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Urban Flash Flood Management in Arid and Semi-Arid Regions under Climate Change " Modelling Approaches and Adaptation Strategies – A State-of-the-Art Review"

Year: 2025
Type: article
Abstract: Urban flash floods in arid and semi-arid regions are emerging as a critical constraint on sustainable urbanisation, as rapid land-use change interacts with highly responsive dryland hydrology and a warming climate that amplifies short-duration extreme rainfall. This paper presents a structured state-of-the-art review of urban flash-flood management in dry climates, with a dual focus on modelling approaches and adaptation strategies under climate change. The review synthesises 1D, 2D and 1D–2D hydrologic–hydraulic applications based on HEC-RAS, MIKE and SWMM, alongside RS–GIS–MCDA and hybrid hydro–machine-learning frameworks used for hazard and susceptibility mapping in data-scarce wadis and cities. Particular attention is given to the role of multi-resolution DEMs, multi-source rainfall estimates, remote sensing and IoT-enabled monitoring in compensating for sparse hydrometric networks and incomplete drainage inventories. On the adaptation side, the paper critically assesses portfolios of structural measures in wadis and urban channels, urban drainage upgrades, green infrastructure and low-impact development, and non-structural instruments such as zoning, early warning and risk-governance reforms. By organising more than two decades of work into five analytical pillars—hazard mapping, hydrologic–hydraulic modelling, urban drainage and dual drainage, adaptation strategies, and monitoring/early warning—the review identifies common limitations, transferable good practice and key research gaps. It argues for integrated, climate-informed decision-support systems that fuse models, remote sensing, machine learning and IoT, and for embedding these tools within proactive planning and governance to achieve genuinely climate-resilient urban flash-flood management in arid and semi-arid regions.
Language: English
Open Access status: green
OpenAlex ID: W7117306290
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