Flood risk cascade analysis and vulnerability assessment of watershed based on Bayesian network

Under the dual impact of climate change and accelerated urbanization, urban flood disasters are frequent, resulting in severe losses, and there has been widespread concern. Through constructing the topological structure of flood control network and collecting the hydrological information from hydrological stations, this study proposes a Bayesian flood network model of Haihe river basin (Beisanhe and Yongdinghe river basin) to assess the flood risk. Flood Probability (FP) and Flood Network Cascade (flood network cascade) are proposed to characterize the vulnerability and flood cascade of flood control networks respectively. The accuracy of the flood cascade simulation of the Beisanhe river basin exceeds 80%, and the accuracy of the Yongdinghe river basin exceeds 85%. It is proved that the Bayesian network model proposed in this study has good simulation performance. The derived vulnerability assessment indicates that the central and southern regions of the Beisanhe River and Yongdinghe River basin are easily affected by floods at other nodes. The proposed Bayesian network modeling framework can also simulate the flood cascade in flood control infrastructure, so it can be used for scenario planning and real-time flood forecasting to provide information for flood management and operation.