Bayesian network of risk assessment for a super-large dam exposed to multiple natural risk sources
Bayesian network of risk assessment for a super-large dam exposed to multiple natural risk sources
复制标题
多重自然风险源特大型大坝风险评估贝叶斯网络
DOI：
10.1007/s00477-018-1631-0
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发表时间：
2018-11
影响因子：
4.2
通讯作者：
Lin Pengzhi
中科院分区：
文献类型：
--
作者：
Yu Chen;Lin Pengzhi
面对多种自然风险源的超大型大坝，其风险评价工作因其复杂的环境系统中的不确定性而显得十分艰巨。很少有风险评估研究考虑以下所有因素：梯级大坝效应、重大自然灾害源以及影响因素之间的概率关系。在这项研究中，我们提出了一个贝叶斯模型的风险分析（BMRA）下的洪水和地震的联合作用下的大坝漫顶。BMRA包括（1）构造特定的贝叶斯网络结构，（2）利用水文统计和特殊概率分析方法确定父节点的先验概率，（3）利用半经验半理论的方法和美国大坝的相关统计分析结果建立父子因果关系，（4）利用噪声OR模型建立条件概率表，并对大坝漫顶风险概率进行了评估。应用该模型对大渡河流域双江口大坝在洪水和地震作用下的漫顶风险进行了分析。研究结果表明，SJK大坝在整个生命周期内的年漫坝概率很低，满足相应的风险控制标准。与传统的方法相比，贝叶斯理论的逻辑背景下的BMRA解决了风险分析中的不确定性，并提供了一个先进的，可更新的手段来评估洪水和地震灾害的综合影响的大坝风险。因此，BMRA方法能够改进、更好地了解和更可靠地估计大坝风险。
The risk assessment of a super-large dam exposed to multiple natural risk sources is arduous because of uncertainties in the complex environmental system. Few risk assessment studies consider all of the following factors: the cascade dam effects, the major natural hazard sources and the probabilistic relations between the influencing factors. In this study, we present a Bayesian model of risk analysis (BMRA) for dam overtopping under the combined effects of flood and earthquake. The BMRA involves (1) constructing the specific Bayesian network structure, (2) determining the prior probabilities of parent nodes by hydro-statistical and special probabilistic analysis methods, (3) establishing the parent–child causal relationships by a semi-empirical semi-theoretical method and the relevant statistical analyses results for American dams, (4) creating the conditional probability table by the noisy-OR model, and evaluating the dam-specific overtopping risk probability. The model is applied to analyze the overtopping risk of the Shuangjiangkou (SJK) dam (in the Dadu River Basin, Southwestern China) under flood and seismic impacts. The results reveal that the SJK dam has a very low annual dam overtopping probability over its life cycle and satisfies the corresponding risk control standard. Compared with conventional approaches, the BMRA within the logical context of Bayesian theory addresses uncertainties in risk analysis and provides an advanced, updatable means to assess the dam risk affected by the combined effects of flood and seismic hazards. Thus, the BMRA approach enables an improved, better-informed and more reliable estimate of dam risk.
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影响因子：
3.8
作者：
Lianfa Li;Jinfeng Wang;Hareton K. N. Leung;Cheng-Sheng Jiang
通讯作者：
Lianfa Li;Jinfeng Wang;Hareton K. N. Leung;Cheng-Sheng Jiang
DOI：
10.1007/s00477-012-0663-0
发表时间：
2013-02
影响因子：
4.2
作者：
S. Adarsh;M. J. Reddy
通讯作者：
S. Adarsh;M. J. Reddy
影响因子：
3.7
作者：
Peng, M.;Zhang, L. M.
通讯作者：
Zhang, L. M.
DOI：
10.1002/9781118558522.ch12
发表时间：
2016-06
期刊：
--
影响因子：
--
作者：
L. Zhang;M. Peng;D. Chang;Yao Xu
通讯作者：
L. Zhang;M. Peng;D. Chang;Yao Xu
影响因子：
2.5
作者：
S. Ahmed
通讯作者：
S. Ahmed