Modelling the high-resolution dynamic exposure to flood in city-region.

Urban flooding exposure is generally investigated with the assumption of stationary disasters and disaster-bearing bodies within an event, and thus cannot satisfy the increasingly elaborative modelling and management of urban flood. In this study, a comprehensive method was developed to simulate dynamic exposure to urban flooding considering residents' travel behavior. First, a flood simulation was conducted using the LISFLOOD-FP model to predict the spatio-temporal distribution of flooding. Second, an agent-based model was used to simulate residents' movements during the period of urban flooding. Finally, to study the evolution and patterns of urban flooding exposure, the exposure of population, roads, and buildings to urban flooding was simulated using Lishui, China as the case study. The results indicated evident spatio-temporal variations in urban flooding and population distribution. Additionally, the exposure increased with increasing rainfall and flooding severity. The urban area near the Oujiang River was the most severely flooded and indicated the largest amount of exposure of population, roads, and buildings. Furthermore, the impacts of flooding on roads were greater than those on population and on buildings. This study presents the first fully formulated method for dynamic urban flood exposure simulation at high spatio-temporal resolution. The results of this study can provide baseline data for determining urban flood disaster vulnerability, socioeconomic loss assessment, urban disaster risk management, and for establishing emergency response plans. [ABSTRACT FROM AUTHOR]