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Storm waves and rising sea levels pose significant threats to low-lying coastal areas, particularly sandy beaches, which are especially vulnerable. The research on the long-time-scale changes in sandy coasts, especially the identification of tipping points in the shoreline-retreat rate, is limited. Vung Tau beach, characterized by its low terrain and rapid tourism-driven economic growth, was selected as a typical study area to quantify the shoreline retreat throughout the 21st century under various sea-level rise (SLR) scenarios, and to identify the existence of tipping points by investigating the projected annual change in shoreline retreat (m/yr). This study employs the Probabilistic Coastline Recession (PCR) model, a physics-based tool specifically designed for long-term coastline change assessments. The results indicate that shoreline retreat accelerates over time, particularly after a tipping point is reached around 2050 in the SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios. Under the SSP5-8.5 scenario, the median retreat distance is projected to increase from 19 m in 2050 to 89 m by 2100, nearly a fourfold rise. In comparison, the retreat distances are smaller under the SSP1-2.6 and SSP2-4.5 scenarios, but the same accelerating trend is observed beyond 2050. These findings highlight the growing risks associated with sea-level rise, especially the rapid increase in exceedance probabilities for retreat distances by the end of the century. By 2100, the probability of losing the entire beach at Vung Tau is projected to be 22% under SSP5-8.5. The approach of identifying tipping points based on the PCR model presented here can be applied to other sandy coastal regions, providing critical references for timely planning and the implementation of adaptation measures. [ABSTRACT FROM AUTHOR]

Urbanization and climate change are the critical challenges in the 21st century. Flooding by extreme weather events and human activities can lead to catastrophic impacts in fast-urbanizing areas. However, high uncertainty in climate change and future urban growth limit the ability of cities to adapt to flood risk. This study presents a multi-scenario risk assessment method that couples the future land use simulation model (FLUS) and floodplain inundation model (LISFLOOD-FP) to simulate and evaluate the impacts of future urban growth scenarios with flooding under climate change (two representative concentration pathways (RCPs 2.6 and 8.5)). By taking Shanghai coastal city as an example, we then quantify the role of urban planning policies in future urban development to compare urban development under multiple policy scenarios (Business as usual, BU; Growth as planned, GP; Growth as eco-constraints, GE). Geospatial databases related to anthropogenic flood protection facilities, land subsidence, and storm surge are developed and used as inputs to the LISFLOOD-FP model to estimate flood risk under various urbanization and climate change scenarios. The results show that urban growth under the three scenario models manifests significant differences in expansion trajectories, influenced by key factors such as infrastructure development and policy constraints. Comparing the urban inundation results for the RCP2.6 and RCP8.5 scenarios, the urban inundation area under the GE scenario is less than that under the BU scenario, but more than that under the GP scenario. We also find that urban will tend to expand to areas vulnerable to floods under the restriction of ecological environment protection. The increasing flood risk information determined by the coupling model helps to understand the spatial distribution of future flood-prone urban areas and promote the re-formulation of urban planning in high-risk locations. [ABSTRACT FROM AUTHOR]