Enhancing Urban Flood Resilience Through Emergency Shelter Assessment: A Coupled InfoWorks ICM–NetLogo Simulation and Spatial Evaluation Framework
Year: 2026
Type: article
Abstract: With increasing extreme rainfall, assessing whether emergency shelters remain accessible and functional during flood-constrained evacuation is essential for enhancing urban flood resilience. However, flood simulation, evacuation behavior, shelter suitability, and spatial accessibility are often examined separately, leaving the relationship between shelter reception performance and pre-disaster spatial support insufficiently clarified. This study evaluates emergency-shelter evacuation-support capacity in the Qingdao West Coast New Area under a 100-year, 24 h design rainstorm scenario. InfoWorks ICM was used to simulate two-dimensional surface inundation without explicitly resolving the sewer-pipe network, and hourly inundation depths were coupled with NetLogo to model evacuee movement, road passability, and shelter reception performance. An entropy-weighted TOPSIS model was applied within the 800 m road-network service areas of 20 shelters, comprising the 10 highest- and 10 lowest-arrival shelters. Results show that widespread shallow inundation coexisted with localized deep-water accumulation, and shelter reception performance varied substantially. Higher simulated arrivals did not necessarily indicate stronger evacuation-support capacity. Within the selected sample, parks and green spaces and intersection density received relatively higher weights. Four representative shelter cases were identified—core load-bearing, high-pressure risk, potential improvement, and inefficient vulnerable—providing a process-based basis for emergency shelter assessment and urban flood resilience enhancement.
Source: Sustainability
DOI: 10.3390/su18178878
Institution: Shandong University of Science and Technology
Language: English
Subfield: Global and Planetary Change
Field: Environmental Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,896
OpenAlex ID: W7204928725