Prediction of Future Groundwater Contamination Risk in Rural Agricultural Regions

Strategies for understanding regional groundwater contamination risk are often challenged by changing land use and climate conditions. Furthermore, index-based assessment methods are typically implemented in a static manner which inherently precludes possible changes in future contamination risk resulting from these dynamic conditions. It is perhaps equally important to consider the manner in which climate forcing and land use are represented. With regards to land use in particular, rural regions may have unique concerns; agricultural land use is commonly represented as a single land use class despite the complex land management practices that may be present and the subsequent implications for groundwater quality. This investigation demonstrates alteration of the conventional DRASTIC-LU methodology to assess mid-century changes in groundwater contamination risk through the treatment of recharge, depth to water table, and land use as dynamic factors. The potential influence of agricultural land use representation on DRASTIC-LU model performance and prediction is concurrently examined. The Upper Parkhill watershed in southwestern Ontario, Canada is explored as a case study for method application. Study results indicate that the inclusion of crop rotation and tile drainage data has the potential to improve model functioning. Moreover, predicted future changes in groundwater contamination risk may differ depending on the manner in which agricultural land use is represented. This investigation helps to resolve the influence of land use on groundwater contamination risk and provides a screening tool that may be used to support groundwater decision making.