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

Simon Keith Allen; Guoqing Zhang; Weicai Wang; Tandong Yao; Tobias Bolch

doi:10.1016/j.scib.2019.03.011

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

Sci Bull (Beijing). 2019 Apr 15;64(7):435-445. doi: 10.1016/j.scib.2019.03.011. Epub 2019 Mar 18.

Authors

Simon Keith Allen¹, Guoqing Zhang², Weicai Wang², Tandong Yao², Tobias Bolch³

Affiliations

¹ Department of Geography, University of Zurich, Zurich 8057, Switzerland. Electronic address: simon.allen@geo.uzh.ch.
² Key Laboratory of Tibetan Environmental Changes and Land Surface Processes, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China; Center for Excellence in Tibetan Plateau Earth Sciences, Chinese Academy of Sciences, Beijing 100101, China.
³ Department of Geography, University of Zurich, Zurich 8057, Switzerland; School of Geography and Sustainable Development, University of St Andrews, St Andrews KY16 9AL, Scotland, UK.

PMID: 36659793
DOI: 10.1016/j.scib.2019.03.011

Abstract

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 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.

Keywords: Danger; Exposure; GLOF; Hazard; Himalaya; Tibetan Plateau.