A Multi-Scenario Flood Risk Reasoning Method for Critical Urban Facilities Based on Facility–Scenario Risk Chains

Multi-scenario flood simulation supports urban flood-risk assessment, but scenario-specific outputs are difficult to use to identify facility-level risk evolution and critical risk conditions. This study proposes a multi-scenario flood risk reasoning method for critical urban facilities based on facility–scenario risk chains (FSRCs). The method constructs internally comparable rainfall–inundation scenario subsets, anchors each facility to a fixed triangular mesh cell, and organizes inundation depths and depth-based risk states into ordered chains. Boundary-crossing reasoning is then used to derive scenario-context-dependent critical rainfall threshold (CRT) estimates and ordered risk-state transition sequences. The method was evaluated in the Hexi drainage area of Nanjing, China, using 184 rainfall–inundation scenarios and 241 critical facilities. The results show that accumulated rainfall alone is insufficient for consistent risk ordering across different rainfall durations, while facility risk states vary across comparable rainfall-ordered scenario sequences. Representative facilities exhibited distinct CRT positions and transition intervals. Sensitivity analysis showed that CRT estimates varied with scenario spacing, while a computational consistency assessment confirmed the reproducibility of boundary-crossing results. The proposed method transforms discrete flood simulation outputs into structured object-level risk knowledge, supporting facility-level risk screening, risk-state comparison, and subsequent knowledge-driven applications.