Simulating the Extent of TCE Contamination in Antrim County, Michigan Using Publicly Available Data
Tuesday, April 26, 2016
Confluence Ballroom Foyer (The Westin Denver Downtown)
Access to data necessary to construct, calibrate, and test groundwater flow models poses a primary challenge in groundwater and contaminant transport modeling. Spatial data appropriate for model input are, however, becoming increasingly available for download through state and federal agencies. Despite the access to publicly available data, most modeling efforts rely on expensive project-focused site investigations, in part because the data are collected with the purpose of creating model input. We explored the value added for site investigation data in constructing a model for simulating the groundwater flow field for a large trichloroethylene (TCE) plume in Antrim County, Michigan. Located in a heterogeneous glacial aquifer system, the plume extends approximately six miles northwest from the industrial source area and is estimated to affect four primary water-bearing zones that supply drinking water to the Village of Mancelona and surrounding area, including individual wells for rural residents. Spatial data downloaded from the Michigan Geographic Data Library, and other online sources, were used as a means to characterize the hydrogeology of the subsurface, formulate inputs for the regional conceptual model and subsequently develop numerical (MODFLOW-2005) groundwater flow models of varying complexities. This modeling approach was successful in simulating the groundwater flow using a the three-layer system by calibrating recharge and hydraulic conductivities that agreed with independent estimates of recharge and aquifer properties. In order to analyze the value added from site characterization data, the model based on publically available data was reformulated using the plume-project site investigation data, which included monitoring well soil-boring logs, monitoring activity records, geophysical seismic surveys, and source site evaluations. The final analysis provides insight to the models’ ability to simulate field data, forecast behaviors of production wells, and serves as the basis for recommendations for plume capture.