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Shoreline changes are among the major effects of sea level rise, affecting more than 10% of the global population living in low-lying coastal areas. Coastal dynamics pose a significant risk to human health, biodiversity, and infrastructure resilience. While peninsulas such as Qatar would be ideal for studying the impact of shoreline retreat, this knowledge remains largely unquantified. This peninsula has witnessed rapid urbanization and large-scale economic and industrial development along its coastlines, making it an effective case study for experimenting with vulnerable eroded zones. To address these challenges, high-resolution remote sensing (RS) and a wind-wave database were used to quantify shoreline evolution along 563 km of Qatar’s coasts over the last 15 years. A machine-learning vector classification algorithm, the Digital Shoreline Analysis System (DSAS) tool, remote-sensing indices, and statistical analysis methods were used to assess land-water interfaces. This geospatial assessment was performed using Pleaides spectral bands (0.5 m) and the DSAS shoreline statistical analysis shows that 32 sites are classified as coastal erosion hotspots, with an EPR exceeding -0.5 ± 0.15 m/yr. The most vulnerable area is the low-lying Al Shamal coast, where two hotspot segments have been identified with alarming retreat rates exceeding − 3 m. The dominant wind directions in these hotspot areas are from the N-NW quadrant, reaching 74% in the winter months. Analysis of ERA5 data shows that during strong wind events, significant wave height (SWH) in these areas can exceed 3 m. This study emphasizes the urgent need to implement Nature-based Solutions (NbS) to enhance coastal resilience in eroded hotspot areas amid global climate change.
Hzami et al. (Fri,) studied this question.