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dc.contributor.authorAllen, Simon Keith
dc.contributor.authorZhang, Guoqing
dc.contributor.authorWang, Weicai
dc.contributor.authorYao, Tandong
dc.contributor.authorBolch, Tobias
dc.date.accessioned2019-04-15T16:30:01Z
dc.date.available2019-04-15T16:30:01Z
dc.date.issued2019-04-15
dc.identifier.citationAllen , S K , Zhang , G , Wang , W , Yao , T & Bolch , T 2019 , ' Potentially dangerous glacial lakes across the Tibetan Plateau revealed using a large-scale automated assessment approach ' , Science Bulletin , vol. 64 , no. 7 , pp. 435-445 . https://doi.org/10.1016/j.scib.2019.03.011en
dc.identifier.issn2095-9273
dc.identifier.otherPURE: 258172109
dc.identifier.otherPURE UUID: a1f1eaaf-1d2c-40da-a077-78f79063b190
dc.identifier.otherORCID: /0000-0002-8201-5059/work/55643858
dc.identifier.otherScopus: 85063424705
dc.identifier.otherWOS: 000472941500007
dc.identifier.urihttp://hdl.handle.net/10023/17527
dc.descriptionThe study was supported by the project “Recent and future EVOlution of Glacial LAkes in China (EVOGLAC): Spatio-temporal diversity and hazard potential” funded by the Swiss National Science Foundation (No. IZLCZ2_169979/1) add counterpart grant of the Natural Science Foundation of China (No. 21661132003). The project further benefited from support of the Strategic Priority Research Program (A) of the Chinese Academy of Sciences (No. XDA20060201) and collaboration within the Dragon 4 project funded by the European Space Agency (No. 4000121469/17/I-NB).en
dc.description.abstractGlacial 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 1291 glacial lakes (>0.1 km2 ) 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.
dc.format.extent11
dc.language.isoeng
dc.relation.ispartofScience Bulletinen
dc.rightsCopyright © 2019 Science China Press. Published by Elsevier B.V. and Science China Press. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).en
dc.subjectGLOFen
dc.subjectHazarden
dc.subjectExposureen
dc.subjectDangeren
dc.subjectTibetan Plateauen
dc.subjectHimalayaen
dc.subjectGE Environmental Sciencesen
dc.subject3rd-DASen
dc.subject.lccGEen
dc.titlePotentially dangerous glacial lakes across the Tibetan Plateau revealed using a large-scale automated assessment approachen
dc.typeJournal articleen
dc.description.versionPublisher PDFen
dc.contributor.institutionUniversity of St Andrews.Bell-Edwards Geographic Data Instituteen
dc.contributor.institutionUniversity of St Andrews.School of Geography & Sustainable Developmenten
dc.identifier.doihttps://doi.org/10.1016/j.scib.2019.03.011
dc.description.statusPeer revieweden


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