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

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.本研究结合ICESat-2、全球地表水数据集（Global Surface Water Dataset, GSWD）与地理插值方法，推导恩加林科湖（Nganga Rinco）的水深数据，并评估其近30年的储水量变化。相较于SRTM数字高程模型（SRTM DEM），动态区域的水深数据具备更高的空间分辨率与更精准的高程数据。与原位实测水深相比，本研究推导得到的水深数据平均误差为3.64米，误差主要集中于较深水域。1992年至2021年间，恩加林科湖的储水量整体呈上升趋势，峰值达12.16立方千米。