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

作     者：Simon Keith Allen Guoqing Zhang Weicai Wang TANDong Yao Tobias Bolch 

作者机构：Department of Geography University of Zurich Key Laboratory of Tibetan Environmental Changes and Land Surface Processes Institute of Tibetan Plateau Research Chinese Academy of Sciences Center for Excellence in Tibetan Plateau Earth Sciences Chinese Academy of Sciences School of Geography and Sustainable Development University of St Andrews 

出 版 物：《Science Bulletin》 (科学通报（英文版）)

年 卷 期：2019年第64卷第7期

页      面：435-445页

核心收录：

学科分类：07[理学] 08[工学] 081501[工学-水文学及水资源] 0815[工学-水利工程] 0705[理学-地理学] 070501[理学-自然地理学] 

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) 

主　　题：GLOF Hazard Exposure Danger Tibetan Plateau Himalaya 

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.