Toggle Main Menu Toggle Search

Open Access padlockePrints

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

Lookup NU author(s): Asid Ur Rehman, Dr Vassilis GlenisORCiD, Dr Elizabeth Lewis, Emeritus Professor Chris Kilsby, Professor Claire WalshORCiD

Downloads


Licence

This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

© 2025 The Author(s). Journal of Flood Risk Management published by Chartered Institution of Water and Environmental Management and John Wiley & Sons Ltd. 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.


Publication metadata

Author(s): Ur Rehman A, Glenis V, Lewis E, Kilsby C, Walsh C

Publication type: Article

Publication status: Published

Journal: Journal of Flood Risk Management

Year: 2025

Volume: 18

Issue: 3

Online publication date: 07/09/2025

Acceptance date: 04/08/2025

Date deposited: 16/09/2025

ISSN (print): 1753-318X

ISSN (electronic): 1753-318X

Publisher: John Wiley and Sons Inc.

URL: https://doi.org/10.1111/jfr3.70118

DOI: 10.1111/jfr3.70118

Data Access Statement: The datasets generated and/or analysed during the current study are available from the corresponding author on reasonable request.


Altmetrics

Altmetrics provided by Altmetric


Funding

Funder referenceFunder name
NE/S007512/1Natural Environment Research Council (NERC)

Share