Impact of Flood Progression on Evacuation Efficiency in Underground Metro Stations: A Proposed Macro-Level Analysis Using a Node-and-Link Simulation Approach

Abstract

Underground subway stations are highly vulnerable to flooding due to their below-grade configuration, multiple interconnected levels, and reliance on a limited number of vertical access points, yet the extent to which flood progression affects evacuation performance remains insufficiently quantified. This study evaluates the impact of flooding on evacuation performance in an actual four-level transfer station in Seoul, South Korea, by coupling a hydraulic inundation model with a node–link-based evacuation simulation. Water depth and flow velocity obtained from an EPA SWMM-based inundation simulation were converted into walking-speed reduction factors and applied to link weights in a Dijkstra’s algorithm-based evacuation routing model, together with crowd-congestion-based speed reduction. Evacuation performance was compared across three scenarios: a non-flooded baseline and evacuation initiated under 300 s and 600 s flood conditions. The maximum evacuation time increased from 453 s under the non-flooded condition to 523 s and 596 s under the 300 s and 600 s flood conditions, respectively, corresponding to increases of approximately 15.5% and 31.6%. Tracing the route of the last evacuated group showed that this delay arose not from a change in route length—the governing route measured approximately 78 m in all three cases—but from a congestion-driven shift in which platform side produced the binding delay, as evacuee flow was redistributed away from the flooded exit toward the unaffected side. These findings indicate that the onset of flooding measurably increases evacuation time by altering the spatial distribution of congestion rather than the route itself, and that evacuation guidance based on a fixed, pre-computed route cannot fully offset this time-dependent penalty, underscoring the need for real-time, flood-adaptive evacuation routing in underground station environments.