陈国芳，张新如，李海港，等. 基于文献计量和ISM的尾矿库洪水风险评估[J].河南理工大学学报(自然科学版)，doi:10.16186/j.cnki.1673-9787.2025030057

CHEN G F, ZHANG X R, LI H G，et al．Flood risk assessment of tailings reservoirs based on bibliometrics and ISM［J］.Journal of Henan Polytechnic University( Natural Science) ，doi:10.16186/j.cnki.1673-9787. 2025030057

基于文献计量和ISM的尾矿库洪水风险评估(网络首发)

陈国芳¹，张新如¹，李海港^1,2,3，郑宇^2,3，汪柳月¹

（1.江西理工大学 应急管理与安全工程学院，江西 赣州 340010；2.江西省应急管理科学研究院，江西 南昌 330030；3.安全生产风险监测预警与防控江西省重点实验室，江西 南昌 330030）

摘要: [目的] 洪水是影响尾矿库安全的重要因素，明晰洪水对尾矿库的风险传导路径有利于帮助识别关键风险因素，优化防控措施。因此，开展尾矿库洪水风险评估模型研究，构建科学合理的风险评估体系，对有效预防尾矿库洪水灾害具有重要现实意义。[方法] 结合文献计量法和专家决策筛选出尾矿库洪水风险的重要影响指标，利用解释结构模型（ISM）对指标的层次进行划分，最后基于事故树分析（FTA）解析灾害的演化路径，并提出相应的预防措施。[结果] 结果表明：（1）基于文献计量法总共筛选出24个尾矿库洪水风险影响因素，结合平均权重值与专家经验确定了10个相对重要的尾矿库洪水风险影响因素；（2）基于ISM计算得出10个影响因素和洪水风险间的相互影响关系，确定了尾矿库洪水灾害的直接、间接和最根本影响因素；（3）结合ISM和事故案例，建立了尾矿库洪水灾害事故树，通过布尔代数运算得出了18种致灾路径和9种预防事故的路径；（4）分析事故树的结构重要度后发现对尾矿库洪水风险影响最大的事件是排洪能力不足、洪峰流量大和初始浸润线埋深浅。[结论] 提出的文献计量法、ISM与FTA相结合的方法不仅实现了客观指标筛选与系统建模的融合，而且为尾矿库防洪实现从“被动应对”向“主动阻断”的转变提供了理论支撑。

关键词: 尾矿库；洪水风险；文献计量法；解释结构模型；事故树

中图分类号：TD853

doi: 10.16186/j.cnki.1673-9787.2025030057

基金项目: 国家重点研发计划项目(2023YFC3012200)

收稿日期：2025-03-25

修回日期：2025-05-19

网络首发日期：2025-06-05

Flood risk assessment of tailings reservoirs based on bibliometrics and ISM

Chen Guofang¹, Zhang Xinru¹, Li Haigang^1,2,3, Zheng Yu^2,3, Wang Liuyue¹

(1.School of Emergency Management and Safety Engineering, Jiangxi University of Science and Technology, Ganzhou 340010, Jiangxi, China；2. Jiangxi Academy of Emergency Management Science, Nanchang 330030, Jiangxi, China；3.Jiangxi Provincial Key Laboratory of Safety Production Risk Monitoring, Early Warning, and Prevention, Nanchang Jiangxi 330030, Jiangxi, China)

Abstract: [Objective] Floods are identified as a critical factor affecting the safety of tailings pond. The risk transmission pathways of floods in tailings pond are clarified to facilitate the identification of key risk factors and the optimization of prevention measures. Therefore, researching flood risk assessment model and establishing a scientific risk assessment system hold significant practical importance for the prevention of floods in tailings pond. [Methods] Bibliometric analysis and expert decision-making were used to select the important flood risk influencing factors in tailings pond. The hierarchical structure of indicators was determined using the Interpretative Structural Modeling (ISM) method. Disaster evolution paths were analyzed and corresponding preventive measures were proposed through Fault Tree Analysis (FTA). [Results] (1) 24 flood risk factors were initially identified through bibliometric analysis. 10 key factors were ultimately determined by combining average weight values with expert experience. (2) Interrelationships between the 10 factors and flood risks were calculated through ISM. Direct, indirect, and fundamental influencing factors of tailings pond flood disasters were identified. (3) A fault tree for tailings pond flood disasters was constructed by integrating ISM with accident cases. 18 disaster-causing paths and 9 accident prevention paths were derived through Boolean algebraic operations. (4) It was revealed that insufficient drainage capacity, large peak flood flow, and shallow initial phreatic line are the most critical events affecting flood risks, through structural importance analysis. [Conclusion] With the application of the integrated methodology combining bibliometric analysis, ISM and FTA, the fusion of objective indicator screening and system modeling was achieved, and theoretical support was provided for transforming tailings pond flood prevention strategies from passive response to active prevention.

Key words: tailings reservoirs; flood risk; Bibliometric analysis; ISM; FTA

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