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Assimilation of the soil resistance to evaporation in ICARE Model

N. Alaa, W. Bouarifi, G. Chehbouni, R. Khiri, L. Hanich, J.R. Roche

Abstract


In recent years, understanding and quantifying the global hydrologic cycle has become a priority research topic. Hydrologists now face the challenge to apply true data assimilation techniques to all problems where remote sensing data can provide new insights. However, this is a difficult task due to the highly nonlinear nature of land-surface processes, the size of the problem, and the lack of data and experience to determine error statistics accurately. Consequently, the implementation of data assimilation techniques always requires trade-offs between resolution, complexity, computational effort, and data availability. Our approach is based in variational data assimilation. All control theory or variational assimilation approaches perform a global time-space adjustment of the model solution to all observations and thus solve a smoothing problem. Firstly, we give a description about the site of this study and then we describe the modeling approach used to simulate the temperatures and moistures in SVAT-ICARE model. The optimisation problem is then formulated in the framework of control optimal theory, followed by a brief discussion of genetic algorithms used in the optimization algorithm.

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