Improving hydrologic forecasting using spaceborne soil moisture retrievals

Using existing data sets of passive microwave spaceborne soil moisture retrievals, streamflow and precipitation for 26 basins in the United States Southern Great Plains, a 5-year analysis is performed to quantify the value of soil moisture retrievals derived from the Tropical Rainfall Mission (TRMM) Microwave Imager (TMI) X-band (10.7 GHz) radiometer for forecasting storm event-scale runoff ratios. The predictive ability of spaceborne soil moisture estimates is objectively compared to that obtainable using only available rainfall observations and the antecedent precipitation index (API). The Kalman filter-based assimilation of spaceborne observations into an API soil moisture proxy is demonstrated to add skill to the forecasting of land surface response to precipitation. Improvemnts are especially pronounced when API moisture proxies are derived using satellite-based precipitation data results. Results demonstrate the potential of spaceborne soil moisture retrievals for improving the accuracy of short-term hydrologic model forecasts.