Groundwater response to climate variability and land cover change is important for sustainable management of water resources in the Southwest US. Global Climate Models (GCM) project that the region will dry in the 21st century and the transition to a more arid climate may be under way. In semiarid Basin and Range systems, this impact is likely to be most pronounced in Mountain System Recharge (MSR), a process which constitutes a significant component of recharge in these basins. Despite the importance of MSR the physical processes that control MSR, and hence the climate change impacts, have not been fully investigated because of the complexity of recharge processes in mountainous catchments and limited observations. In this study, methodologies were developed to provide process-based understanding of MSR based on empirical and data-driven approaches. For the empirical approach, a hydrologically-based seasonal ratio the Normalized Seasonal Wetness Index (NSWI) was developed. It incorporates seasonal precipitation variability and temperature regimes to seasonal MSR estimation using existing empirical equations. Stable isotopic data was used to verify recharge partitioning. Using the NSWI and statistically downscaled monthly GCM precipitation and temperature data, climate change impacts on seasonal MSR are evaluated. Second, a novel data-based approach was developed to quantify mountain block recharge based on the catchment storage-discharge (S-Q) relationships and informed by isotopic data. Development of S-Q relationships across the Sabino Creek catchment, Arizona, allowed understanding of MBR dynamics across scale.Two ArcGIS desktop applications were developed for ArcGIS 9.2 to enhance recharge and evapotranspiration (ET) estimation: Arc-Recharge and RIPGIS-NET. Arc-Recharge was developed to quantify and distribute recharge along MODFLOW cells using spatially explicit precipitation data and a digital elevation model. RIPGIS-NET was developed to provide parameters for the RIP-ET package and to visualize MODFLOW results. RIP-ET is an improved MODFLOW ET module for simulating ET. RIPGIS-NET improves alluvial recharge estimation by providing spatially explicit riparian ET estimates. Using such tools and the above methods improves recharge and ET estimation in groundwater models by incorporating temporally and spatially explicit data and hence the assessment of climate variability and land cover change on groundwater resources can be improved.