Articles | Volume 25, issue 7
https://doi.org/10.5194/hess-25-4081-2021
https://doi.org/10.5194/hess-25-4081-2021
Research article
 | 
14 Jul 2021
Research article |  | 14 Jul 2021

Assimilation of probabilistic flood maps from SAR data into a coupled hydrologic–hydraulic forecasting model: a proof of concept

Concetta Di Mauro​​​​​​​, Renaud Hostache, Patrick Matgen, Ramona Pelich, Marco Chini, Peter Jan van Leeuwen, Nancy K. Nichols, and Günter Blöschl

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Latest update: 13 Dec 2024
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Short summary
This study evaluates how the sequential assimilation of flood extent derived from synthetic aperture radar data can help improve flood forecasting. In particular, we carried out twin experiments based on a synthetically generated dataset with controlled uncertainty. Our empirical results demonstrate the efficiency of the proposed data assimilation framework, as forecasting errors are substantially reduced as a result of the assimilation.