Satellite inspired hydrology in an uncertain future: a H SAF and HEPEX workshop

A project is being proposed which will investigate multiple issues that arise when assimilating remotely sensed soil moisture data into a distributed hydrological model for flood forecasting. The first issue is estimating subsurface soil moisture from satellite surface measurements. Although root zone soil moisture is more important for streamflow modeling, satellites can estimate soil moisture only for a thin uppermost soil layer. The second issue is the spatial interpolation/extrapolation of satellite soil moisture data over an entire watershed, in order to mitigate the spatial discontinuity problem inherent in satellite soil moisture datasets. The third issue is to investigate whether joint assimilation of soil moisture datasets from multiple sources in an operational flood forecasting system is beneficial or not. Finally, artificial intelligence (AI) based methods will be used in different aspects of the abovementioned topics. Assimilation experiments will be conducted on the Au Saumon watershed in Quebec and the Susquehanna watershed in Pennsylvania. The choice of distributed hydrological model is HYDROTEL, which was developed particularly for incorporating remotely sensed data. The choice of data assimilation algorithm will be decided upon testing between Ensemble Kalman Filter and Particle Filter.