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 two 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 RMSE) 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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.