ASSESSING RECHARGE IN ALLUVIAL AQUIFER SYSTEMS: AN INNOVATIVE APPROACH

Quantifying alluvial aquifer recharge comes as a challenge due to hydrologic boundaries as well as spatial variations in precipitation and aquifer characteristics. Spatially inconsistent amounts of rainfall and infiltration combined with variable vegetation, land cover, and sediments result in over or underestimated recharge rates using regionally uniform model parameters. Spatially-based techniques for aquifer assessment are applicable in complex systems to gain better insight into shallow aquifer dynamics. This research describes different novel techniques for assessment applied to a shallow alluvial aquifer in central Texas. The Brazos River Alluvium Aquifer is a shallow, directly-recharged system that occurs adjacent to the Brazos River within its alluvial valley. The Brazos Alluvium is comprised of heterogeneous fluvial sediments that typically fine upward but are both vertically and laterally discontinuous. Spatial characterization of sediment coupled with the delineation of hydrologic boundaries show isolated compartments where discreet flow systems may be present. Many model studies utilize uniform, average annual precipitation as input. While this type of approach lends itself to classical methods of recharge quantification over a continuous uniform aquifer, compartmentalized aquifers require more detailed spatially-distributed precipitation estimates. Therefore, we propose using spatial rainfall distributions over discreet compartments to better determine actual recharge. The use of radar-derived rainfall estimates from the National Weather Service’s WSR-88D radar (Weather Surveillance Radar - 1988 Doppler), including those from the new dual-polarization rainfall algorithm, provide new opportunities to better understand spatial rainfall-recharge relationships. Compared with data using only rain gauges, radar-derived rainfall estimates provide more spatially-distributed data that can be coupled with hydrogeological boundaries and sediment heterogeneity to improve recharge estimates for many shallow groundwater systems.