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Potentially dangerous glacial lakes across the Tibetan Plateau revealed using a large-scale automated assessment approach 被引量:20

Potentially dangerous glacial lakes across the Tibetan Plateau revealed using a large-scale automated assessment approach
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摘要 Glacial lake outburst floods(GLOFs) are a major concern in the Himalaya and on the Tibetan Plateau(TP),where several disasters occurring over the past century have caused significant loss of life and damage to infrastructure. This study responds directly to the needs of local authorities to provide guidance on the most dangerous glacial lakes across TP where local monitoring and other risk reduction strategies can subsequently be targeted. Specifically, the study aims to establish a first comprehensive prioritisation ranking of lake danger for TP, considering both the likelihood and possible magnitude of any outburst event(hazard), and the exposure of downstream communities. A composite inventory of 1,291 glacial lakes(>0.1 km^2) was derived from recent remote sensing studies, and a fully automated and object assessment scheme was implemented using customised GIS tools. Based on four core determinates of GLOF hazard(lake size, watershed area, topographic potential for ice/rock avalanching, and dam steepness), the scheme accurately distinguishes the high to very high hazard level of 19 out of 20 lakes that have previously generated GLOFs. Notably, 16% of all glacial lakes threaten human settlements, with a hotspot of GLOF danger identified in the central Himalayan counties of Jilong, Nyalam, and Dingri, where the potential trans-boundary threat to communities located downstream in Nepal is also recognised. The results provide an important and object scientific basis for decision-making, and the methodological approach is ideally suited for replication across other mountainous regions where such first-order studies are lacking. Glacial lake outburst floods(GLOFs) are a major concern in the Himalaya and on the Tibetan Plateau(TP),where several disasters occurring over the past century have caused significant loss of life and damage to infrastructure. This study responds directly to the needs of local authorities to provide guidance on the most dangerous glacial lakes across TP where local monitoring and other risk reduction strategies can subsequently be targeted. Specifically, the study aims to establish a first comprehensive prioritisation ranking of lake danger for TP, considering both the likelihood and possible magnitude of any outburst event(hazard), and the exposure of downstream communities. A composite inventory of 1,291 glacial lakes(>0.1 km^2) was derived from recent remote sensing studies, and a fully automated and object assessment scheme was implemented using customised GIS tools. Based on four core determinates of GLOF hazard(lake size, watershed area, topographic potential for ice/rock avalanching, and dam steepness), the scheme accurately distinguishes the high to very high hazard level of 19 out of 20 lakes that have previously generated GLOFs. Notably, 16% of all glacial lakes threaten human settlements, with a hotspot of GLOF danger identified in the central Himalayan counties of Jilong, Nyalam, and Dingri, where the potential trans-boundary threat to communities located downstream in Nepal is also recognised. The results provide an important and object scientific basis for decision-making, and the methodological approach is ideally suited for replication across other mountainous regions where such first-order studies are lacking.
出处 《Science Bulletin》 SCIE EI CAS CSCD 2019年第7期435-445,共11页 科学通报(英文版)
基金 supported by the Swiss National Science Foundation (IZLCZ2_169979/1) counterpart grant of the National Natural Science Foundation of China (21661132003) support of the Strategic Priority Research Program (A) of the Chinese Academy of Sciences (XDA20060201) collaboration within the Dragon 4 project funded by the European Space Agency (4000121469/17/I-NB)
关键词 GLOF HAZARD Exposure DANGER TIBETAN PLATEAU HIMALAYA GLOF Hazard Exposure Danger Tibetan Plateau Himalaya
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