Process-driven susceptibility assessment of glacial lake outburst debris flow in the Himalayas under climate change

IF 6.4 1区 地球科学 Q1 ENVIRONMENTAL SCIENCES Advances in Climate Change Research Pub Date : 2024-06-01 DOI:10.1016/j.accre.2023.11.002
Bin Zhou , Qiang Zou , Hu Jiang , Tao Yang , Wen-Tao Zhou , Si-Yu Chen , Hong-Kun Yao
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Abstract

Global warming is causing glaciers to retreat and glacial lakes to expand in the Himalayas, which amplifies the risk of glacial lake outburst debris flows (GLODFs) and poses a significant threat to downstream lives and infrastructures. However, the complex interplay between GLODF occurrences and associated indicators, coupled with the lack of a comprehensive susceptibility indicator system that considers the entire GLODF process, presents a substantial challenge in assessing GLODF susceptibility in the Himalayas. This study proposes a process-driven GLODF susceptibility assessment indicator system responding to climate change that considers the complete process of GLODF formation, incorporating relevant parameters about upstream, themselves, and downstream of glacial lakes. Furthermore, to mitigate subjective factors associated with traditional evaluation methods, we developed three novel hybrid machine-learning models by integrating classic machine-learning algorithms with the whale optimization algorithm (WOA) to delineate the distribution of GLODF susceptibility in the Himalayas. All the hybrid models effectively predicted the GLODFs occurrence, with the WOA-SVC model demonstrating the highest prediction accuracy. Approximately 34% of the catchments exhibit high and very high susceptibility levels, primarily concentrated along the north and south sides of the Himalayan ridge, particularly in the eastern and central Himalayas. Indicators capturing the physical formation process of hazards, such as topographic potential (highest relative importance value of 40%), can precisely identify GLODF. A total of 128 catchments pose potential transboundary threats, with 24 classified as having a very high susceptibility level and 25 as having a high susceptibility level. Notably, the border region between China and Nepal is a prominent hotspot for transboundary threats of GLODF. These findings can provide valuable clues for disaster prevention, mitigation, and cross-border coordination in the Himalayas.

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气候变化下喜马拉雅山冰湖溃决泥石流的过程驱动易感性评估
全球变暖正在导致喜马拉雅山脉的冰川退缩和冰湖扩大,这加大了冰湖溃决泥石流(GLODF)的风险,并对下游生命和基础设施构成重大威胁。然而,冰湖溃决泥石流的发生与相关指标之间存在复杂的相互作用,加之缺乏考虑冰湖溃决泥石流整个过程的综合易感性指标体系,这给评估喜马拉雅山冰湖溃决泥石流易感性带来了巨大挑战。本研究针对气候变化提出了一个过程驱动的 GLODF 易感性评估指标体系,该体系考虑了 GLODF 形成的完整过程,纳入了冰川湖泊上游、自身和下游的相关参数。此外,为了减少传统评估方法中的主观因素,我们通过将经典机器学习算法与鲸鱼优化算法(WOA)相结合,开发了三种新型混合机器学习模型,以划定喜马拉雅山地区 GLODF 易感性的分布。所有混合模型都能有效预测 GLODF 的发生,其中 WOA-SVC 模型的预测精度最高。约有 34% 的集水区表现出高和极高的易发程度,主要集中在喜马拉雅山脉山脊的南北两侧,尤其是喜马拉雅山脉的东部和中部。捕捉灾害物理形成过程的指标,如地形潜力(相对重要性最高值为 40%),可精确识别全球沼泽地发展框架。共有 128 个流域构成了潜在的跨境威胁,其中 24 个流域被归类为极易受灾等级,25 个流域被归类为较易受灾等级。值得注意的是,中国和尼泊尔边境地区是 GLODF 跨界威胁的突出热点。这些发现可为喜马拉雅地区的防灾、减灾和跨境协调提供有价值的线索。
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来源期刊
Advances in Climate Change Research
Advances in Climate Change Research Earth and Planetary Sciences-Atmospheric Science
CiteScore
9.80
自引率
4.10%
发文量
424
审稿时长
107 days
期刊介绍: Advances in Climate Change Research publishes scientific research and analyses on climate change and the interactions of climate change with society. This journal encompasses basic science and economic, social, and policy research, including studies on mitigation and adaptation to climate change. Advances in Climate Change Research attempts to promote research in climate change and provide an impetus for the application of research achievements in numerous aspects, such as socioeconomic sustainable development, responses to the adaptation and mitigation of climate change, diplomatic negotiations of climate and environment policies, and the protection and exploitation of natural resources.
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