Chained hydrologic-hydraulic for flood modeling by assimilating SAR-derived flood extent and FFSAR-processed altimetry data

Résumé fourni par la source

Flood inundation mapping for gauged and ungauged basins relies on chained hydrologic-hydrodynamic models, combined with multi-source remote sensing (RS) datasets and in-situ gauge measurements when available. In this work, a large-scale hydrologic model provides forcing data to a high-fidelity local hydrodynamic model. The latter acts as an advanced interpolator, bridging the gap in both space and time between the high-frequency yet sparse in-situ measurements and the large-coverage but less frequent satellite data gathered from various Earth Observation (EO) missions. These data are combined with physics-based equations using data assimilation (DA) algorithms. This study presents a novel use of nadir and off-nadir altimetry data from the Sentinel-6 (S6) mission, processed with Fully-focused SAR (FFSAR) algorithms, alongside Sentinel-1 (S1) SAR-derived flood extents, for DA over the Garonne River. Using a dual state-parameter Ensemble Kalman Filter (EnKF), it is shown that assimilating S6 altimetry data brings significant improvements along the riverbed, as well as addressing gaps left by other remote sensing datasets. It was demonstrated that DA allows for the combination of various EO datasets, overcoming the limitations of spatial RS low revisit frequency and improving the representation of the flood dynamics in the riverbed and the floodplains.

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