Impact of urban waterlogging on fire service accessibility under extreme rainfall events

Extreme rainfall events associated with climate change exacerbate urban waterlogging, posing significant threats to fire services. This study constructs a hierarchical evaluation model to quantify the impact of such climate-driven compound events on fire service accessibility. Waterlogging avoidance areas were designated, and rescue times were then simulated using real-time traffic data. The model was applied and validated under a 100-year rainstorm scenario in Longhua District, China. A total of 9,094 points of interest and 70 fire stations were used to represent fire service demand points and supply points, respectively. Travel times and driving distances of fire vehicles were analyzed with and without waterlogging avoidance constraints under both congested and non-congested traffic conditions. The results identify 16 vehicle-restricted zones that delay responses to approximately 4% of demand points, with time delays escalating by 153% (661 s) during congestion and 143% (441 s) under non-congested conditions, alongside 2.7 km average route extensions. Under non-congested conditions, degradation severity varied: 64.5% mild, 15.2% moderate, 11.0% severe, and 9.3% catastrophic. During congestion, the proportion of mild cases decreased while moderate cases increased. The model provides critical support for optimizing fire-service resource allocation and prioritizing infrastructure upgrades.