International audienceA numerical method for model parameters identification is presented for a river model based on a finite volume discretization of the bidimensional shallow water equations. We use variational data assimilation to combine optimally physical information from the model and observation data of the physical system in order to identify the value of model inputs that correspond to a numerical simulation which is consistent with reality. Two numerical examples demonstrate the efficiency of the method for the identification of the inlet discharge and the bed elevation. An application to real data on the Pearl River for the identification of boundary conditions is presented
International audienceWe present a method to use lagrangian data from remote sensing observation in ...
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 audienceA numerical method for model parameters identification is presented for a rive...
International audienceWe address two problems related to variational data assimilation (VDA) as appl...
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...
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...
Ce travail porte sur l'assimilation variationnelle de données lagrangiennes en hydraulique fluviale,...
International audienceRecent applications of remote sensing techniques produce rich spatially distri...
We analyze in this thesis various aspects associated with the modeling of free surface flows in shal...
In river hydraulics, assimilation of water level measurements at gauging stations is well controlled...
International audienceRecent applications of remote sensing techniques produce rich spatially distri...
International audienceRecent applications of remote sensing techniques produce rich spatially distri...
International audienceWe present a method to use lagrangian data from remote sensing observation in ...
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 audienceA numerical method for model parameters identification is presented for a rive...
International audienceWe address two problems related to variational data assimilation (VDA) as appl...
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...
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...
Ce travail porte sur l'assimilation variationnelle de données lagrangiennes en hydraulique fluviale,...
International audienceRecent applications of remote sensing techniques produce rich spatially distri...
We analyze in this thesis various aspects associated with the modeling of free surface flows in shal...
In river hydraulics, assimilation of water level measurements at gauging stations is well controlled...
International audienceRecent applications of remote sensing techniques produce rich spatially distri...
International audienceRecent applications of remote sensing techniques produce rich spatially distri...
International audienceWe present a method to use lagrangian data from remote sensing observation in ...
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...