Abstract

The Tien Shan Mountain range connects Central Asia with northwestern China and is a crucial transport junction between East and West Asia. It is a common location for regional debris flows, which pose a significant risk to ecological security and the safety of people and property. Nevertheless, limited knowledge exists about the distribution of disaster risks and the impacted populations. This study uses advanced machine learning techniques to identify the key natural and social factors influencing these hazards and incorporates the Social Vulnerability Index (SoVI) to assess societal vulnerability. The outcomes demonstrate that (1) the debris flow hazard in the Tien Shan Mountain area is primarily governed by the geological structure, which dictates the material source and, in turn, dictates the onset of debris flows. (2) The vulnerability demonstrates a high spatial tendency in the north and a low one in the south, with evident spatial clustering characteristics. (3) A total of 19.13% of the study area is classified as high-hazard, with specific distribution zones including the northern foothills of the Tien Shan Mountains, the low-mountain zones of the southern foothills of the Tien Shan Mountains, and the Yili Valley zone. This holistic approach offers valuable insights into the spatial distribution of risks, aiding in prioritizing disaster preparedness and mitigation efforts. Also, our findings and conclusions are beneficial for local decision makers to allocate resources effectively and promote sustainable development practices in the region.

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