Hind Oubanas (INRAE, France); Pierre-Olivier Malaterre (INRAE, France); Sophie Ricci (Univ Toulouse, CNRS/CERFACS/IRD, CECI, France); Quentin Bonassies (Univ Toulouse, CNRS/CERFACS/IRD, CECI, France); Igor Gejadze (INRAE, France); Andrea Piancentini (Univ Toulouse, CNRS/CERFACS/IRD, CECI, France); Thanh Huy Nguyen (LIST, Luxembourg); Patrick Matgen (LIST, Luxembourg); Marco Chini (LIST, Luxembourg)

This study leverages the innovative capabilities of the SWOT, especially its river node products, to enhance the accuracy of riverine flood reanalysis, performed on a 50-km stretch of the Garonne River (France). The experiments incorporate various data assimilation strategies, based on the ensemble Kalman filter, which allows for sequential updates of hydraulic model parameters based on available observations. The assessments with respect to a reference simulation in OSSE mode (using synthetical SWOT-like observations) as well as with respect to Sentinel-1 and Sentinel-6 data for a real event, show that while SWOT data alone offers some improvements. In addition, combining SWOT river node products with in-situ water level measurements provides the most accurate representation of flood dynamics, both at gauge stations and along the river. Similar analyses are also carried out over other challenging catchments such as Ohio and Mississippi Rivers (US) and Severn River (UK). It was demonstrated that the assimilation of SWOT offers promising prospects for future river dynamics and flood monitoring systems making the most of various and complementary strengths of Earth Observation data. In addition, we explore the combined assimilation of SWOT WSE and altimetry satellite data to estimate river discharge over a set of study areas to improve the temporal frequency. These estimates can then be assimilated into global hydrological/routing models (RAPID, ISBA-CTRIP) to further enhance the estimates at finer scales.