OATAO - Open Archive Toulouse Archive Ouverte Open Access Week

On the assimilation of altimetric data in 1D Saint-Venant river flow models

Brisset, Pierre and Monnier, Jérôme and Garambois, Pierre-André and Roux, Hélène On the assimilation of altimetric data in 1D Saint-Venant river flow models. (2018) Advances in Water Resources, 119. 41-59. ISSN 0309-1708

[img]
Preview
(Document in English)

PDF (Author's version) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
1MB

Official URL: https://doi.org/10.1016/j.advwatres.2018.06.004

Abstract

Given altimetry measurements, the identification capability of time varying inflow discharge Qin(t) and the Strickler coefficient K (defined as a power-law in h the water depth) of the 1D river Saint-Venant model is investigated. Various altimetry satellite missions provide water level elevation measurements of wide rivers, in particular the 21 future Surface Water and Ocean Topography (SWOT) mission. An original and synthetic reading of all the available information (data, wave propagation and the Manning-Strickler’s law residual) are represented on the so-called identifiability map. The latter provides in the space-time plane a comprehensive overview of the inverse problem features. Inferences based on Variational Data Assimilation (VDA) are investigated at the limit of the data-model inversion capability : relatively short river portions, relatively infrequent observations, that is inverse problems presenting a low identifiability index . The inflow discharge Qin(t) is infered simultaneously with the varying coefficient K(h). The bed level is either given or infered from a lower complexity model. The experiments and analysis are conducted for different scenarios (SWOT-like or multi-sensors-like). The scenarios differ by the observation frequency and by the identifiability index. Sensitivity analyses with respect to the observation errors and to the first guess values demonstrate the robustness of the VDA inferences. Finally this study aiming at fusing relatively sparse altimetric data and the 1D Saint-Venant river flow model highlights the spatiotemporal resolution lower limit, also the great potential in terms of discharge inference including for a single river reach.

Item Type:Article
Additional Information:Research data for this article can be downloaded at: https://ars.els-cdn.com/content/image/1-s2.0-S0309170817302476-mmc1.zip
HAL Id:hal-02044488
Audience (journal):International peer-reviewed journal
Uncontrolled Keywords:
Institution:French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Other partners > Ecole Nationale du Génie de l'Eau et de l'Environnement de Strasbourg - ENGEES (FRANCE)
Université de Toulouse > Institut National Polytechnique de Toulouse - INPT (FRANCE)
Université de Toulouse > Institut National des Sciences Appliquées de Toulouse - INSA (FRANCE)
Other partners > Institut National des Sciences Appliquées de Strasbourg - INSA (FRANCE)
Other partners > Université de Strasbourg - UNISTRA (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UPS (FRANCE)
Université de Toulouse > Université Toulouse - Jean Jaurès - UT2J (FRANCE)
Université de Toulouse > Université Toulouse 1 Capitole - UT1 (FRANCE)
Laboratory name:
Statistics:download
Deposited By: Helene ROUX
Deposited On:21 Feb 2019 14:00

Repository Staff Only: item control page