Sentinel-1 Backscatter Assimilation Using Support Vector Regression or the Water Cloud Model at European Soil Moisture Sites

Sentinel-1 backscatter observations were assimilated into the Global Land Evaporation Amsterdam Model (GLEAM) using an ensemble Kalman filter. As a forward operator, which is required to simulate from soil moisture and leaf area index (LAI), we evaluated both traditional water cloud model (WCM) support vector regression (SVR). With SVR, closer fit between simulations was achieved. The impact on correlation modeled in situ measurements similar when assimilating Sentinel data WCM ( $\Delta R = +0.037$ ) or SVR +0.025$ ).