Lagrangian data assimilation for river hydraulics simulations

Abstract

We present a method to use lagrangian data from remote sensing observation in a data assimilation process for parameters identification in a river hydraulics model based on the bidimensional shallow water equations. The trajectories of particles advected by the flow can be extracted from video images and are used in addition to classical eulerian observations. This lagrangian data bring information on the surface velocity thanks to an appropriate transport model. Numerical twin data assimilation experiments demonstrate that this method makes it possible to significantly improve the identification of bed elevation and initial conditions.