基于Bayes网络的暴雨情景构建和演化方法

姜波; 张超; 陈涛; 袁宏永; 范维澄

doi:10.16511/j.cnki.qhdxxb.2020.22.039

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清华大学学报（自然科学版） ›› 2021, Vol. 61 ›› Issue (6) : 509-517. DOI: 10.16511/j.cnki.qhdxxb.2020.22.039

防灾减灾

基于Bayes网络的暴雨情景构建和演化方法

姜波¹, 张超², 陈涛¹, 袁宏永¹, 范维澄¹

作者信息 +

Construction and deduction of rainstorm disaster scenarios based on Bayesian networks

JIANG Bo¹, ZHANG Chao², CHEN Tao¹, YUAN Hongyong¹, FAN Weicheng¹

Author information +

文章历史 +

摘要

暴雨灾害具有强度大、时间长、易引发次生衍生事件、应急处置难度大等特点。该文从全局的角度研究暴雨风险。针对暴雨过程复杂性和次生衍生特点，提出了一种突发事件情景构建模型，构建了暴雨情景演化全流程，进而应用Bayes网络方法，结合风险因子的概率，构建了暴雨灾害的Bayes网络模型。应用Bayes网络模型计算暴雨引发洪水的量化风险，通过考察风险因素的敏感性得出网络中关键节点。结果表明：基于Bayes网络的暴雨情景构建和定量风险分析，能够帮助应急管理决策者掌握暴雨事件全局态势，研判关键节点，提高应急响应措施的及时性、针对性。

Abstract

Rainstorm disasters are characterized by high intensity and long duration that lead to secondary events and difficult emergency response. This study analyzed rainstorm risks from a global perspective. An emergency scenario was constructed that considered the complexity of the secondary events to analyze the entire development of a rainstorm scenario. A Bayesian network (BN) was used with various risk factor probabilities to analyze the flood risks caused by various rainstorms. The key nodes in the network were then identified by a sensitivity analysis of the risk factors. The results show that the rainstorm risk analysis based on this BN model can help decision makers evaluate storm conditions, develop response plans, identify key risk factors, and improve the timeliness and effectiveness of emergency responses.

导出引用

姜波, 张超, 陈涛, 袁宏永, 范维澄. 基于Bayes网络的暴雨情景构建和演化方法[J]. 清华大学学报（自然科学版）. 2021, 61(6): 509-517 https://doi.org/10.16511/j.cnki.qhdxxb.2020.22.039

JIANG Bo, ZHANG Chao, CHEN Tao, YUAN Hongyong, FAN Weicheng. Construction and deduction of rainstorm disaster scenarios based on Bayesian networks[J]. Journal of Tsinghua University(Science and Technology). 2021, 61(6): 509-517 https://doi.org/10.16511/j.cnki.qhdxxb.2020.22.039

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基金

国家重点研发计划项目（2018YFC0807000）

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收稿日期	出版日期
2020-09-07	2021-06-15
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2021-04-28

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