An Integrated Risk Assessment for Snow Disasters in Jilin Province, China: Insights from Multi-Source Data and GIS Analysis

Snow disasters are severe natural hazards in Jilin Province, China. This research formulated a holistic risk assessment framework which integrates the factors of hazardousness, sensitivity, vulnerability, and disaster prevention and mitigation capacity. Using multi-source data and Geographic Information System (GIS), we evaluated snow disaster risks through 15 selected indicators weighted by the entropy method. Results show high-risk areas primarily concentrated in southeastern mountainous regions, including Jingyu, Fusong, Changbai, and Linjiang. Disaster sensitivity decreases from southeast to northwest, while high-vulnerability zones appear in central urban areas like Changchun. The comprehensive risk generally declines from the southeastern mountains to the northwestern plains. This assessment model effectively reflects snow disaster formation mechanisms and spatial patterns, providing scientific support for disaster prevention and emergency management in Jilin Province.

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Publication Details

Journal
Water
Published
2025-11-28
DOI
https://doi.org/10.3390/w17233402
Primary Topic
Cryospheric studies and observations
Type
article
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article

An Integrated Risk Assessment for Snow Disasters in Jilin Province, China: Insights from Multi-Source Data and GIS Analysis

Chongchang Wang, Xuetong Zhang, Shangfeng Li, Yao Wang et al.
Water
Cryospheric studies and observations
article

An Integrated Risk Assessment for Snow Disasters in Jilin Province, China: Insights from Multi-Source Data and GIS Analysis

Chongchang Wang, Xuetong Zhang, Shangfeng Li, Yao Wang, Qian Yang, Yingxin Shang
article en

Abstract

Snow disasters are severe natural hazards in Jilin Province, China. This research formulated a holistic risk assessment framework which integrates the factors of hazardousness, sensitivity, vulnerability, and disaster prevention and mitigation capacity. Using multi-source data and Geographic Information System (GIS), we evaluated snow disaster risks through 15 selected indicators weighted by the entropy method. Results show high-risk areas primarily concentrated in southeastern mountainous regions, including Jingyu, Fusong, Changbai, and Linjiang. Disaster sensitivity decreases from southeast to northwest, while high-vulnerability zones appear in central urban areas like Changchun. The comprehensive risk generally declines from the southeastern mountains to the northwestern plains. This assessment model effectively reflects snow disaster formation mechanisms and spatial patterns, providing scientific support for disaster prevention and emergency management in Jilin Province.

WaterVol. 17(23)
China Meteorological Administration (CN), Liaoning Technical University (CN), Chinese Academy of Sciences (CN), Northeast Institute of Geography and Agroecology (CN), Jiaxing Vocational Technical College (CN), Jilin Meteorological Bureau (CN), Dingxi City People's Hospital (CN)
Openalex Percentile: Top 58%
Cryospheric studies and observations
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