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Fonds National Suisse de la Recherche Scientifique (FNSRS) 2022

Improving Process Representation in Hydrological Models for Reliable Climate Change and Land Use Change Predictions with Satellite Data in West Africa

Satellite Hydrological Models Climate Change

Titre : Improving Process Representation in Hydrological Models for Reliable Climate Change and Land Use Change Predictions with Satellite Data in West Africa

Numéro  : 199547

Début/Fin : 01.01.2022 - 30.06.2023

Requérant  : Dembélé Moctar
Institution de Recherche : School of Geography and the Environment University of Oxford

Présentation
Amélioration de la représentation des processus dans les modèles hydrologiques pour des prédictions fiables en contexte de changement climatique et de l’utilisation des terres avec des données satellitaires en Afrique de l’Ouest.

Résumé
Global warming is imposing unprecedented pressure on the world’s water resources with high uncertainty in water availability and the occurrence of extreme weather events such as floods and droughts. Unfortunately, our current understanding of the water cycle and its evolution under climate change is still imperfect, thereby making accurate process representation in models one of the key challenge in hydrology in the 21st century. Furthermore, ground measurement of hydro-climatic variables is a luxury in major parts of the world, thus impeding research and operational management of water resources in data scarce regions. This is the case in Africa, which is expected to be hardest hit by climate change in the near future, thus exposing its growing population to serious risks associated with hydrological extremes, risks which are extremely poorly known, rendering adaptation extremely difficult. Nowadays, a unique opportunity arises to advance hydrological predictions in poorly gauged regions because of the increasing and unprecedented availability of satellite remote sensing data, and the development of high-performance computational facilities. However, these datasets contain uncertainties. Therefore, appropriate strategies are needed to harness their most reliable and useful content for hydrological modelling. This research project aims at improving hydrological model predictions for a better understanding and assessment of hydrological systems in changing environments. To fulfil this objective, the methodology consists of (1) exploring the potential of multi-process model calibration strategies and data assimilation techniques to improve hydrological model simulations, and (2) developing innovative approaches to inform hydrological models with readily available satellite data. The objective is to better understand and improve the representation of hydrological processes in the globally used and state-of-the-art Joint UK Land Environment Simulator (JULES) model for reliable assessment of climate change and anthropogenic land use change impacts on water resources. The selected case studies are two major transboundary river basins in West Africa, the Volta and the Niger, which are typical examples of large river basins both severely affected by climate change and heavily understudied, particularly because of the notorious lack of hydro-meteorological ground observations. The expected advances in hydrological process representation will improve our understanding of complex land-atmosphere interactions, and ultimately lead to a better assessment of environmental change impacts on water resources. Therefore, the resulting outcome has both scientific and societal relevance. This timely and high-impact research will be carried out in the School of Geography and Environment at the University of Oxford, United Kingdom, where top-end modelling expertise and computational equipment are available to successfully achieve the ambitious research objectives.

Mots clés : Land surface models ; Data scarce regions ; West Africa ; Hydrological modelling ; Satellite remote sensing ; Land Use Land Cover Change ; Climate change

Fonds National Suisse de la Recherche Scientifique

Page publiée le 17 septembre 2022