Risk assessment for people and vehicles in an extreme urban flood: Case study of the “7.20” flood event in Zhengzhou, China

Extreme flood events in urban environments have become a major source of threat to human life and property, and therefore have attracted widespread concerns. In this study, a hydrodynamic modeling and flood risk assessment framework was utilized to replicate the “7.20” extreme urban flood process in Zhengzhou, China, with precise assessments of corresponding hazard degrees for people and vehicles being provided. Model predictions indicated that the study area was seriously flooded during the “7.20” urban flood event, with 28.9% of the buildings having an inundation water depth of more than 0.5 m. Due to the low-lying nature, roads were the vulnerable areas during the flood event, with the maximum water depth and flow velocity up to 1.2 m and 1.0 m/s, respectively. In addition, the response between rainfall intensity and flood risk was also discussed. The overall hazard degrees for people and vehicles sharply increased during the peak rainfall period, and however, the hazard degree of people declined after this period, while the hazard degree for vehicles remained almost unchanged. The flood risk in the Jingguang Road North Tunnel (JRT) was extremely high after the tunnel was inundated. The cascaded inflow from the entrance of the tunnel would reduce the evacuation speed of trapped people, or even lead to a loss of human stability and cause consequent drowning. The results obtained in this study can facilitate the awareness of urban flood risk among the public as well as decision-makers, and can therefore help to improve urban resilience . • A module was proposed for evacuation assessment from flooded underground spaces. • The “7.20” extreme urban flood event in Zhengzhou was simulated. • Instability formulas were used to evaluate flood risks of people and vehicles. • Spatial and temporal variations of flood risks to people and vehicles were investigated. • The temporal variation in escape time from a seriously flooded tunnel was calculated.