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Simulation du métabolisme de la Seine par assimilation de données en continu

Abstract : The aim of the thesis is to implement a data assimilation scheme in the hydro-biogeochemical model ProSe, in order to assimilate continuous measurements of dissolved oxygen in the water column and to determine the temporal evolution of the physiological properties of the communities of living species. First, a new parallel version of ProSe, ProSe-P, is developed coupling the three packages: hydrodynamic, transport and biogeochemical (C-RIVE). Second, a sensitivity analysis of the C-RIVE model allows the identification of a limited number of influentiel parameters controlling the dissolved oxygen concentrations. Based on the selection, a particle filtering algorithm is implemented in order to assimilate sequentially the high frequency oxygen data. The coupling ProSe-P-particle filtre, ProSe-PA is then applied on a synthetic case to tune the numerical settings for the data assimilation and to test the efficiency of the particle filter in river water quality models. Finally, the continuous measurements of dissolved oxygen of the year 2011 in the Seine River are assimilated by ProSe-PA. The results show that ProSe-PA improves significantly the simulation of the dissolved oxygen concentrations, especially the dynamics of algal blooms periods and the fast chute of O2 for the critical periods. This application to the real oxygen data reveals however some limits of the developed approach, especially the sensitivity to the boundary conditions. Some ideas are proposed to improve the performances of ProSe-PA.
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Submitted on : Monday, December 2, 2019 - 9:39:10 AM
Last modification on : Friday, April 8, 2022 - 4:12:01 PM
Long-term archiving on: : Tuesday, March 3, 2020 - 9:46:02 PM


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  • HAL Id : tel-02388690, version 1


Shuaitao Wang. Simulation du métabolisme de la Seine par assimilation de données en continu. Hydrologie. Université Paris sciences et lettres, 2019. Français. ⟨NNT : 2019PSLEM029⟩. ⟨tel-02388690⟩



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