Marine Flood Hazard Modelling in Salé, Morocco: Current Risks and Future Scenarios

Coastal flooding poses a major threat to urbanized coastlines, where extreme marine forcing interacts with complex coastal morphology and concentrated human activities. This study investigates storm-induced marine flooding along the Sidi Moussa-Salé coastline, Morocco, using the two-dimensional Iber hydrodynamic model. Simulations were conducted for the January 2014 and February 2017 storm events using atmospheric, wave, water-level, topographic, and bathymetric data. The results reveal a spatially heterogeneous response, with the 2014 event producing a maximum inland inundation extent of approximately 0.20 km and a flooded area of 0.20 km2, compared with 0.15 km and 0.10 km2, respectively, in 2017. The simulated inundation patterns highlight the influence of coastal morphology, localized depressions, and preferential flow pathways on flood propagation. Spatial exposure mapping indicates an overlap between flood-prone areas and coastal roads, residential and commercial zones, recreational facilities, and other public assets. Field observations provide qualitative contextual evidence of storm-related impacts, although the absence of surveyed flood boundaries and measured water levels limits quantitative model validation. Future simulations, based on the February 2017 storm forcing and prescribed sea-level-rise increments, indicate an expanded inundation footprint under the examined scenarios. Under RCP8.5-2100, the maximum inland extent reaches 0.42 km and the flooded area 0.32 km2, compared with 0.15 km and 0.10 km2 under the 2017 baseline. These results constitute conditional sensitivity assessments rather than deterministic forecasts, given the uncertainties in model inputs and the omission of future changes in storm forcing and coastal morphology. The study provides a site-specific basis for identifying potentially exposed coastal sectors and supporting hazard-informed coastal planning, while highlighting the need for improved observational validation and systematic uncertainty assessment.