SPLASH: Small Ponds and Lakes in West Africa by SWOT and High resolution satellite sensors

Principle Investigator: Manuela Grippa (Géosciences Environnement Toulouse (France))

Co-Investigator(s): Laurent Kergoat, Félix Girard, Hedwige Nikiema, Cheikh Faye, Amadou Abdourahame Toure, Ibrahim Mainassara, Maxime Wubda, Elodie Robert, Jean-Marie Dipama

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Small water bodies (SWBs) play a pivotal role in semi-arid regions, and particularly in the Sahel. They are widely spread all over the landscape, which makes them a primary source of water for people and livestock. Also, in a region where water borne diseases are the first cause of mortality among young children, water quality is a major issue. In addition, small water bodies have been shown to be a major source of greenhouse gases and they strongly impact biogeochemical and carbon cycles.

However, given their small size and their important temporal variability, their hydrological dynamics remains poorly known at the regional scale and it is and difficult to model. Also SBWs are very reactive to climate and human forcing with a complex and sometimes unexpected dynamics which questions their future evolution in a context of environmental changes and demographic increase.

Recent and forthcoming satellites provide unprecedented vision of small water bodies at the large scale, combining high resolution, high frequency and new observations of water height and volume.

The SPLASH project relying on SWOT data to explore the dynamics of water volumes in the thousands of lakes present in the study area and to switch from case studies on specific areas to the regional scale. The implementation of the project is summarized in the following steps:

1. Evaluate the performance of SWOT on lakes and reservoirs in West Africa using in-situ data and other satellite estimates by altimeters data (Sentinel3 and ICEsat-2), for the lakes below the orbit, and high resolution DEM (Pleaides) acquired when water levels are at minimum (Girard et al. 2024).
2. Analyze the spatial distribution of water stocks and their seasonal dynamics (de Fleury et al 2023), including water withdrawals from anthropogenic activities, at the regional scale.
3. Reconstruct past changes in water stocks by combining height-area relationships derived from SWOT with changes in surface water areas estimated through optical imaging (Sentinel-2, Landsat archives, and SPOT) and deep-learning algorithms (de Fleury et al. 2024).
4. Better understand the relationships between water stock dynamics, water quality parameters environmental variables (precipitation, vegetation cover, and soil characteristics), and anthropogenic forcing using a multi-sensor approach.

Combined estimates of water amount and quality will provide a global and dynamic inventory of SWBs characteristics, improving knowledge on SWBs current spatial distribution of water storage and their seasonal dynamics which is at the moment unknown at the regional scale. Addressing relationships between water bodies dynamics environmental variables and anthropogenic activities will help understanding past changes in SWBs and anticipate future changes under climate and anthropogenic constraints.

In addition, results from SPLASH will be employed for large range of applications including health issues (particularly diarrheal diseases, i.e. Robert et al 2021) and SWBs climate impacts related to the carbon cycle and to greenhouses gases emissions.