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<p>Glacial lakes in the steep, high-altitude Himalaya are both hazardous and ecologically vital. They can trigger sudden glacial lake outburst floods (GLOFs) that endanger downstream communities, while also storing crucial freshwater, supporting cold-adapted biodiversity, and serving as indicators of climate change. The <i>in-situ</i> lake bathymetry data are extremely scarce in the Himalaya. The Chandra-Bhaga valley in the Western Himalaya hosts several high-risk lakes that remain largely data-deficient. This limits the ability to model GLOF hazards, assess risks to downstream populations, and evaluate ecosystem vulnerability in this semi-arid, high-elevation landscape, which includes Ramsar-designated wetlands. Using an unmanned surface vehicle (USV), we acquired high-resolution bathymetry for three priority lakes: two very high-risk proglacial lakes (Gepang Gath and Kadu Nala) and the high-altitude Ramsar wetland Chandra Tal, enabling detailed mapping of lake-bed topography and robust estimation of water storage. Our findings show that commonly used empirical formulas for estimating glacial lake volume are substantially biased in this region, prompting more <i>in-situ</i> surveys and data sharing. This unique dataset can be valuable to glacio-hydrologists, geomorphologists, climate scientists, GLOF hazard modelers, conservation biologists, and disaster risk planners.</p>

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USV-derived bathymetry of high-risk glacial lakes and a critical semi-arid ecosystem lake in the Himalaya

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月6日

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  • Sheikh Nawaz Ali,
  • Shubhajit Ghosh,
  • Anshuman Bhardwaj,
  • Pratima Pandey,
  • Lydia Sam,
  • Mitra Rajak,
  • Tara Tripura Mantha,
  • Mahesh G. Thakkar

摘要

Glacial lakes in the steep, high-altitude Himalaya are both hazardous and ecologically vital. They can trigger sudden glacial lake outburst floods (GLOFs) that endanger downstream communities, while also storing crucial freshwater, supporting cold-adapted biodiversity, and serving as indicators of climate change. The in-situ lake bathymetry data are extremely scarce in the Himalaya. The Chandra-Bhaga valley in the Western Himalaya hosts several high-risk lakes that remain largely data-deficient. This limits the ability to model GLOF hazards, assess risks to downstream populations, and evaluate ecosystem vulnerability in this semi-arid, high-elevation landscape, which includes Ramsar-designated wetlands. Using an unmanned surface vehicle (USV), we acquired high-resolution bathymetry for three priority lakes: two very high-risk proglacial lakes (Gepang Gath and Kadu Nala) and the high-altitude Ramsar wetland Chandra Tal, enabling detailed mapping of lake-bed topography and robust estimation of water storage. Our findings show that commonly used empirical formulas for estimating glacial lake volume are substantially biased in this region, prompting more in-situ surveys and data sharing. This unique dataset can be valuable to glacio-hydrologists, geomorphologists, climate scientists, GLOF hazard modelers, conservation biologists, and disaster risk planners.