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Apport des données de télédétection haute résolution et haute répétitivité dans la modélisation hydro-météorologique

Abstract : Agricultural practices generate strong spatial and temporal heterogeneities of the vegetation in agrosystems. Land Surface Models (LSMs), which simulate water and energy fluxes between soil, vegetation and atmosphere, use coarse spatial resolutions and very simplified agricultural practices representations. Therefore, they cannot characterize such heterogeneities. However, simulating agrosystems in a realistic way is of great interest to manage water resources at landscape scale, like a river basin, or study the interactions between climate evolution and agriculture. High resolution remote sensing, like the ESA's Sentinel-2 space mission, allows monitoring the Earth surface globally with unprecedented spatio-temporal resolution of 10 meters and 5 days. This Ph. D. thesis aimed to exploit such data in the SURFEX-ISBA LSM, developed by the CNRM, to represent agricultural practices in the hydrometeorological fluxes estimation at landscape scale. The first part of the thesis aimed at representing the spatial and temporal heterogeneities of the vegetation due to the choice of sewing and harvesting dates and crop rotations in the model. I used multi-temporal Leaf Area Index and annual land cover maps derived from the Formosat-2 remote sensing date (8m, tasking acquisitions). Simulations were performed on a 576 km2 agricultural plain in southwestern France. In order to keep the interest of high resolution while saving computation time, a plot scale simulation approach was used.
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Jordi Etchanchu. Apport des données de télédétection haute résolution et haute répétitivité dans la modélisation hydro-météorologique. Hydrologie. Université Paul Sabatier - Toulouse III, 2019. Français. ⟨NNT : 2019TOU30205⟩. ⟨tel-02459812⟩

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