45% of variation in each model and identified three categories of critical correlated variables: source (high agricultural nitrogen inputs), vulnerable soil conditions (low soil organic carbon and high hydraulic conductivity), and transport mechanisms (high aquifer recharge). These findings add to the body of literature seeking to identify communities at risk of elevated nitrate and study associated adverse health outcomes.