Robust Blue-Green Urban Flood Risk Management Optimised With a Genetic Algorithm for Multiple Rainstorm Return Periods

Flood risk managers seek to optimise Blue-Green Infrastructure (BGI) designs to maximise return on investment. Current systems often use optimisation algorithms and detailed flood models to maximise benefit–cost ratios for single rainstorm return periods. However, the BGI scheme optimised for one return period (e.g., 100 years) may differ significantly from those optimised for others (e.g., 10 or 20 years). This study aims to assess the effectiveness of single return period-based BGI design across multiple storm magnitudes and introduces a novel multi-objective optimisation framework that simultaneously incorporates five return periods (T = 10, 20, 30, 50 and 100 years). The framework combines a non-dominated sorting genetic algorithm II (NSGA-II) with a fully distributed hydrodynamic model to optimise the spatial placement and combined size of BGI features. For the first time, direct damage cost (DDC) and expected annual damage (EAD), calculated for various building types, are used as risk objective functions, transforming a many-objective problem into a multi-objective one. Performance metrics such as Median and Maximum Risk Difference (MedRD, MaxRD) between reference and trial Pareto fronts, capturing characteristic single values from the distribution of risk differences, and the Area Under Pareto Front (AUPF), indicating overall optimisation quality, reveal that a 100-year optimised BGI design performs poorly when evaluated for other return periods, particularly shorter ones. In contrast, a BGI design optimised using composite return periods enhances performance metrics across all return periods, with the greatest improvements observed in MedRD (22%) and AUPF (73%) for the 20-year return period, and MaxRD (23%) for the 50-year return period. Furthermore, climate uplift stress testing confirms the robustness of the proposed design to future rainfall extremes. This study advocates a paradigm shift in flood risk management, moving from single maximum to multiple rainstorms-based optimised designs to enhance resilience and adaptability to future climate extremes.