Data assimilation to quantify and reduce uncertainty in ecohydrology modelling
Résumé
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. In my studies, I aim to exploit these 3 types of information (model, in situ data,
images) with adapted data assimilation methods, in order to improve pesticide and hydrological parameters, and quantify and reduce the simulations uncertainties. This seminary will discuss the methods and results from several studies developed in the RIVERLY unit (INRAE Lyon), from hydroclimatology to ecohydrology.
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