CHEN G F, ZHANG X R, LI H G,et al.Flood risk assessment of tailings dams based on bibliometrics and ISM[J].Journal of Henan Polytechnic University(Natural Science) ,2025,44(6):18-26.

doi:10.16186/j.cnki.1673-9787.2025030057

Received: 2025/03/25

Revised: 2025/05/19

Published: 2025/10/14

Flood risk assessment of tailings dams based on bibliometrics and ISM

Chen Guofang1, Zhang Xinru1, Li Haigang2,3, Zheng Yu2,3, 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， Prevention and Control， Nanchang  330030， Jiangxi， China

Abstract: Objectives Floods are a critical factor affecting the safety of tailings dams. Clarifying the risk transmission pathways of floods in tailings dams helps identify key risk factors and optimize preventive measures. Methods Bibliometric analysis and expert judgment were used to select important flood risk indicators. The hierarchical structure of these indicators was determined using Interpretative Structural Modeling （ISM）. Disaster evolution pathways were further analyzed through Fault Tree Analysis （FTA）， and corresponding preventive measures were proposed.  Results （1） A total of 24 flood risk factors were identified through bibliometric analysis， from which 10 key factors were determined based on average weight values and expert experience. （2） ISM revealed the interrelationships among the 10 factors and flood risks， identifying direct， indirect， and fundamental influencing factors.  （3） A fault tree model for flood disasters in tailings dams was constructed by integrating ISM with accident cases. Boolean algebraic operations yielded 18 disaster-causing paths and 9 prevention paths. （4） Structural importance analysis indicated that insufficient drainage capacity， high peak flood flow， and shallow initial phreatic line are the most critical events influencing flood risks. Conclusions The proposed methodology， which integrates bibliometric analysis， ISM， and FTA， achieves the fusion of objective indicator screening and system modeling，  and provides theoretical support for transforming flood prevention in tailings dams  from passive response to active prevention.

Key words: tailing reservoir; flood risk; bibliometric analysis; interpretative structural modeling; fault tree analysis