Flood Retention Lakes in a Rural‐Urban Catchment: Climate‐Dominated and Configuration‐Affected Performances

Abstract

Flood retention lakes (RLs) are widely employed in rural‐urban catchments with low impacts on the natural environment. However, insights are lacking regarding the control of climate conditions on RLs' performances and how they are affected by different geographic configurations. This study applies a 2D hydrodynamic model to perform a catchment‐scale performance assessment of RLs beyond the scope of analytical and hydrological models. We conduct extensive numerical experiments of rainstorm‐induced flooding in a rural‐urban catchment with a constructed RL and blueprinted ones upstream. Results demonstrate an L‐shaped band of satisfactory performance of the current RL in the frequency‐duration diagram, which coincides with short return periods (<5 years) and long durations (>4 hr), or short durations (<3 hr) and moderate to long return periods (5–50 years); such L‐shaped pattern is also valid for additional RLs and their combinations. With the increase in event size, the first two modes of RL performance (out of four) correspond to effective flood mitigation. When working jointly, RLs with series configurations are more effective in reducing the mainstream flood peaks, while parallel connections provide a greater spatial extent of flood hazard mitigation. For both series and parallel configurations, the upstream‐weighted settings tend to outperform downstream‐weighted ones under more extreme events; the decentralized arrangement in the urban area yields more benefits in spatial flood hazard mitigation compared to the centralized case. The study highlights the critical role of rainstorm severity (with possible spatiotemporal variabilities) in controlling RL performances despite various configurations and hydraulic settings.

Urbanization Further Intensifies Short‐Duration Rainfall Extremes in a Warmer Climate

“…Opinions vary as to whether rainfall extremes have nonstationary frequencies, and whether to adopt nonstationary models to adjust local climate allowances for infrastructure design (Agilan & Umamahesh, 2016;Ganguli & Coulibaly, 2017;Sarhadi & Soulis, 2017;Vu & Mishra, 2019;Westra et al, 2014;Yilmaz et al, 2014). However, the heterogeneous duration-and land-cover dependent non-stationarity (e.g., Figures 2b and 3), which also exhibits spatial scale-dependent variabilities, suggests that more nuanced approaches to flood risk assessment and management are needed (Yan et al, 2023). At regional scales (∼100 km), variations in non-stationarity are detected in the annual trends of return periods for urban and rural subgroups (Figure 2b) and integrated in the NS-RP scaling (Figure 3).…”