Quantitative assessment of coastal geomorphological and ecological damage risks: a case study of Sheyang coast

As critical zones of land–sea interaction, coastal areas serve as core regions for dense populations, economic development, and sustainable social progress. However, coastal erosion poses a significant challenge for China. Current risk management practices often rely on subjective judgment and lack standardized, quantifiable frameworks that integrate both subjective and objective perspectives. This study aims to develop a comprehensive classification framework for coastal degradation risk. By integrating the Analytic Hierarchy Process (AHP) and Criteria Importance Through Intercriteria Correlation (CRITIC) method using game theory, this framework effectively combines expert insights with empirical evidence. Six key indicators were collected for Sheyang coast over the past two decades, including shoreline change rate, nearshore mean wave height, nearshore mean current velocity, salt marsh vegetation area, mudflat area, and coastal slope. Based on the combined weights, coastal damage risk values were calculated. By leveraging the cloud model, critical thresholds were systematically identified to differentiate five risk levels—ranging from accretion to severe erosion—through a comprehensive assessment of shoreline siltation, shoreline stability, shoreline erosion accompanied by salt marsh vegetation disappearance, and steep slope formation with near-complete mudflat loss. This approach integrates multi-dimensional coastal parameters to establish a scientific framework for risk classification, enabling precise distinction between gradual sediment accumulation and catastrophic erosive degradation. The study reveals that the hydrodynamic conditions of Sheyang coast has gradually shifted from tide-dominated to wave-dominated, indicating a significant intensification of wave action in the region. The geomorphology evolved from wide tidal flats to steep erosional features, with a marked cumulative effect of coastal degradation, reflected in the escalation of risk level from level 2 to level 5. The proposed framework exhibits notable enhancements in both accuracy and adaptability, offering robust scientific support for targeted coastal zone management strategies. It not only elevates the precision of risk identification across dynamic coastal environments but also advances the methodological frontiers of coastal risk assessment.