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Poster

Data assimilation of image data into a spatialized water and pesticide fluxes model

Claire Lauvernet 1 Laure-An Gatel 1, 2 Damiano Pasetto 3 Arthur Vidard 4 Maëlle Nodet 4 Claudio Paniconi 2
4 AIRSEA - Mathematics and computing applied to oceanic and atmospheric flows
Inria Grenoble - Rhône-Alpes, Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology, UGA [2016-2019] - Université Grenoble Alpes [2016-2019], LJK - Laboratoire Jean Kuntzmann
Abstract : Physically-based models represent detailed surface/subsurface transfer, but the required spatial information does not allow their operational use. In situ data on pesticides in a catchment are usually rare and not continuous in time and space. Satellite images, on the other hand, well describe data in space, but only water related, and at limited time frequency. This study aims to exploit these 3 types of information (model,in situ data, images) with data assimilation methods adapted to image data, in order to improve pesticide and hydrological parameters and better understand physical processes. This poster discusses the proposed methodology as well as the available study site data and modeling components.
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Poster
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https://hal.inrae.fr/hal-02605355
Déposant : Migration Irstea Publications <>
Soumis le : samedi 16 mai 2020 - 10:51:49
Dernière modification le : jeudi 19 novembre 2020 - 13:02:32

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pub00052388.pdf
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  • HAL Id : hal-02605355, version 1
  • IRSTEA : PUB00052388

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Claire Lauvernet, Laure-An Gatel, Damiano Pasetto, Arthur Vidard, Maëlle Nodet, et al.. Data assimilation of image data into a spatialized water and pesticide fluxes model. CNA-2016 : Colloque National d'Assimilation de Données 2016, Nov 2016, Grenoble, France. pp.1, 2016. ⟨hal-02605355⟩

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