Research Insights
Risk-Informed, Performance-Based Evaluation of Local and Regional Surface and Groundwater Hydrology using Alternative Conceptual Models
We propose to continue development of a groundwater-hydrologic model for southeast Georgia and surrounding region (Okefenokee Swamp and associated rivers). We will explore the role of groundwater flows across southeast Georgia for future climate and coastal development scenarios including the effective dispersion of scalars within the groundwater system. We will maintain a specific focus on net flow from groundwater into/out of the Okefenokee Swamp, Trail Ridge, and the St. Marys River and how this net flow is expected to change under future conditions. The model will allow us to quantify the fate of groundwater and solutes in the system. With the models we will be able to estimate impacts of mining on water levels and dispersion of solutes (tailings) in both groundwater and surface waters with particular focus on solutes potentially entering the Floridian aquifer, the Okefenokee Swamp, and the St. Marys River; how Floridan Aquifer withdrawals may influence the Okefenokee Swamp; and how mine operations and reclamation may affect the characteristics of the Surficial Aquifer and how such changes may influence the hydrologic characteristics of Trail Ridge and the Okefenokee Swamp.. Our initial
focus will be on the surficial and Floridian aquifer and their interaction with the Okefenokee Swamp and associated rivers. We will use the numerical model outputs to develop conceptual models of the water cycle in the region and estimates of solute dispersion and changes in surface water levels.
We will use the regional scale model as boundary conditions for two high resolution mine-specific models (Mission and Amelia mines). We will use these models to estimate impacts of mining on groundwater flows, water table elevations, and the dispersal of solutes under future climate scenarios.
If available, we will review the hydrologic model(s) prepared by Twin Pines’ consultants in order to understand key assumptions, model construction, and data sets and to possibly guide enhancements of our model.
Funder: Chemours Company
Amount: $552,950
PI: C. Brock Woodson, College of Engineering