基于贝叶斯网络的梯级水库连溃风险

Risk of cascade reservoirs collapse based on Bayesian network

  • 摘要: 为研究梯级水库漫坝连溃的风险,并探索贝叶斯网络在水库连溃风险分析中的可行性,通过构建洪水作用下双库连溃的贝叶斯网络模型,并选取四川省大渡河上两相邻梯级水库进行分析,以推求水库漫(溃)坝概率及评估连溃风险。分析过程表明贝叶斯网络方法能直观、简便地分析多风险源共同作用下的水库群连溃风险问题。结果表明,两水库天然洪水漫坝条件概率的数量级均为10-6,洪水引发单库漫坝风险较小;正常蓄水位以上,上游水库溃坝洪水致下游水库漫坝条件概率超0.8,即上游水库溃坝导致水库连溃的风险很大。

     

    Abstract: This paper evaluated the risk of reservoirs collapse caused by nature-flood-based dam overtopping using a Bayesian network. Probabilities of single and cascade reservoirs collapse were calculated for reservoirs in Sichuan Province. The analysis demonstrates that Bayesian network is intuitive and user-friendly to investigate the risk of reservoirs collapse under multiple risk sources. A same conditional dam overtopping probability magnitude of 10-6 is derived, indicating a low risk of single reservoir dam overtopping. However, the conditional probability of dam overtopping is over 0.8 when the water storage level is higher than normal, meaning there is a high probability of dam overtopping under this condition.

     

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