Evolutionary Analysis of Earthquake Secondary Geological Disasters Scenario Based on Knowledge Element and Bayesian Network
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摘要: 根据以往地震发生后现场实际破坏数据可知，地震次生地质灾害已造成严重的灾区人员伤亡和经济损失，为此，需对地震次生地质灾害情景进行演化分析。为了解地震次生地质灾害的演化过程，首先基于突发事件知识元模型，对地震次生地质灾害情景组成要素进行分析。其次基于贝叶斯模型，明确构成地震次生地质灾害演化贝叶斯网络的节点变量及其取值范围，根据这些节点变量之间的因果关系和专家打分，建立贝叶斯网络图和节点变量条件概率模型。并利用证据理论将概率融合修正，计算次生地质灾害下关键节点状态概率，实现事故关键情景的推演。最后结合知识元模型和构建的地震次生地质灾害贝叶斯网络模型，对临夏积石山6.2级地震发生后导致的次生地质灾害情景进行分析。Abstract: Based on field data from previous earthquakes, it is evident that secondary geological disasters triggered by seismic events have caused significant casualties and economic losses in affected areas. Consequently, it is essential to analyze the evolutionary scenarios of these secondary disasters. To understand the progression of earthquake-induced secondary geological hazards, this study first analyzes the components of such disaster scenarios using a critical incident knowledge element model. Then, a Bayesian network is constructed by identifying the key node variables, their value ranges, and the causal relationships among them. A corresponding Bayesian network diagram and a conditional probability model are developed, informed by expert scoring. Evidence theory is applied to refine probability fusion, enabling the calculation of the likelihood of critical node states during secondary disasters and facilitating the deduction of potential accident scenarios. Finally, the evolutionary process of secondary geological disasters following the M6.2 Linxia Jishishan earthquake is examined through the integrated use of the knowledge element model and the Bayesian network framework.
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图 1 地震次生地质灾害情景要素结构
Figure 1. Structure of scenario elements for secondary geological disasters of earthquake
图 2 地震次生地质灾害情景演化
Figure 2. Scenario evolution of secondary geological disasters of earthquakes
图 4 地震次生地质灾害贝叶斯网络
Figure 4. Bayesian networks for secondary geological disaster of earthquake
图 5 积石山地震次生地质灾害情景贝叶斯网络
Figure 5. Bayesian network for secondary geological disaster scenarios of the Jishishan earthquake
表 1 知识元模型各变量含义
Table 1. Definit ion of variables in the knowledge element model
变量 含义 $ {K}_{m} $ 共性知识 $ {N}_{m} $ 概念或属性名 $ {A}_{m} $ 状态集 $ {R}_{m} $ 属性状态变化关系集 $ {p}_{a} $ 可测特征描述 $ {d}_{a} $ 测度量纲集 $ {f}_{a} $ 关系规则 $ {p}_{r} $ 属性特征描述或辨识方法特征 $ {A}_{r}^{I} $ 输入属性状态集 $ {A}_{r}^{O} $ 输出属性状态集 $ {f}_{r} $ 输入属性到输出属性之间的具体映射函数$ {A}_{r}^{I}={f}_{r}\left({A}_{r}^{O}\right) $ 
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表 2 地震次生地质灾害事故演化过程
Table 2. Evolutionary process of secondary geological disaster accident of earthquake
名称 事故情景简述 四川汶川地震 2008年5月12日地震发生，诱发大量泥石流、滑坡、崩塌、堰塞湖等地质灾害；交通、通信、电力、供水等生命线系统以及相关企业、水利工程等遭到破坏；事故造成人员伤亡、经济损失；应急救援人员展开抗灾救援工作；最后，对灾区进行灾后重建。 青海玉树地震 2010年4月14日地震发生，诱发滑坡、崩塌、山体震裂；水渠溃决、砂土液化等导致山体局部地质灾害加剧，房屋倒塌；交通、通信、电力等生命线工程损坏；事故造成人员伤亡、经济损失；应急救援人员展开抗灾救援工作；最后，对灾区进行灾后重建。 ······ ······ 四川九寨沟 2017年8月8日地震发生，地震区域位于高山峡谷，10年内发生了2次强震，加剧了山体内部结构的破坏，诱发滚石、崩塌等地质隐患，房屋破坏；交通、通信、电力等生命线工程损坏；事故造成人员伤亡、经济损失；应急救援人员展开抗灾救援工作；最后，对灾区进行灾后重建。
