A Multiscale Assessment of Shallow Groundwater Salinization in Michigan
by Zachary K. Curtis, Hua-Sheng Liao, Shu-Guang Li, Prasanna Venkatesh Sampath, and David P. Lusch
February 2019, Journal of Groundwater, National Groundwater Association
Abstract
Managing nonpoint-source (NPS) pollution of groundwater systems is a significant challenge because of the heterogeneous nature of the subsurface, high costs of data collection, and the multitude of scales involved. In this study, we assessed a particularly complex NPS groundwater pollution problem in Michigan, namely, the salinization of shallow aquifer systems due to natural upwelling of deep brines. We applied a system-based approach to characterize, across multiple scales, the integrated groundwater quantity–quality dynamics associated with the brine upwelling process, assimilating a variety of modeling tools and data—including statewide water well datasets scarcely used for larger scientific analysis. Specifically, we combined (1) data-driven modeling of massive amounts of groundwater/geologic information across multiple spatial scales with (2) detailed analysis of groundwater salinity dynamics and process-based flow modeling at local scales. Statewide “hotspots” were delineated and county-level severity rankings were developed based on dissolved chloride (Cl−) concentration percentiles. Within local hotspots, the relative impact of upwelling was determined to be controlled by: (1) streams—which act as “natural pumps” that bring deeper (more mineralized) groundwater to the surface; (2) the occurrence of nearly impervious geologic material at the surface—which restricts fresh water dilution of deeper, saline groundwater; and (3) the space–time evolution of water well withdrawals—which induces slow migration of saline groundwater from its natural course. This multiscale, data-intensive approach significantly improved our understanding of the brine upwelling processes in Michigan, and has applicability elsewhere given the growing availability of statewide water well databases.