Evaluating urban flood impacts under climate change using temporal-spatially varied design rainfall

Climate change is expected to increase both the frequency and intensity of extreme rainfall events, which poses a particularly high risk to urban areas due to their high levels of impervious surfaces and population density. Consequently, surface flooding is likely to intensify in the future, highlighting the importance of assessing climate change impacts in urban flood risk management. Design rainfall based on Depth-Duration-Frequency (DDF) curves is commonly used to assess flood risk, while climate change effects are incorporated by applying a rainfall uplift allowance to represent future scenarios. However, this approach typically assumes spatially uniform rainfall over the simulation domain, which can misrepresent storm movement as well as the timing and location of rainfall peaks, thereby compromising the accuracy of flood risk assessment. To address this limitation, it is important to use temporally and spatially variable rainfall as input to flood risk assessments. In this study, a temporally and spatially variable rainfall generator is developed, which generates spatial-temporal design rainfall events from Depth-Duration-Frequency (DDF) curves. To ensure that the generated rainfall realistically represents observed storm characteristics, the parameters of the rainfall generator are derived from historical weather radar observations. The generated events are used to drive hydrodynamic flood models to evaluate flood impacts in the West Midlands, UK, under climate change. By producing more realistic design storms, the proposed approach provides a basis for more reliable flood mapping and risk-informed adaptation planning at city-scales.