Bayesian Projections of Shoreline Retreat Under Climate Change Along the Arid Coast of Duba, Saudi Arabia

Coastal zones in arid regions are particularly vulnerable to climate change because of their limited sediment supply and high sensitivity to marine and aeolian forces. This study provides probabilistic projections of coastal evolution for a 130 km segment of the Duba shoreline, Saudi Arabia, a rapidly developing region that includes the NEOM mega-project. An integrated modeling framework was developed by combining a four-decade (1985–2024) diachronic analysis of shoreline evolution from Landsat imagery with a cascade of numerical models. Specifically, climate projections from CMIP6 (under SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios) were dynamically downscaled using the regional climate models COSMO-CLM and RegCM, which provided boundary conditions for the SWAN hydrodynamic model to simulate the wave dynamics. The SWAN outputs were then used to force the Delft3D morphodynamic model to project future shoreline evolution. A Bayesian framework was applied to systematically quantify and integrate the uncertainties across all modeling steps, enabling robust probabilistic forecasts. Results indicate an accelerated trend of shoreline retreat, with mean Net Shoreline Movement (NSM) by 2100 ranging from −8.1 m under the low-emission SSP1-2.6 scenario to a critical −25.6 m under the high-emission SSP5-8.5 scenario, with 95% confidence intervals reaching −47.9 m. This erosion is mainly driven by a projected relative sea-level rise of up to 48.3 cm (±15.8 cm) and an increase in significant wave height of up to 40% (mean of 1.95 m). By delivering probabilistic rather than deterministic results, this study provides a solid scientific basis to guide sustainable coastal management, inform the design of risk-sensitive infrastructure, and support the development of climate-resilient adaptation strategies in one of the world’s most rapidly transforming coastal regions.