The use of cross-correlation analysis on spring discharge and precipitation data in karst aquifer basins has been used for many years to develop a conceptual understanding of an aquifer and estimate aquifer properties. However, to this point, the application of these processes has relied on gaged precipitation at discrete locations. The use of spatially varying precipitation data and cross-correlation analysis provides a means of spatially characterizing recharge locations on a karst aquifer. NEXRAD provides a spatial estimate of precipitation based by combining reflectivity measurements from radar stations and traditional precipitation gages. This study combines NEXRAD precipitation data with spring discharge data to develop maps of contributing areas for two karst springs in Central Texas. By calculating the cross-correlation of each NEXRAD measurement to spring flow data for the same period of time a map showing the locations hydraulically connected to the spring can be developed. Both numerical experiments and field applications were conducted as part of the study. The numerical experiments conducted by Padilla and Pulido-Bosch are revisited using the numerical groundwater model MODFLOW. This allowed the introduction of spatially varying parameters into the model. The results show that spatially varying parameters can be inferred based on the results cross-correlation of spatially varying precipitation with respect to a single spring discharge location. Also, contributing area maps are prepared for both Barton Springs and Jacob’s Well. Barton Springs has a precise estimate of the recharge area. The current map of the recharge area and the NEXRAD derived map show good agreement with the cross-correlation results. Conversely, Jacob’s Well has not been sufficiently studied to delineate a contributing area map. This study provides an preliminary estimate of the area contributing to flow at Jacob’s Well. Finally, the development of these maps can also be applied to the construction of regional groundwater models. An application of this methodology with the groundwater availability model for the Barton Springs portion of the Edward’s aquifer is introduced. The application of spatial cross-correlation analysis to constrain recharge in the model showed a reduction in the objective function with respect to discharge at Barton Springs of 15%. / text