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Open AccessArticle

Flood Risk Analysis of Different Climatic Phenomena during Flood Season Based on Copula-Based Bayesian Network Method: A Case Study of Taihu Basin, China

College of Hydrology and Water Resource, Hohai University, Nanjing 210098, China
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Water 2019, 11(8), 1534; https://doi.org/10.3390/w11081534
Received: 19 June 2019 / Revised: 16 July 2019 / Accepted: 23 July 2019 / Published: 24 July 2019
(This article belongs to the Special Issue Flood Risk Analysis and Management from a System's Approach )
We propose a flood risk management model for the Taihu Basin, China, that considers the spatial and temporal differences of flood risk caused by the different climatic phenomena. In terms of time, the probability distribution of climatic phenomenon occurrence time was used to divide the flood season into plum rain and the typhoon periods. In terms of space, the Taihu Basin was divided into different sub-regions by the Copula functions. Finally, we constructed a flood risk management model using the Copula-based Bayesian network to analyze the flood risk. The results showed the plum rain period occurs from June 24 to July 21 and the typhoon period from July 22 to September 22. Considering the joint distribution of sub-region precipitation and the water level of Taihu Lake, we divided the Taihu Basin into three sub-regions (P-I, P-II, and P-III) for risk analysis in the plum rain period. However, the Taihu Basin was used as a whole for flood risk analysis in the typhoon period. Risk analysis indicated a probability of 2.4%, and 0.8%, respectively, for future adverse drainage during the plum rain period and the typhoon period, the flood risk increases rapidly with the rising water level in the Taihu Lake. View Full-Text
Keywords: flood risk analysis; plum rain period; typhoon period; copula; bayesian network; Taihu Basin flood risk analysis; plum rain period; typhoon period; copula; bayesian network; Taihu Basin
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MDPI and ACS Style

Luo, Y.; Dong, Z.; Guan, X.; Liu, Y. Flood Risk Analysis of Different Climatic Phenomena during Flood Season Based on Copula-Based Bayesian Network Method: A Case Study of Taihu Basin, China. Water 2019, 11, 1534.

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