A Copula-XAI framework for assessing compound typhoon disaster-chain risks and driving mechanisms in coastal mountainous cities: Evidence from Fujian, China

Study region
Fujian Province, China.

Study focus
To address the limited quantitative understanding of compound disaster chain risks in highly urbanized mountainous coastal regions, this study develops an integrated framework combining a Copula-based joint probability model with explainable machine learning (XGBoost–SHAP). Using Fujian Province as a case study, we identify high-risk areas, quantify exposure inequality, and analyze key driving factors, nonlinear thresholds, and transition mechanisms across typical typhoon disaster chains.

New insights for the region
High-risk areas of typhoon disaster chains in Fujian Province show a clear spatial contrast, with single disaster chains being widely distributed and compound disaster chains strongly clustered. Although compound-chain high-risk areas account for only 0.8 % of the provincial area, they concentrate 12.6 % of the population and 14.1 % of economic activity. Correspondingly, population and GDP exposure lift values reach 16.3 and 18.2, respectively, which are substantially higher than those of single disaster chains, indicating pronounced exposure inequality. Overall, typhoon disaster chain risks follow a “natural triggering–social amplification” pathway and exhibit nonlinear threshold behavior. ... mehrTransitions from single to compound disaster chains are governed by two dominant pathways: socioeconomic-driven and naturally driven transitions. These findings support fine-scale identification and differentiated management of compound disaster chain risks in mountainous coastal cities.