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International Journal of Mathematics and Statistics 4, S09 (2009) 38-56
Assimilation of the soil resistance to evaporation in ICARE
Nourredine Alaa 1, W. Bouarifi 2, G. Chehbouni 3, G. Khiri 2, R. Hanich 2, Jean Rodolphe Roche 4, 5
(2009)

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.
1:  Faculte des Sciences et Techniques (FSTG)
Universite Cady Ayyad
2:  Faculte des Sciences et Techniques Gueliz. (FSTG)
Universite Cadi Ayyad-Marrakech
3:  Centre d'études spatiales de la biosphère (CESBIO)
CNRS : UMR5126 – Institut de recherche pour le développement [IRD] – CNES – Observatoire Midi-Pyrénées – INSU – Université Paul Sabatier [UPS] - Toulouse III
4:  Institut Elie Cartan Nancy (IECN)
CNRS : UMR7502 – INRIA – Université Henri Poincaré - Nancy I – Université Nancy II – Institut National Polytechnique de Lorraine (INPL)
5:  CALVI (INRIA Nancy - Grand Est / IECN / LSIIT / IRMA)
CNRS : UMR7005 – INRIA – Université de Strasbourg – Université de Lorraine
Mathematics/Optimization and Control