Assimilation of spatial distributed water levels into a shallow-water flood model. Part II: using a remote sensing image of Mosel riverReport as inadecuate




Assimilation of spatial distributed water levels into a shallow-water flood model. Part II: using a remote sensing image of Mosel river - Download this document for free, or read online. Document in PDF available to download.

1 CRPGL - Centre de Recherche Public - Gabriel Lippmann 2 Niglas - Nanjing Institute of Geography and Limnology 3 MOISE - Modelling, Observations, Identification for Environmental Sciences Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, INPG - Institut National Polytechnique de Grenoble 4 UMR TETIS - Territoires, Environnement, Télédétection et Information Spatiale

Abstract : With rapid flood extent mapping capabilities, Synthetic Aperture Radar SAR images of river inundation prove to be very relevant to operational flood management. In this context, a recently developed method provides distributed water levels from SAR images. Furthermore, in view of improving numerical flood prediction, a variational data assimilation method 4D-var using such distributed water level has been developed in Part I of this study. This method combines an optimal sense remote sensing data distrib- uted water levels extracted from spatial images and a 2D shallow water model. In the present article Part II of the study, we also derive water levels with a ±40 cm average vertical uncertainty from a RADARSAT-1 image of a Mosel River flood event 1997, France. Assimilated in a 2D shallow water hydraulic model using the 4D-var developed method, these SAR derived spatially distributed water levels prove to be capable of enhancing model calibration. Indeed, the assimilation process can identify optimal Manning friction coefficients, at least in the river channel. Moreover, used as a guide for sensitivity anal- ysis, remote sensing water levels allow also identifying some areas in the floodplain and the channel where Manning friction coefficients are homogeneous. This allows basing the spatial segmentation of roughness coefficient on floodplain hydraulic functioning.

keyword : Hydraulic modelling Roughness parameters Satellite SAR images Digital Elevation Model Variational data assimilation Hydraulic coherence





Author: Renaud Hostache - Xijun Lai - Jerome Monnier - Christian Puech -

Source: https://hal.archives-ouvertes.fr/



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