EVALUATION OF ARTIFICIAL RECHARGE AND GROUNDWATER FLOW IN A SMALL NEW ENGLAND AQUIFER
The model uses a suite of open-source resources including python packages, Modflow-setup, and flopy, that discretize grid-independent source data files, execute MODFLOW6 groundwater flow and transport simulations, and provide post-processing options of results. A python package is developed to process existing datasets, generate model source data files, execute the automated parameter estimation, and analyze model output.
Model calibration with PEST quantifies parameter correlations and uncertainties using existing datasets collected during preliminary hydrogeological investigations, studies conducted to permit the production well and artificial recharge system, and annual aquifer monitoring from 2012-2023. Data from ongoing on-site monitoring of surface and groundwater stations, including water levels, streamflow measurements, and water quality samples analyzed for stable isotopes and trace metals, are also used to help calibrate the model, characterize the fate and transport of artificial recharge water in the aquifer, and estimate groundwater discharge into the adjacent Chesley Brook.
Results demonstrate the influence of aquifer properties, artificial recharge system usage, and environmental conditions on storage efficiency and sustainable yield and provide a case study for applying artificial recharge in other settings.