Study of the effects of urban elements on traffic access in flooding at the neighbourhood scale

Traffic congestion caused by urban flooding poses a notable threat to public safety and property and the factors influencing traffic flow exhibit pronounced spatial heterogeneity. At the neighbourhood scale, the complexity of layout and diversity of infrastructure result in distinct challenges. Investigating the impact of urban elements on traffic flow at the neighbourhood scale is a key issue in urban flood management. We adopted a neighbourhood-level perspective, based on the composition of urban elements, to analyse the natural environmental, structural, and social element indicators associated with traffic conditions under the influence of urban flooding disasters. Leveraging the advantages of the hierarchical Bayesian network (HBN) model in quantifying uncertainty relationships, we analysed indicator sensitivity to determine the impact of urban elements on traffic conditions during peak and off-peak periods at different floodwater depths at the neighbourhood scale. The results were validated using Zhengzhou City, China, as an example, and they indicated that at the neighbourhood scale, the social elements of regional population density (PD) and regional per capita GDP (GDP pc) had the highest impact on traffic conditions during urban flooding at different travel times and flood depths, with values of 0.34 and 0.25, respectively; structural elements had a relatively lower impact on traffic conditions during urban flooding. Among them, the proportion of commercial land (CLP) and the proportion of road area (RAP) had the highest impact on traffic conditions during urban flooding disasters under different travel times and flood depths, with values of 0.043 and 0.057, respectively; all indicators had a higher impact on traffic conditions during urban flooding disasters during peak periods than that during off-peak periods.