4.7 Article

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

Journal

SCIENCE OF THE TOTAL ENVIRONMENT
Volume 806, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.scitotenv.2021.150442

Keywords

Glacial lake outburst flood (GLOF); Hazard; GLOF susceptibility; Weighting scheme; Himalayas

Funding

  1. Second Tibetan Plateau Scientific Expedition and Research (STEP) Program [2019QZKK0208]
  2. National Natural Science Foundation of China [41771088]
  3. Strategic Priority Research Program of the Chinese Academy of Sciences [XDA20100300]
  4. International Partnership Program of Chinese Academy of Sciences [131C11KYSB20200029]

Ask authors/readers for more resources

Glacial lakes in the Himalayas have been the source of over 100 glacial lake outburst floods (GLOFs) since 1900, causing significant casualties and economic losses. This study presents a thorough inventory of potentially dangerous glacial lakes (PDGLs) and improves the evaluation system to identify high-hazard glacial lakes based on key assessment factors. The best combination of assessment factors is applied to 1650 glacial lakes in the Himalayas, identifying 207 as very high-hazard and 345 as high-hazard, which can serve as benchmark data for assessing GLOF risks for local communities.
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 km(2)) 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 km(2) 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. (C) 2021 The Authors. Published by Elsevier B.V.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available