2D horizontal unsteady flow model for assimilating remote sensing water-levels

Taking the initial condition,the flow boundary condition and the roughness as the control parameters,an adjoint model of 2D horizontal unsteady flow model is established based on the optimal control theory of partial differential equations. A variational data assimilation method is developed by the mathematical model and the field data of flow. According to the spatial density characteristic of remote sensing data,a new item of cost function is introduced in order to improve the assimilation of remote sensing water levels with the emphasis laid on the assimilation of remote sensing water level.The assimilation numerical experiment of synthetical single water level image shows that the spatially distributed information provided by the remote sensing data is available to the identification of spatially distributed parameters,and the additional item is useful for the assimilation of measurement and identification of time-dependent parameters. In the simulation of an actual river,the method is applied to the assimilation of distributed water level data from satellite remote sensing images.