Improved Groundwater Arsenic Contamination Modeling Using 3-D Stratigraphic Mapping, Eastern Wisconsin, USA

Dissolved arsenic in private bedrock drinking water wells is a problem in eastern Wisconsin. Previous studies have identified bedrock sources of arsenic as discrete intervals within the local Paleozoic sedimentary section and have also identified release mechanisms causing arsenic to enter well boreholes. However, widespread contamination modeling is hindered by a lack of 3-D knowledge constraining the depth of the arsenic-bearing units in the subsurface. The growth and improvement of 3-D geologic mapping provides an opportunity to improve predictive models. This study in eastern Wisconsin, USA, uses a multivariate binary logistic regression analysis combined with 3-D geologic mapping to both assess various geologic and well construction factors that impact arsenic occurrence, and improve the ability to predict contamination risk. We find well construction characteristics, the stratigraphic unit within the open interval of a well, and the proximity to fold axes/fault zones are all statistically significant variables that impact the probability of a well exceeding either 2 or 10 µg/L dissolved arsenic. We apply these results by using 3-D mapping to determine the geologic unit present within the open interval of thousands of untested wells and use the logistic regression results to calculate contamination probability. This allows arsenic risk to be rapidly estimated for thousands of individual groundwater wells, and models of potential casing regulations to be assessed.