Estimating Basin-Scale Water Budgets With SMAP Soil Moisture Data

Abstract

Soil Moisture Active Passive (SMAP) Level-2 soil moisture retrievals collected during 2015–2017 are used in isolation to estimate 10-day warm season precipitation and streamflow totals within 145 medium-sized (2,000–10,000 km2) unregulated watersheds in the conterminous United States. The precipitation estimation algorithm, derived from a well-documented approach, includes a locally calibrated loss function component that significantly improves its performance. For the basin-scale water budget analysis, the precipitation and streamflow algorithms are calibrated with 2 years of SMAP retrievals in conjunction with observed precipitation and streamflow data and are then applied to SMAP retrievals alone during a third year. While estimation accuracy (as measured by the square of the correlation coefficient, r2, between estimates and observations) varies by basin, the average r2 for the basins is 0.53 for precipitation and 0.22 for streamflow. For the subset of 22 basins that calibrate particularly well, the r2 increases to 0.63 for precipitation and to 0.51 for streamflow. The magnitudes of the estimated variables are also accurate, with sample pairs generally clustered about the 1:1 line. The chief limitation to the estimation involves large biases induced during periods of high rainfall; the accuracy of the estimates (in terms of r2 and root-mean-square error) increases significantly when periods of higher rainfall are not considered. The potential for transferability is also demonstrated by calibrating the streamflow estimation equation in one basin and then applying the equation in another. Overall, the study demonstrates that SMAP retrievals contain, all by themselves, information that can be used to estimate large-scale water budgets.