Development of a new framework for assessing beach loss risk under future climate and population scenarios

The loss of sandy beaches due to coastal erosion can affect coastal communities by reducing disaster prevention functions, tourism revenue, and ecosystem services. This study developed a new framework for assessing beach loss risk and applied it to 59 beach zones along the mainland Chinese coast. Using a multi-criteria decision analysis (MCDA) approach, fifteen indicators were selected to calculate hazard, vulnerability, and exposure indices and to construct an integrated risk index. Two commonly used objective weighting methods, principal component analysis (PCA) and the entropy weight method (EWM), were employed to derive indicator weights and compare the resulting risk rankings. High-risk beach zones were concentrated primarily along the southeast coast, where higher wave heights, stronger storm surges, and lower seawall coverage highlight the protective role of beaches. Additional high-risk zones were scattered along the northern coast, where more intensive urban development and fisheries increased exposure. Spearman's rank correlation analysis showed that the PCA-derived risk rankings were more consistent with historical economic-loss rankings (ρ = 0.70) than the EWM-derived rankings (ρ = 0.57) under the present dataset and evaluation criterion. Under the adopted future climate and population scenarios, beach loss risk increased by up to 33% across the study area. Sea level rise (SLR) was projected to increase risk by approximately 10% in most beach zones, while the impacts of future wave height changes and shoreline retreat exhibit notable spatial variation. Population change had a limited effect on overall risk due to continued coastward migration; however, population-related risk decreased by up to 7% in northern beach zones because of a projected shift in migration from the northern to southern coasts. The developed framework in this study provides an adaptable approach for comprehensively assessing beach loss risk in other coastal regions where region-specific indicators and datasets are available. It also offers a basis for incorporating future environmental and socioeconomic changes into coastal risk assessments.