水深测量
高原(数学)
高度计
遥感
卫星测高
地质学
环境科学
大地测量学
海洋学
数学
数学分析
作者
Hao He,Jun Chen,Hui Sheng,Drolma Lhakpa,Kai Sun,Zheng Duan
标识
DOI:10.1080/01431161.2025.2496531
摘要
Lake water storage variations on the Tibetan Plateau (TP) serve as crucial indicators of regional hydrological dynamics and climate changes, providing more comprehensive insights than discrete measurements of lake area or water level alone. While accurate bathymetric data is fundamental for quantifying lake water storage, conventional bathymetric surveys are often constrained by logistical challenges and high operational costs in the remote region like the TP. The high altitude and minimal human activity on the TP result in exceptional lake water clarity, allowing laser altimetry to penetrate water depths of several tens of metres. In this study, we used data from Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) laser altimetry data collected from 2019 to 2023 to map five shallow, elongated lakes on the TP. First, we applied the DBSCAN denoising algorithm to eliminate anomalous photons and then fitted polynomial functions to the lakebed elevation profiles for individual tracks. Subsequently, we merged the profiles from all valid tracks within each lake area to derive comprehensive lakebed topography and depth estimates. Comparative analysis with depth measurements from previous studies revealed strong agreement in both absolute depths and spatial patterns of bottom topography. Our results showed that the water depths of the five studied lakes range from 0 to 47 m, with Puma Yumco identified as the deepest (maximum depth of 47 m) and Pelrap Tso as the shallowest (maximum depth of 26 m. The shoreline of Puma Yumco exhibited steeper topography compared to the other four lakes. This study demonstrated the capability of ICESat-2 laser altimetry as a cost-effective and reliable tool for lake bathymetry estimation on the TP. The approach presented in this study holds promise for broader applications in other regions with optically clear water bodies, thereby contributing to improve monitoring of lake dynamics and understanding of regional water storage dynamics and climate change impacts.
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