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表 3 地震次生地质属性及环境属性变量离散化方法
Table 3. Discretization method for secondary geological and environmental attribute variables of earthquake
序号 变量 组数 取值范围 1 地震烈度 4 VIII/IX/X/XI 2 地震发生时间 2 易伤亡时间/相对安全时间 3 天气 3 南方雨季：4～10月；北方雨季：6～9月/高温/降雪、冬季（寒冷地区） 4 地下水位 2 地下水位高度影响地质灾害{是，否} 5 地下活动 2 地下活动影响地质灾害{是，否} 6 范围影响 2 遭受范围影响{是，否}
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表 4 贝叶斯网络中部分节点状态变量离散化分布
Table 4. Discretized distribution of state variables of some nodes in Bayesian network
序号 变量 状态值 1 灌溉区 是否属于灌溉区{是，否} 2 地震次生地质灾害导致人员伤亡 是否伤亡{是，否} 3 地震次生地质灾害导致建筑物倒塌 是否倒塌{是，否} 4 地震次生地质灾害导致通讯中断 是否中断{是，否} 5 地震次生地质灾害导致交通中断 是否中断{是，否} 6 地震次生地质灾害导致供水、电、气等基础设施破坏 是否破坏{是，否} 7 崩塌 是否发生{是，否} 8 滑坡 是否发生{是，否} 9 泥石流 是否发生{是，否} 10 滚石 是否发生{是，否} 11 地裂缝 是否发生{是，否} 12 地震次生地质灾害导致救援阻断 是否受到阻断{是，否} 13 建筑物倒塌导致人员伤亡 人员伤亡{是，否} 14 建筑物倒塌导致救援阻断 是否受到阻断{是，否} 15 疾病传染 是否有疾病传染{是，否} 16 环境污染 环境污染是否处于正常情况{是，否} 17 生活物资缺乏 物资缺乏{是，否} 18 社会恐慌 是否发生{是，否}
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表 5 基本事件概率分布
Table 5. Probability distribution of fundamental event
事件名称 概率分布（先验概率） 地震烈度 {0.34,0.5,0.08,0.08} 震发时间 {0.33,0.67} 天气 {0.33,0.67} 地下水位 {0.5,0.5} 灌溉区 {0.5,0.5} 地震次生地质灾害导致建筑物倒塌 {1,0} 地震次生地质灾害导致交通中断 {0.9,0.1} 地震次生地质灾害导致供水、电、气等基础设施破坏 {0.7,0.3} 地质灾害 {0.9,0.1} 次生灾害导致救援中断 {0.4,0.6}
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表 6 积石山地震灾害事件情景要素表示
Table 6. Representation of the elements of scenario for the earthquake disaster event in the Jishishan
情景阶段 情景要素 初始情景 孕灾环境：饱和黄土稳定强度E1，冬灌E2，范围
影响E3致灾因子：地震烈度H1 发展情景 致灾因子：滑坡-泥流灾害H2，地下水位上升H3，
道路交通恢复H4，灾害消退H5承灾体：建筑物倒塌情况C1，供水、供电、通讯
中断情况C2，道路中断情况C3，人员伤亡情况C4应急救援：交通管制、疏导M1，临时安置M2，及
时救援M3结束情景 承灾体：灾后区域恢复C5 应急救援：应急救援物资发放M4，人员安置M5，
建筑房屋灾后重建M6，疾病防疫M7
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表 7 滑坡-泥流节点变量条件概率打分及证据合成结果
Table 7. Conditional probability score for the landslide-debris flow node variable and synthesis results of evidence
代号 条件概率 m1 m2 m3 m P21 p（H21|E1） 0.45 0.3 0.55 0.400333 P22 p（H22|E1） 0.5 0.6 0.3 0.449333 P23 p（H23|E1） 0.25 0.1 0.4 0.156250
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表 8 节点变量状态概率分布
Table 8. Probability distribution of node variable state
情景阶段 变量名称 取值范围 状态概率 初始情景 饱和黄土稳定强度 不稳定/稳定 （1,0）证据信息 冬灌导致地下水位上升 发生/未发生 （1,0）证据信息 范围影响 是/否 （1,0）证据信息 地震烈度 VIII/IX/X/XI （1,0,0,0）证据信息 发展情景 滑坡-泥流灾害 严重/不严重/无 （ 0.4034 ,0.3977 ,0.1989 ）建筑物倒塌 严重/不严重/无 （ 0.4517 ,0.4061 ,0.1422 ）道路中断 是/否 （ 0.9115 ,0.0885 ）供水、电等基础设施破坏 是/否 （ 0.8794 ,0.1206 ）交通管制、疏导 是/否 （ 0.9514 ,0.0486 ）道路交通恢复 是/否 （ 0.7840 ,0.2160 ）临时安置 是/否 （ 0.9393 ,0.0607 ）及时救援 是/否 （ 0.8048 ,0.1952 ）灾害消退 是/否 （ 0.6719 ,0.3081 ）人员伤亡 严重/不严重/无 （ 0.3434 ,0.3552 ,0.3014 ）结束情景 人员安置 是/否 （ 0.7183 ,0.2817 ）应急救援物资 充足/不足 （ 0.5251 ,0.4749 ）建筑房屋灾后重建 是/否 （ 0.9623 ,0.0377 ）疾病防疫 是/否 （ 0.9260 ,0.0740 ）灾后区域恢复 是/否 （ 0.8794 ,0.1206 ）
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