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<p>Quantifying the coupling relationships among risk factors of earth-rock dam break, identifying critical failure paths, and determining core risk factors are essential for improving dam risk management. To this end, this study proposes a risk factor coupling analysis framework based on the Interpretive Structural Model (ISM) and Bayesian Network (BN). First, 16 representative risk factors were selected through an analysis of domestic and international dam failure cases, establishing a risk assessment index system for earth-rock dam break. A statistical analysis was then conducted on 592 cases of failed and hazardous earth-rock dams. Second, the ISM method was employed to hierarchically classify risk factors, and a BN-based topological structure was constructed. The Expectation Maximization (EM) algorithm was used for BN parameter learning. Finally, causal inference and inverse diagnostic reasoning were applied to quantitatively analyze the influence intensity and sensitivity of risk factors. The results indicate a significant coupling effect among risk factors, with multi-factor interactions markedly increasing dam break risk. The most probable break path is: improper human operation (S5) → extreme flood (S1) → slope instability (S7) → damage to flood discharge structures (S4) → overtopping (L1) → dam break. The key risk factors influencing dam break are L1, insufficient spillway discharge capacity (S3), and S4. This study provides a scientific basis for the safety management and risk prevention of earth-rock dams, contributing to improved risk identification and mitigation capabilities in dam engineering.</p>

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Coupling analysis of earth-rock dam break risk factors based on the ISM-BN model

  • 期刊论文

  • 发表日期：

    2025年8月14日

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  • Yanlong Li,
  • Qiaogang Yin,
  • Yuchun Zhang,
  • Ting Wang,
  • Ning Shi,
  • Zengguang Xu,
  • Yunhe Liu

摘要

Quantifying the coupling relationships among risk factors of earth-rock dam break, identifying critical failure paths, and determining core risk factors are essential for improving dam risk management. To this end, this study proposes a risk factor coupling analysis framework based on the Interpretive Structural Model (ISM) and Bayesian Network (BN). First, 16 representative risk factors were selected through an analysis of domestic and international dam failure cases, establishing a risk assessment index system for earth-rock dam break. A statistical analysis was then conducted on 592 cases of failed and hazardous earth-rock dams. Second, the ISM method was employed to hierarchically classify risk factors, and a BN-based topological structure was constructed. The Expectation Maximization (EM) algorithm was used for BN parameter learning. Finally, causal inference and inverse diagnostic reasoning were applied to quantitatively analyze the influence intensity and sensitivity of risk factors. The results indicate a significant coupling effect among risk factors, with multi-factor interactions markedly increasing dam break risk. The most probable break path is: improper human operation (S5) → extreme flood (S1) → slope instability (S7) → damage to flood discharge structures (S4) → overtopping (L1) → dam break. The key risk factors influencing dam break are L1, insufficient spillway discharge capacity (S3), and S4. This study provides a scientific basis for the safety management and risk prevention of earth-rock dams, contributing to improved risk identification and mitigation capabilities in dam engineering.