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Pré-Publication, Document De Travail Année : 2015

Inverse computational algorithms for flood plain dynamic modelling

Résumé

Flood plain dynamic modelling remains a challenge because of the complex multi-scale data, data uncertainties and the uncertain heterogeneous flow measurements. Mathematical models based on the 2d shallow water equations are generally suitable but wetting-drying processes can be driven by small scale data features. The present study aims at deriving an accurate and robust direct solver for dynamic wet-dry fronts and a variational inverse method leading to sensitivity analyses and data assimilation processes. The numerical schemes and algorithms are assessed on academic benchmarks representing well some flood dynamic features and a real test case (Lèze river, southwestern of France). Original sensitivity maps with respect to the (friction , topography) fields are performed and discussed. Furthermore, the identification of inflow discharges (time series) or roughness coefficients defined by land covers (spatially distributed parameters) demonstrate the relevance of the approach and the algorithm efficiency. Inverse computational methods may contribute to breakthrough in flood plain modelling.
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Dates et versions

hal-01233493 , version 1 (25-11-2015)

Identifiants

  • HAL Id : hal-01233493 , version 1

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Jerome Monnier, Frédéric Couderc, Denis Dartus, Kévin Larnier, Ronan Madec, et al.. Inverse computational algorithms for flood plain dynamic modelling. 2015. ⟨hal-01233493⟩
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