Water Resources Research Act Program

Details for Project ID WY_2025_68_Zhang

Elucidating mountain front aquifer recharge using machine learning, hydrogeochemistry, and groundwater modeling

Institute: Wyoming
Year Established: 2025 Start Date: 2026-01-01 End Date: 2026-12-31
Total Federal Funds: $18,000 Total Non-Federal Funds: $33,498

Principal Investigators: Ye Zhang

Project Summary: This study integrates machine learning, hydrochemistry, geophysical imaging, and groundwater modeling to understand, replicate, and predict mountain front recharge to a karst aquifer in southeastern Wyoming. First, historical (2016-2025) hydrometeorological measurements and monitored aquifer and stream water levels and hydrochemistry will be jointly interpreted to identify aquifer recharge mechanism including timing, pathways, and rate. During the peak flow of 2026, campaign-level electrical resistivity tomography will be conducted to verify the recharge, specifically resolving stream sinks as dynamic pathways for surface water to enter the aquifer. Given the complementary field data, a three-dimensional groundwater model will be built, calibrated, and verified using historical pumping test data as well as the monitored aquifer and stream water levels. With this model, aquifer dynamics (i.e., water level, flow rate, residence time, recharge) will be predicted for a range of future precipitation and water use scenarios relevant for the site's groundwater management planning.