Reliable bathymetric information is essential for reservoir management, yet conventional surveys are difficult to repeat consistently across large numbers of reservoirs.This study evaluated the potential and limitations of the Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) photon-level observations for reservoir bathymetry using surveyed reference bathymetry from eight major dam reservoirs in South Korea.A fixed analysis set of 33 ICESat-2 track-reservoir cases and 66 water-body intervals was established through screening of ATL03 photon distributions, and bottom-associated ATL03 returns were assessed against surveyed reservoir depths and the official ATL13 water-depth product.Across 747 ATL03 bathymetric matchups, bottom-associated returns showed a clear correspondence with surveyed reference depths, with a squared Pearson correlation coefficient (R²) of 0.779 and root mean square difference (RMSD) of 1.20 m.Valid observations were strongly concentrated in shallow water, with 80.1% occurring at reference depths of 5 m or less.In contrast, 331 official ATL13 water-depth observations showed little systematic correspondence with surveyed reservoir depth (R² = 0.002, RMSD = 21.48 m).A representative Chungju Dam crossing further demonstrated that an along-track reservoir-bottom profile could be reconstructed from ATL03 photon observations without using surveyed bathymetry during bottom estimation, yielding R² = 0.844 and an RMSD of 0.37 m.These results indicate that useful bathymetric information exists within ATL03 photon distributions, but its practical availability remains limited by the occurrence of distinguishable bottom returns and is likely sensitive to water optical properties, depth, bottom reflectance, and observation conditions.Improved objective and automated interpretation of ATL03 bottom photons could extend this capability to poorly surveyed reservoirs and provide complementary geometric information for integration with optical, synthetic aperture radar (SAR), and wide-swath altimetry observations in multi-sensor reservoir monitoring.
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Kim et al. (2026) studied this question.
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