Assimilation of backscatter observations in a hydrological model: a case study in Belgium using ASCAT data

We investigate the possibilities to improve hydrological simulations by assimilating active radar backscatter observations from the Advanced Scatterometer (ASCAT) in the hydrological model SCHEME. This effort is motivated by the great need of accurate initial model states in hydrological forecasting and the potential to improve them by using remotely sensed data of land surface processes. ASCAT data assimilation is enabled by coupling the Water Cloud Model (WCM) with the SCHEME model. We calibrated the WCM over two catchments in Belgium exhibiting different hydrological regimes. We explore a data assimilation system based on the Ensemble Kalman Filter (EnKF) whereby the observation operator is given by the coupling of WCM and SCHEME models. This coupling underlines the advantage of using backscatter data for assimilation purposes instead of a soil moisture product carrying its own climatology. In the present study we focus on optimising the EnKF for the task, unveil the main challenges and investigate possible solutions including methods to address the biases affecting the data assimilation procedure.