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Disaster management often serves as the primary defense against ecological damage and threats to social well-being resulting from natural disasters. However, the quantitative research on unified disaster risk management capacity assessment has not been scrutinized. Based on the time series structure, this study proposes a novel framework and risk management contribution models for exploiting a community risk management capacity to debris flows (CRMCD) assessment system. A comprehensively improved method was utilized for indicator selection by combining R hierarchical clustering (RHC) and coefficient of variation methods (CV). Entropy-weighted grey correlation analysis (EGCA) and geographic information system (GIS) methods are employed to assign weights and visualize the disaster management capacity of research areas. Three risk management contribution models are constructed according to the criterion layers defined by CRMCD: prevention-oriented, emergency-oriented, and recovery-oriented. Furthermore, a questionnaire was designed by introducing multi-ethnic cultural scenarios to assess public risk awareness, avoidance behaviors, and management demands. A total of 3,060 survey samples were conducted among ethnic minority communities in Sichuan that issued debris flow disaster declarations in 2022. Social welfare and public satisfaction were examined to validate the applicability of the CRMCD assessment system and risk management contribution model. The results identified key indices contributing to enhancing CRMCD: The proportion of financial investment in disaster prevention and public security, Professional skills diversity of emergency responders, and Installed power capacity. The multinomial logistic regression analysis revealed public preference for the prevention-oriented type in the risk management contribution model, and interviewees demonstrated a more positive response regarding motivation and participation in disaster prevention under this model. Kruskal-Wallis H significance analysis highlighted that ethnic minorities and elderly populations exhibited lower levels of disaster knowledge reserves, avoidance awareness, and propensity to purchase disaster insurance. Unexpectedly, respondents with higher household income and education levels paid less attention to seeking assistance from professional community organizations. Disaster early warning emerged as a priority for respondents interested in strengthening community disaster management initiatives. Overall, this study outlines a systematic methodology to establish an objective index system and summarize management models, which provide breakthroughs in developing participatory disaster management frameworks and resilience communities.
Chen et al. (Wed,) studied this question.