STATEWIDE ESTIMATES OF GROUND-WATER RECHARGE IN MINNESOTA

Regional-scale ground-water recharge in Minnesota was estimated using regression analysis. The regional regression recharge (RRR) analysis related precipitation and landscape characteristics to basin-scale recharge. Specific yield, estimated from data in the State Soil Geographic (STATSGO) Data Base, was modeled as the primary characteristic that affects recharge from precipitation. Specific yield was computed using the Rosetta software, which estimates soil hydraulic properties using a neural network. Presence of lakes in the basin and slope also were important landscape characteristics that affected recharge. Thirty nine basins were used in the final RRR analysis and are fairly well distributed throughout the state, except for high-slope areas in the northeastern and southeastern parts of Minnesota. Because few basins that met our selection criteria were in high slope areas, the RRR estimates for high-slope areas are not accurate. Recharge as computed by the RRR analysis was near 0 cm per year in areas of low specific yield (less than 0.15) and less than 52 cm per year precipitation. The lowest recharge generally occurred in the northwestern part of the sate. The greatest RRR estimate was about 32 cm per year in areas of high specific yield (greater than 0.16) and greater than 77 cm per year precipitation. As expected areas of greatest recharge occur in sandplain and outwash areas, but is sensitive the amount of annual precipitation. The RRR rates agree well with other methods for estimating recharge, suggesting that this method could be a useful tool for regionalizing recharge estimates from long-term streamflow, specific yield, and precipitation data in other subhumid and humid areas of the world.