Urban flood hazard mapping in Dubai’s Hyper-Arid environment using a 2D HEC-RAS and GIS–MCDA–AHP integrated framework

In April 2024, Dubai recorded 118.9 mm of rain in 24 h during a multi-day storm (April 15–17), overwhelming drainage systems across a hyper-arid, densely built landscape. We map urban flood hazard by coupling a 2D HEC-RAS rain-on-grid simulation with a GIS-based MCDA weighted by AHP. Six drivers elevation, slope, aspect, land use/land cover, simulated flood depth, and surface flow velocity are standardized via functional rescaling and fused into a Hydrological Hazard Index (HHI). Inputs are harmonized at 12.5 m (ALOS PALSAR), while Landsat-9 supports LULC mapping and NDWI-based post-event validation (IoU > 0.86; ĸ = 0.81), confirming high model accuracy. Approximately 43 % of Dubai’s urban area falls within the High Hazard class, with localized flood depths reaching 2.5–3.0 m and peak surface velocities exceeding 2.5–3.0 m/s, particularly in low-lying underpasses and constrained flow corridors. High-hazard polygons (Classes 4/5) cluster over flat, impervious districts, offering actionable targets for detention storage, inlet retrofits, tidal backflow control at outfalls, and blue–green corridor integration. The results demonstrate that incorporating dynamic hydraulic parameters is essential for future urban planning and drainage design in Dubai. The combined 2D HEC-RAS and GIS–MCDA–AHP framework provides a reliable, transferable method for flood hazard assessment in hyper-arid cities. Future work should integrate real-time hydrological sensors, non-stationary climate-adjusted rainfall inputs, and socio-economic exposure layers to progress from hazard mapping to full urban flood risk assessment, supporting climate-resilient infrastructure and long-term adaptation planning.