To meet future water demands, the Cheyenne Board of Public Utilities (BOPU) plans to develop the Casper Aquifer at the Belvoir Ranch, Cheyenne, as a groundwater resource. Despite several preliminary studies that evaluated and characterized the Casper Aquifer at this site, complex site hydrogeology precludes the development of a well-informed drilling plan, i.e., where future municipal water supply wells should be placed and the appropriate seasonal pumping rate, duration, and well rotation. To ensure sustainable well yields, water supply wells need to tap into aquifer regions with high hydraulic conductivity (K) that can also capture the natural recharge into the subsurface. However, uncertainty exists in the current understanding of groundwater flow in this aquifer due to several reasons: (1) aquifer K distribution is highly uncertain; (2) location, timing, and rate of aquifer recharge remain uncertain; (3) aquifer boundary conditions are uncertain, i.e., at the Belvoir Ranch, the aquifer is intersected by several faults that range from impervious to conductive. To effectively manage this aquifer and to provide guidance for its sustainable development, these uncertainties must be reduced. This study proposes to use groundwater modeling to understand and quantify groundwater flow in this aquifer for both the pre-development phase and the drilling phase. The modeling study will integrate existing static geological and geophysical characterization data with hydrodynamic data, such as monitored water levels, well test results, and prior recharge estimates. To reduce the uncertainty in estimating aquifer K, recharge rate, and boundary conditions, a hybrid model calibration technique will be developed and tested that will combine a novel steady-state aquifer inverse method capable of simultaneous parameter and boundary condition estimation, with an objective-function-based traditional inversion technique that can utilize transient data. Because of the limited static and hydrodynamic data at this site and the ambiguity associated with data interpretation, the proposed study will aim to account for subsurface uncertainty, while reducing its impact on the modeling outcomes. Thus, we will (1) create alternative aquifer hydrostratigraphic model realizations that are all consistent with the available static data; (2) calibrate these static models with the hybrid inversion technique; (3) verify and rank the calibrated models with a post-audit analysis; and (4) with the highest ranked model(s), conduct a well capture zone analysis to analyze different hypothetical pumping programs, i.e., varying pumping well location, perforation, duration, and timing. Therefore, modeling will be used to help guide drilling in order to capture natural recharge into the aquifer, thus providing sufficient flow rates over a long period of time without unacceptable level of drawdowns. The results will thus identify an optimal drilling program (with uncertainty) for achieving sustainable well yields at Belvoir Ranch, while the study methodology, if proven successful, can be extended to evaluating other hydrogeological environments in the State.