Estimation of Spatio-Temporally Variable Groundwater Recharge Using a Rainfall-Runoff Model

Abstract

This paper describes the radar-based estimation of groundwater recharge by means of distributed hydrologic modeling used to estimate components of the hydrologic water balance. Conventional management of water resources has focused on groundwater as a separate constituent of surface water in hydrologic systems, but factors such as precipitation, surface runoff, base flow, evapotranspiration, and water demands determine the change in storage in a stream-aquifer system that varies in both time and space. The temporal and spatial variability of groundwater recharge have been estimated in the eastern outcrop of the Arbuckle-Simpson aquifer, located in Oklahoma. Distributed maps of precipitation from radar were corrected for bias using rain gauges and used as input to a distributed hydrologic model. Distributed grids of infiltration were combined with evapotranspiration to extend groundwater recharge estimates from three years, when streamflow records existed, to 13 years, using archival radar. The results show that better characterization of precipitation and runoff, achieved with bias-corrected radar, produces more reliable estimates of runoff and groundwater recharge than those derived from the use of rain gauge data alone.