International audienceWe 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
International audienceWe address the problem of coupling 2D shallow water equations with 1D shallow ...
Abstract. We present a method to use lagrangian data from remote sensing observation in a data assim...
We present a method to use lagrangian data from remote sensing observation in a data assimilation pr...
International audienceWe address two problems related to variational data assimilation (VDA) as appl...
A major difficulty in the simulation of river hydraulics flows is bound to model parameters definiti...
International audienceWe present a method to use lagrangian data from remote sensing observation in ...
We present variational data assimilation methods applied to river hydraulics, especially when floodi...
International audienceA numerical method for model parameters identification is presented for a rive...
This work concerns the variational assimilation of lagrangian data in river hydraulics, for the iden...
This work concerns the variational assimilation of lagrangian data in river hydraulics, for the iden...
International audienceA numerical method for model parameters identification is presented for a rive...
Abstract. In the context of river hydraulics, we develop the idea of a richer local zoom model super...
Ce travail porte sur l'assimilation variationnelle de données lagrangiennes en hydraulique fluviale,...
Abstract. We present a method to use lagrangian data from remote sensing observation in a data assim...
International audienceWe address the problem of coupling 2D shallow water equations with 1D shallow ...
International audienceWe address the problem of coupling 2D shallow water equations with 1D shallow ...
Abstract. We present a method to use lagrangian data from remote sensing observation in a data assim...
We present a method to use lagrangian data from remote sensing observation in a data assimilation pr...
International audienceWe address two problems related to variational data assimilation (VDA) as appl...
A major difficulty in the simulation of river hydraulics flows is bound to model parameters definiti...
International audienceWe present a method to use lagrangian data from remote sensing observation in ...
We present variational data assimilation methods applied to river hydraulics, especially when floodi...
International audienceA numerical method for model parameters identification is presented for a rive...
This work concerns the variational assimilation of lagrangian data in river hydraulics, for the iden...
This work concerns the variational assimilation of lagrangian data in river hydraulics, for the iden...
International audienceA numerical method for model parameters identification is presented for a rive...
Abstract. In the context of river hydraulics, we develop the idea of a richer local zoom model super...
Ce travail porte sur l'assimilation variationnelle de données lagrangiennes en hydraulique fluviale,...
Abstract. We present a method to use lagrangian data from remote sensing observation in a data assim...
International audienceWe address the problem of coupling 2D shallow water equations with 1D shallow ...
International audienceWe address the problem of coupling 2D shallow water equations with 1D shallow ...
Abstract. We present a method to use lagrangian data from remote sensing observation in a data assim...
We present a method to use lagrangian data from remote sensing observation in a data assimilation pr...