On variational data assimilation for 1D and 2D fluvial hydraulics
Résumé
We address two problems related to variational data assimilation (VDA) as applied to river hydraulics (1D and 2D shallow water models). First, we seek to estimate accurately some parameters such as the inflow discharge, manning coefficients, the topography and/or the initial state. We develop a method which allow to assimilate lagrangian data (trajectory particles at the surface e.g. extracted from video images). Second, we develop a joint data assimilation - coupling method. We seek to couple accurately a 1D global net-model (rivers net) and a local 2D shallow water model (zoom into a flooded area), while we assimilate data. Numerical twin experiments are presented.
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