RAPID applied to the SIM-France model

Authors

  • Cédric H. David,

    Corresponding author
    1. Centre de Géosciences, Mines Paristech, Fontainebleau, France
    2. Center for Research in Water Resources, University of Texas at Austin, Austin, TX, USA
    3. Department of Geological Sciences, Jackson School of Geosciences, University of Texas at Austin, Austin, TX, USA
    • Department of Geological Sciences, Jackson School of Geosciences, The University of Texas at Austin, 1 University Station C1160, Austin, TX 78712, USA.
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  • Florence Habets,

    1. UMR-7619 Sisyphe [CNRS, UPMC, Mines-Paristech], Paris, France
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  • David R. Maidment,

    1. Center for Research in Water Resources, University of Texas at Austin, Austin, TX, USA
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  • Zong-Liang Yang

    1. Department of Geological Sciences, Jackson School of Geosciences, University of Texas at Austin, Austin, TX, USA
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Abstract

SIM-France is a large connected atmosphere/land surface/river/groundwater modelling system that simulates the water cycle throughout metropolitan France. The work presented in this study investigates the replacement of the river routing scheme in SIM-France by a river network model called RAPID to enhance the capacity to relate simulated flows to river gauges and to take advantage of the automated parameter estimation procedure of RAPID. RAPID was run with SIM-France over a 10-year period and results compared with those of the previous river routing scheme. We found that while the formulation of RAPID enhanced the functionality of SIM-France, the flow simulations are comparable in accuracy to those previously obtained by SIM-France. Sub-basin optimization of RAPID parameters was found to increase model efficiency. A single criterion for quantifying the quality of river flow simulations using several river gauges globally in a river network is developed that normalizes the square error of modelled flow to allow equal treatment of all gauging stations regardless of the magnitude of flow. The use of this criterion as the cost function for parameter estimation in RAPID allows better results than by increasing the degree of spatial variability in optimization of model parameters. Likewise, increased spatial variability of RAPID parameters through accounting for topography is shown to enhance model performance. Copyright © 2011 John Wiley & Sons, Ltd.

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