<b>Long-term Lake Storage Variation of Nganga Rinco Revealed by ICESat-2 ATLAS Laser Point Cloud and Satellite Remote Sensing Imagery</b>

This study combines ICESat-2, the Global Surface Water Dataset (GSWD), and geographic interpolation to derive lake bathymetry and assess 30-year water storage variation of Nganga Rinco. Bathymetry in dynamic regions offers higher spatial resolution and more precise elevation data compared to the SRTM DEM. When compared to in-situ bathymetry, the derived bathymetry showed an average error of 3.64 m, with errors concentrated in deeper regions. From 1992 to 2021, Nganga Rinco’s water storage exhibited a general increase, reaching a maximum of 12.16 km³.