We present a method to use lagrangian data from remote sensing observation in a variational data assimilation process for 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 brings information on the surface velocity thanks to an appropriate transport model. Numerical twin data assimilation experiments in an academic flow configuration demonstrate that this method makes it possible to significantly improve the identification of local bed elevation and initial conditions.