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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/hess-2019-242
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-2019-242
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 12 Jun 2019

Research article | 12 Jun 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Hydrology and Earth System Sciences (HESS).

Assimilation of wide-swath altimetry observations to correct large-scale river routing model parameters

Charlotte M. Emery1,2, Sylvain Biancamaria1, Aaron Boone3, Sophie Ricci4, Mélanie C. Rochoux4, Vanessa Pedinotti5, and Cédric H. David2 Charlotte M. Emery et al.
  • 1LEGOS, 16 Avenue Edouard Belin, 31400 Toulouse, France
  • 2Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
  • 3CNRM-GAME, Meteo-France, 42 Avenue Gaspard Coriolis, 31000 Toulouse, France
  • 4CECI, Université de Toulouse, CERFACS, CNRS, 42 Avenue Gaspard Coriolis, 31057 Toulouse cedex 1, France
  • 5Magellium, 1 Rue Ariane, 31520 Ramonville-Saint-Agne, France

Abstract. Land surface models combined with river routing models are widely used to study the continental part of the water cycle. They give global estimates of water flows and storages but not without non-negligible uncertainties; among which inexact input parameters have a significant part. The incoming Surface Water and Ocean Topography (SWOT) satellite mission, with a launch schedule for 2021, will be dedicated to measure water surface elevations, widths and surface slopes of rivers larger than 100 meters at global scale. SWOT will provide a significant amount of new data for river hydrology and they could be combined, through data assimilation, to global-scale models in order to correct their input parameters and reduce their associated uncertainty. The objective of this study is to present a data assimilation platform based on the asynchronous ensemble Kalman filter (AEnKF) that assimilates synthetical SWOT observations of water elevations to correct the input parameters of a large scale hydrologic model over a 21-day time window. The study is applied on the ISBA-CTRIP model over the Amazon basin and focuses on correcting the spatial distribution of the river Manning coefficients. The data assimilation algorithm, tested through a set of Observing System Simulation Experiments (OSSE), is able to retrieve the true value of the Manning coefficients within one assimilation cycle most of the time and shows perspectives in tracking the Manning coefficient temporal variations. Ultimately, in order to deal with potential bias between the observed and the model bathymetry, the assimilation of water elevation anomalies was also tested and showed promising results.

Charlotte M. Emery et al.
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Charlotte M. Emery et al.
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Short summary
The flow of freshwater in rivers is commonly studied with computer programs known as hydrological models. An important component of those programs lies in the description of the river environment, such as the channel resistance to the flow, that is critical to accurately predict the river flow but is still not well known. Satellite data can be combined to models to enrich our knowledge of these features. Here, we show that the coming SWOT mission can help better know this channel resistance.
The flow of freshwater in rivers is commonly studied with computer programs known as...
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