An integrative method for identifying potentially dangerous glacial lakes in the Himalayas.

Abstract

Glacial lakes in the Himalayas are widely distributed. Since 1900, more than 100 glacial lake outburst floods (GLOFs) have originated in the region, causing approximately 7000 deaths and considerable economic losses. Identifying potentially dangerous glacial lakes (PDGLs) is considered the first step in assessing GLOF risks. In this study, a more thorough inventory of PDGLs was presented that included numerous small-sized glacial lakes (<0.1\xa0km2) that were generally neglected in the Himalayas for decades. Moreover, the PDGL evaluation system was improved in response to several deficiencies, such as the selection of assessment factors, which are sometimes arbitrary without a solid scientific basis. We designed an optimality experiment to select the best combination of assessment factors from 57 factors to identify PDGLs. Based on the experiments on both drained and non-drained glacial lakes in the Sunkoshi Basin, eastern Himalayas, five assessment factors were determined to be the best combination: the mean slope of the parent glacier, the potential for mass movement into the lake, the mean slope of moraine dams, the watershed area, and the lake perimeter, corresponding to the GLOF triggers for ice avalanches, rockfalls and landslides, dam instability, heavy precipitation or other liquid inflows, and lake characteristics, respectively. We then applied the best combination of assessment factors to the 1650 glacial lakes with an area greater than 0.02\xa0km2 in the Himalayas. We identified 207 glacial lakes as very high-hazard and 345 as high-hazard. It is noteworthy that in various GLOF susceptibility evaluation scenarios with different assessment factors, weighting schemes, and classification approaches, similar results for glacial lakes with high outburst potential have been obtained. The results provided here can be used as benchmark data to assess the GLOF risks for local communities.