A First-order Method to Identify Potentially Dangerous Glacial Lakes in a Region of the Southeastern Tibetan Plateau
Weicai Wang, Tandong Yao, Yang Gao, Xiaoxin Yang, Dambaru Ballab Kattel
Abstract
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Weicai Wang, Tandong Yao, Yang Gao, Xiaoxin Yang, Dambaru Ballab Kattel
Abstract
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Though glacial lake outburst floods have become an urgent issue on the Tibetan Plateau, no standardized methods have been proposed so far to identify and prioritize potentially dangerous glacial lakes (PDGLs). Here, we developed a first-order approach to identify PDGLs in the Boshula Mountain Range, southeastern Tibetan Plateau. Five variables—mother glacier area, distance between lake and glacier terminus, slope between lake and glacier, mean slope of moraine dam, and mother glacier snout steepness—were selected to identify PDGLs on the basis of four criteria we suggested. A fuzzy consistent matrix method was then applied to determine the weight of variables, and characteristic statistical values were used as thresholds to classify each variable. Out of 78 moraine-dammed lakes studied, we identified 8 glacial lakes as potentially very highly dangerous. We also validated our approach with 6 drained glacial lakes inside and outside our study area. Successfully identifying them as potentially very highly and/or highly dangerous lakes demonstrates the validity of the method.
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Though glacial lake outburst floods have become an urgent issue on the Tibetan Plateau, no standardized methods have been proposed so far to identify and prioritize potentially dangerous glacial lakes (PDGLs). Here, we developed a first-order approach to identify PDGLs in the Boshula Mountain Range, southeastern Tibetan Plateau. Five variables—mother glacier area, distance between lake and glacier terminus, slope between lake and glacier, mean slope of moraine dam, and mother glacier snout steepness—were selected to identify PDGLs on the basis of four criteria we suggested. A fuzzy consistent matrix method was then applied to determine the weight of variables, and characteristic statistical values were used as thresholds to classify each variable. Out of 78 moraine-dammed lakes studied, we identified 8 glacial lakes as potentially very highly dangerous. We also validated our approach with 6 drained glacial lakes inside and outside our study area. Successfully identifying them as potentially very highly and/or highly dangerous lakes demonstrates the validity of the method.
Key concepts: Glacier, Glacial period, Plateau (mathematics), Moraine, Glacial lake, Physical geography, Geology, Hydrology (agriculture)