Developing spatial prioritization criteria for integrated urban flood management based on a source-to-impact flood analysis

Integrated flood management is essential in urban planning to align flood protection and mitigation with the complex social and physical infrastructure in cities, and involves managing surface water by retaining and transferring it along its pathway across multiple infrastructure systems. However, despite many potential flood management solutions (natural and engineered), spatial prioritization to implement these solutions from a catchment perspective remains difficult. A transferable, source-to-impact flood analysis is developed to identify locations with high surface flooding (impact) and locations contributing to this flooding (source), to define spatial prioritization criteria for flood management intervention. The analysis was applied to Newcastle-upon-Tyne (UK) and combined a spatial rainfall cell dependency analysis with the hydrodynamic flood model CityCAT. Locations within the study area were then classified based on four priority criteria: contribution to (i) total flood extent; (ii) maximum flood depths; (iii) flooded green spaces and roads; and (iv) likelihood of flood exposure. The results illustrate the importance of considering the catchment holistically and identify hydrological linkages between flood source and impact areas, and the corresponding impact on (and interaction with) different infrastructure systems. Different criteria lead to different spatial prioritization information, which stresses the importance of combining criteria that address the specific needs and targets of the desired flood management strategy (e.g. Blue-Green infrastructure). The concept offers a basis for developing a systematic, high-level approach to inform catchment-scale prioritization for flood management intervention, which can be applied prior to developing flood alleviation schemes. In doing so, the approach will help identify opportunities to combine multiple water management solutions and allocate resources more efficiently