Precipitation undergoes a two-step partitioning when it falls on the land surface. At the land surface and in the shallow subsurface, rainfall or snowmelt can either runoff as infiltration/saturation excess or quick subsurface flow. The rest will be stored temporarily in the root zone. From the root zone, water can leave the catchment as evapotranspiration or percolate further and recharge deep storage. It was recently shown that an index of vegetation water use efficiency, the Horton index (HI), could predict deep storage dynamics. Here we test this finding using 247 MOPEX catchments across the conterminous US. Our results show that the observed HI is indeed a reliable predictor of deep storage dynamics. We also find that the HI can reliably predict the long-term average recharge rate. Our results compare favorably with estimates of average recharge rates from the US Geological Survey. Previous research has shown that HI can be estimated based on aridity index, mean slope and mean elevation of a catchment (Voepel et al., 2011). We recalibrated Voepel’s model and used it to predict the HI for our catchments. We then used these predicted values of the HI to estimate average recharge rates for our catchments, and compared them with those estimated from observed HI. We find that the accuracies of our predictions based on observed and predicted HI are similar. This provides a novel estimation method of catchment-scale long-term average recharge rates based on simple catchment characteristics, such as climate and topography, and free of discharge measurements.