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Lookup NU author(s): Fulvio Lopane, Professor Richard DawsonORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2026 The Author(s). Journal of Flood Risk Management published by Chartered Institution of Water and Environmental Management and John Wiley & Sons Ltd. Infrastructure systems provide crucial services to human settlements. Extreme weather events, especially flooding, can disrupt these vital services. Temporary and demountable flood protections (TDFPs) are increasingly used to protect infrastructure assets and provide resilience. Budget constraints mean that TDFP are typically deployed to multiple sites from a single warehouse. Identifying optimal locations to maximise coverage and minimise costs is a complex spatial problem not yet tackled in the literature. To address this, a Spatial Resource Allocation Optimisation (SRAO) framework, using a genetic algorithm (GA), has been developed. The SRAO framework is applied to a case study in the Humber Estuary (UK) where 133 strategic infrastructure assets serve over 400,000 people in the floodplain. Eight scenarios assess how cost, TDFP availability, transport and asset prioritisation for protection influence warehouse size and sites. The SRAO identifies optimal strategies that, relative to other strategies, reduce annual costs by 40%–50% and deployment times by 60%–70%. Furthermore, 8 ‘hotspot’ sites appear in over 60% of optimal solutions; these can be considered robust to model uncertainties and scenario assumptions, providing decision-makers with locations performing well under varied conditions. The methodology benefits local authorities, infrastructure operators and emergency management agencies, reducing costs and improving resilience for communities.
Author(s): Lopane FD, Dawson RJ
Publication type: Article
Publication status: Published
Journal: Journal of Flood Risk Management
Year: 2026
Volume: 19
Issue: 1
Print publication date: 01/03/2026
Online publication date: 28/01/2026
Acceptance date: 08/01/2026
Date deposited: 09/02/2026
ISSN (electronic): 1753-318X
Publisher: John Wiley and Sons Inc.
URL: https://doi.org/10.1111/jfr3.70182
DOI: 10.1111/jfr3.70182
Data Access Statement: Python code for this work is available on GitHub at github.com/fdlopane/SRAO_HumberEstuary_P3
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