资源环境科技发展态势分析平台

Microwave brightness temperature observations from the NASA Soil Moisture Active‐Passive (SMAP) mission and gauge‐based precipitation data over the US are used to reconstruct the soil water loss function and then historical (1979‐2019) hydrological fluxes in the form of evapotranspiration (ET) and drainage (D) are quantified. Over the period of study, with the exception of snowy and hyper‐arid regions, we observe a correlation of R² > 0.6 between SMAP‐precipitation derived drainage estimates and streamflow measurements from the USGS. There is a bias between estimated drainage and USGS streamflow with an underestimation of about 1 [mm day^‐1] in southwest US to 3 [mm day^‐1] in parts of the eastern US. SMAP‐derived sensitivities of drainage and ET partitioning with respect to precipitation anomalies are also calculated. In parts of the Great Plains the drainage partitioning exhibits a near‐linear response, while in the southeast US, the response is nonlinear. Partitioning also is examined for 6 four‐digit hydrologic unit basins wherein year‐to‐year variations in drainage partitioning are shown to be key mediators in translating precipitation anomalies into streamflow anomalies. Observation‐driven drainage and ET estimates are obtained without relying on full hydrologic and Land Surface Models (LSMs). This independence (isolation from model parameterization assumptions) provides a path towards using satellite‐derived landscape hydrological diagnostics to assess hydrologic models and LSMs as well as to guide their further development.