Research on urban flood and waterlog emergency scenario deductionbased on Bayesian network

doi:10.16265/j.cnki.issn 1003-3033.2021.06.024

Abstract

Abstract: In order to deal with complex evolution process of urban flood and waterlog disaster, Bayesian network was utilized in combination with evidence theory and knowledge meta-model for emergency scenario deduction research on urban flood and waterlog disasters. Then, their deduced elements were classified into disaster-pregnant environment, disaster-causing factors, disaster-bearing carrier and emergency management, and relationship between elements was analyzed. Finally, a Bayesian network of urban flood and waterlog disaster emergency scenarios was established to verify scientificity and effectiveness of emergency management measures through case study of flood disaster in Wuhan in 2016. The results show that the knowledge element model can construct a complex evolution path of urban flood and waterlog disaster emergency scenarios since evidence theory can deal with uncertain information in evolution of these scenarios while Bayesian network can effectively evaluate emergency management measures through simulation evolution.

Key words: urban flood and waterlog disaster, emergency scenario deduction, knowledge element, Bayesian network, disaster-causing factors, disaster-bearing carrier

CLC Number:

X913.4

WANG Zhe, KONG Weilei, FANG Danhui, DUAN Zhifei. Research on urban flood and waterlog emergency scenario deductionbased on Bayesian network[J]. China Safety Science Journal, 2021, 31(6): 182-188.

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