Revealing the dynamics and multidimensional resilience of rainstorm-flood cascade disasters in mountain valley cities: An interpretable machine learning case study from Southwestern China

Key Points

• Resilience is critical to managing flood disasters effectively in mountain valley cities, as revealed by the analysis.
• The study identifies machine learning as a key tool for interpreting complex disaster dynamics across various locations.
• Assessment used interpretable machine learning algorithms to predict and analyze flood risks in specific flood-prone areas.
• Understanding these dynamics may enable better preparedness measures and response strategies for future floods.