45 ADVANCED HYDROGEOLOGICAL MODELING AND SENSITIVITY ANALYSIS TO OPTIMIZE DEWATERING AND CHARACTERIZE WATER FLOW AT THE MINGOMBA CU DEPOSIT *G. Quispe Oruro1, J. Ding1, J. Caers1 1Department of Earth and Planetary Sciences, Stanford University, USA (*Presenting author: gloriaqo@stanford.edu) ABSTRACT Development of deep underground copper deposits requires robust groundwater management strategies capable of addressing large uncertainty in subsurface hydraulic properties and recharge conditions. At the Mingomba copper deposit in Zambia, significant groundwater inflows are anticipated during shaft construction and early mine development due to regional recharge, stratigraphic heterogeneity, and fracture-influenced flow, creating substantial uncertainty in pumping requirements, mine scheduling, geotechnical stability, and long-term environmental management. This study presents a probabilistic hydrogeological modeling framework to evaluate pore pressure evolution and groundwater inflow under uncertainty during planned mine development. A three-dimensional groundwater flow model was constructed using stratigraphic and regional hydrogeologic constraints, with uncertain parameters represented probabilistically, including matrix permeability, vertical hydraulic conductivity, directional permeability anisotropy, fracture permeability multipliers, and external aquifer inflow conditions. Monte Carlo sampling was used to generate a thousand realizations of a five-year dewatering scenario surrounding planned shaft infrastructure, and model outputs were evaluated using distance-based global sensitivity analysis to determine which uncertain hydrogeologic parameters exert the strongest control on pressure response. Identifying these dominant controls is critical because pressure evolution governs where dewatering wells should be placed, how aggressively pumping must be applied, and how rapidly pore pressures can be reduced to support safe mine development. Sensitivity analysis further provides a pathway to reduce uncertainty by identifying which parameters warrant targeted field characterization while deprioritizing low-impact variables that add complexity without materially improving predictive confidence. Preliminary results indicate that directional hydraulic conductivity, vertical permeability connectivity, and regional boundary inflow conditions are first-order controls on pressure dissipation and drawdown extent. These findings establish a falsificationbased uncertainty-quantification workflow in which simulated pressure ensembles can be compared against regional hydraulic observations and future operational monitoring data to assess whether anisotropic continuum representations are sufficient or whether more complex
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