Constructing a risk probability model for resilience construction in mountainous communities in Southwest China based on field theory

Resilience provides a new way for communities to become more disaster-resistant and better able to recover. This study proposes a resilience-building risk framework for mountainous communities in Southwest China based on field theory and the baseline resilience indicator for communities. It calculated the resilience-building risk probability using Bayesian network modeling based on ten communities in the mountainous regions of Southwest China. The study obtained data from multiple sources, calculated conditional probabilities among factors and finally explored the risk of community resilience construction and its influencing factors based on Bayesian networks in three aspects: forward propagation, backward diagnosis, and significance analysis. We found that 1) the overall risk level of community resilience building in mountainous areas of Southwest China is low, only 26.8%; 2) among the sub resilience fields, the organizational field has the lowest probability of risk (14.2%), and the economic field has the highest probability of risk (42.8%); 3) when the overall resilience level decreases, the economic field changes the most, with the most significant magnitude of change in the level of income; and 4) improving residents' information accessibility and enhanced training exercises can reduce the overall resilience risk probability to a greater extent. This study can help local communities evaluate the level of resilience construction correctly, clarify the focus of resilience construction efforts, and provide a reference for resilience-building assessment efforts in other regions.