Coupled Analysis of Risk Factor for Tailing Pond Dam Failure Accident Based on N–K Model and SNA

Liwei Yuan, Di Chen, Sumin Li (), Guolong Wang, Yanlin Li, Bin Li and Minghui Chen
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Liwei Yuan: Faculty of Public Safety and Emergency Management, Kunming University of Science and Technology, Kunming 650093, China
Di Chen: Faculty of Public Safety and Emergency Management, Kunming University of Science and Technology, Kunming 650093, China
Sumin Li: Faculty of Land Resource Engineering, Kunming University of Science and Technology, Kunming 650093, China
Guolong Wang: Yunnan Power Transmission and Transformation Engineering Co., Ltd., Kunming 650216, China
Yanlin Li: Yongshan Jinsha Lead-Zinc Mine Co., Ltd., Zhaotong 657309, China
Bin Li: Yongshan Jinsha Lead-Zinc Mine Co., Ltd., Zhaotong 657309, China
Minghui Chen: Faculty of Public Safety and Emergency Management, Kunming University of Science and Technology, Kunming 650093, China

Sustainability, 2024, vol. 16, issue 19, 1-20

Abstract: The failure of tailings pond dams represents a complex coupled system involving various risk factors, including human, governance, facilities, and environmental aspects. It is crucial to identify key risk factors at the system level to enhance the safety management of tailings ponds. We analyzed 74 cases of tailings pond dam failure accidents, both domestically and internationally, from the perspectives of human, governance, facility, and environment. We employed the 2–4 Model to identify and extract the causes of dam failures, summarizing these into four primary risk factors and 40 secondary risk factors, while constructing a risk coupling mechanism model. The natural killing (N–K) model was implemented to analyze the risk coupling values of primary risk factors and quantify these couplings. The N–K model facilitated an analysis of the risk coupling values of first-level risk factors, while social network analysis (SNA) was employed to visualize the relationships among second-level risk factors and assess the centrality and accessibility of nodes within the risk factor network. The out-degree of the risk nodes was corrected by integrating the N–K model with the SNA, leading to the identification of key risk factors associated with tailings pond dam failures and the formulation of corresponding safety prevention and control strategies. The findings indicate that managing multi-risk factor coupling is an effective approach to mitigating the occurrence of tailings pond dam failure accidents. Notably, unfavorable environmental risk factors significantly contribute to the coupling of human–governance–facility–environmental risks, necessitating targeted management strategies. Furthermore, inadequate safety supervision, weak safety awareness, inadequate receipt and inspection, and irregular operation represent additional key risk factors requiring focused prevention and control efforts.

Keywords: tailing pond safety; risk coupling; natural killing model (N–K); social network analysis (SNA); key security risk factor (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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