Résumé
Hydrological modelling is one of our main tools for flood forecasting. It is essential to help stakeholders planning disaster emergency response. Although a consensus has been reached in the scientific community accepting as beneficial the integration of satellite data with hydrological models, the related assimilation techniques are still evolving. Particle filter-based assimilation techniques have proven their usefulness in various hydrological studies, but degeneracy and sample impoverishment remain their main limitations, as the ensemble of particles lose variety and only a few of them retain a significant weight in the posterior probability distribution after one or a few assimilation steps. Although this new technique has already started to be implemented in large-scale hydrological models, it has still been briefly applied to fully distributed high resolution hydrological models. In this study, a particle filter-based method (Tempered Particle Filter) is utilized to jointly assimilate SMAP soil moisture data and discharge timeseries into Iber+, a fully distributed hydrodynamic model that combines rainfall runoff and shallow water modelling. We use as a case study a 200 km2 catchment located in the northwest of Spain. The results indicate that: (1) soil moisture prediction can be strongly biased if only the streamflow at the catchment outlet is assimilated; (2) streamflow prediction, and especially surface soil moisture prediction, can be improved through the joint assimilation of streamflow and soil moisture observations; (3) it is possible to directly relate the antecedent soil moisture condition of the catchment to some of the hydrological model parameters.