Performance of the Surface Water and Ocean Topography (SWOT) Mission for Monitoring Small Lakes in West Africa

The volume variability and the hydrological functioning of the thousands of lakes in the Sahelian region are poorly known. The recently launched Surface Water and Ocean Topography (SWOT) mission carrying a wide-swath <inline-formula><tex-math notation="LaTeX">$Ka$</tex-math&...

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Main Authors: Felix Girard, Laurent Kergoat, Ibrahim Mainassara, Maxime Wubda, Edwige Dayangnewende Nikiema, Amadou Abdourhamane Toure, Julien Renou, Maxime Vayre, Nicolas Taburet, Nicolas Picot, Manuela Grippa
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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Online Access:https://ieeexplore.ieee.org/document/11006264/
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Summary:The volume variability and the hydrological functioning of the thousands of lakes in the Sahelian region are poorly known. The recently launched Surface Water and Ocean Topography (SWOT) mission carrying a wide-swath <inline-formula><tex-math notation="LaTeX">$Ka$</tex-math></inline-formula>-band radar interferometer offers new opportunities for large-scale monitoring of lake dynamics, and overcomes the spatial coverage limitations of the nadir altimeters. Here, we evaluate the performance of two SWOT data products, namely the PIXel Cloud (PIXC) and the lake single pass (LakeSP), over 16 small and medium-sized lakes in the Central Sahel. For both products, water surface elevations (WSEs) are in excellent agreement with in situ data on two lakes, with 1-<inline-formula><tex-math notation="LaTeX">$\sigma$</tex-math></inline-formula> errors (68th percentile of absolute errors) between 0.06 and 0.11 m, consistently with the mission science requirements. When compared to Sentinel-3 WSE, the PIXC product shows better results than LakeSP, with 1-<inline-formula><tex-math notation="LaTeX">$\sigma$</tex-math></inline-formula> differences of 0.16 m and 0.32 m, respectively. SWOT LakeSP water surface area (WSA) estimates show a general overestimation with a median bias of 17.2% compared to Sentinel-2 measurements. SWOT pixel classification errors are found to affect both products, especially for LakeSP. Elevation-area relationships derived from combined SWOT PIXC and Sentinel-2 compare well with in situ (root mean square errors below 0.28 m), highlighting the capabilities of SWOT for monitoring lake volume changes once complemented by external water masks. Finally, annual water level amplitude estimates of more than 600 lakes of different sizes are derived using SWOT PIXC, emphasizing the spatial coverage potential of SWOT.
ISSN:1939-1404
2151-1535