黄河流域复合型灾害风险特征与演化模式研究  

Investigation of risk characteristics and evolution models for compound disasters in the Yellow River Basin

作　　者：任捷 王迪 王雅荣[1,2,3] 刘颖 REN Jie;WANG Di;WANG Yarong;LIU Ying(School of Economics and Management,Inner Mongolia University of Science&Technology,Baotou 014010,Inner Mongolia,China;Industrial Informatization and Industrial Innovation Research Center,Key Research Base of Humanities and Social Sciences,the Inner Mongolia Autonomous Region,Baotou 014010,Inner Mongolia,China;Yellow River“Ji Zi Wan”Development Research Center,the Key Research Base of Philosophy and Social Sciences in Inner Mongolia,Baotou 014010,Inner Mongolia,China)

机构地区：[1]内蒙古科技大学经济与管理学院,内蒙古包头014010 [2]内蒙古自治区高等学校人文社会科学重点研究基地产业信息化与产业创新研究中心,内蒙古包头014010 [3]内蒙古哲学社会科学重点研究基地黄河“几字弯”发展研究基地,内蒙古包头014010

出　　处：《安全与环境学报》2025年第3期1078-1089,共12页Journal of Safety and Environment

基　　金：国家自然科学基金青年项目(72404153);内蒙古自治区高等学校人文社会科学重点研究基地开放课题(KFSM-KDSK0208);内蒙古自治区社会科学基金2024年度高质量发展专项课题(2024EY22);内蒙古自治区直属高校基本科研业务项目(2024QNJS154)。

摘　　要：为探究黄河流域复合型灾害的特征及其风险演化模式,首先厘清复合型灾害的基本特征,基于黄河流域2000-2023年的1553条灾害数据,归纳出10种典型的灾害链演化路径。通过构建复合型灾害的复杂网络模型,运用基于节点相似度和标签传播的加权网络社团划分算法(Weighted Network Community Division Method based on Node Similarity and Label Propagation,SLWCD)对网络节点进行分类,识别影响复合型灾害风险水平的关键节点。结果表明:洪涝灾害为黄河流域复合型灾害网络中的核心节点,具有最强的全局影响力;水污染事故较易受到自然灾害或首发事故的触发,干旱与地震则为黄河流域的高频灾害。聚类分析结果揭示了四类显著的效应机制,分别为:风雨沙灾害与社会安全事件的时空累积效应、各类灾害与公共卫生事件的级联效应、地质灾害与事故灾难的联动效应及土地问题对公共卫生事件的长期影响。此外,通过Python模拟,研究发现黄河流域复合型灾害网络中潜在路径长度大于4的灾害链条共有7646条。基于研究结果,提出了以下政策建议:增强灾害预警与应急响应能力,统筹跨部门协作,强化高风险区域的监测,推进生态保护与可持续发展,优化水资源与污染防控,采取综合适应策略应对气候变化,以有效提升黄河流域应对复合型灾害的能力。This study elucidates the characteristics of compound disasters,highlighting their diverse types,significant spatiotemporal accumulation effects,strong interconnections among various disasters,and pronounced cascading effects.Utilizing a dataset of 1553 disaster records from the Yellow River Basin spanning 2000 to 2023,we identify and analyze ten typical pathways of disaster chain evolution.By constructing a complex network model of compound disasters and employing Weighted Network Community Division Method based on Node Similarity and Label Propagation(SLWCD)clustering analysis to categorize network nodes,we identify key nodes that significantly impact the risk levels of these disasters.The findings reveal that flood disasters serve as core nodes within the compound disaster network of the Yellow River Basin,exhibiting the strongest global influence.Water pollution incidents can be readily triggered by natural disasters or primary accidents,with droughts and earthquakes being common disaster types in the region.The clustering results reveal four distinct effects:spatial-temporal accumulation effects of wind,rain,and sand disasters combined with social security events;cascading effects of various disasters associated with public health incidents;interaction effects between geological disasters and industrial accidents;the long-term impact of land issues on public health events.Simulations conducted using Python reveal that there are 7646 disaster chains within the compound disaster network of the Yellow River Basin,with potential path lengths exceeding 4.Notably,over 90%of these paths have a length of 5,while the most common paths are of length 7.The longest identified path reaches a length of 10,and as path lengths increase,the concealment of disaster chains also tends to rise.Climate change and land-use changes significantly exacerbate the complexity of these disaster chains.In light of these findings,this study recommends the following policy measures:enhance disaster warning and emergency response capabilitie

关 键 词：公共安全 黄河流域 复合型灾害特征 复杂网络 演化模式 

分 类 号：X43[环境科学与工程—灾害防治]