Modeling Sea Level Rise Impacts on Western Arabian Gulf Cities Using Nighttime Lights and LULC-Driven Cellular Automata

Sea-level rise (SLR) poses a major global risk to the populated coastal zones, with recent assessments indicating significant acceleration due to climate change. In this study, we integrate nighttime light (NTL) data and Land Use and Land Cover (LULC) modeling within a cellular automata framework to project SLR impacts on six major coastal cities of Saudi Arabia’s Eastern Province along the Arabian Gulf. Historical sea-level records (1979–2020) reveal an annual mean rise of 7.9 mm, corroborating global trends. To forecast future inundation, we applied a GIS-based “bathtub” approach using sea-level scenarios from the Intergovernmental Panel on Climate Change Sixth Assessment Report (IPCC AR6) and digital elevation models. Concurrently, LULC transitions for 1973–2020 were derived from Landsat images and extrapolated to future time slices (2070, 2100, and 2130) via cellular automata-based approach. Nighttime light data served as a proxy for economic and urban activity, allowing refined mapping of vulnerable coastal development zones. Results show spatially heterogeneous, yet markedly increasing, inundation exposure by mid- to late-century. Jubail, Qatif, and Ras Tanura emerge as high-risk areas, with up to 40% or more of coastal lands threatened under the worst-case SLR scenario by 2130. Rapidly growing built-up areas and reclaimed lands in Dammam and Khobar also face significant flood hazard. These findings highlight the need for proactive planning and adaptation measures to reduce the economic and ecological impacts of rising seas in the Arabian Gulf region.