Stage-Specific Metro Entry Ridership Responses to Frequent Light-to-Moderate Rainfall Across Station Ridership-Rhythm Types: Evidence from Hangzhou, China

Frequent light-to-moderate rainfall may influence metro demand differently across rainfall stages and station ridership rhythms. Using automatic fare collection data from 80 Hangzhou Metro stations and station-matched hourly meteorological observations, this study examines weekday entry-ridership associations with rainfall onset, continuation, and the first post-rain hour. Three station ridership-rhythm types were identified from non-rain weekday entry–exit profiles: destination-oriented, balanced bidirectional, and origin-oriented. A Bayesian hierarchical negative binomial model estimated stage-specific associations while accounting for station-hour baseline ridership, hourly temperature, peak periods, and station- and date-level heterogeneity. During off-peak periods, rainfall onset and continuation were associated with 4.95% and 6.82% reductions in expected entry ridership at balanced bidirectional stations. Continuation associations were more negative in the primary model, but this difference was substantially attenuated after accounting for cumulative precipitation and elapsed episode duration. Origin-oriented stations generally showed more negative onset and continuation associations, while negative first-post-rain associations were observed across all three station types. These findings demonstrate that routine rainfall responses vary across both event stages and station ridership rhythms, supporting more stage-specific and station-sensitive passenger-flow monitoring.

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Publication Details

Journal
Systems
Published
2026-09-04
DOI
https://doi.org/10.3390/systems14091097
Primary Topic
Transportation Planning and Optimization
Type
article
Field-Weighted Citation Impact
0.00

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article

Stage-Specific Metro Entry Ridership Responses to Frequent Light-to-Moderate Rainfall Across Station Ridership-Rhythm Types: Evidence from Hangzhou, China

Yifan Yue, Xinwei Ma, Jun Chen, Yang Yu et al.
Systems
Transportation Planning and Optimization
article

Stage-Specific Metro Entry Ridership Responses to Frequent Light-to-Moderate Rainfall Across Station Ridership-Rhythm Types: Evidence from Hangzhou, China

Yifan Yue, Xinwei Ma, Jun Chen, Yang Yu, Wei Wang, Yang Li
article en

Abstract

Frequent light-to-moderate rainfall may influence metro demand differently across rainfall stages and station ridership rhythms. Using automatic fare collection data from 80 Hangzhou Metro stations and station-matched hourly meteorological observations, this study examines weekday entry-ridership associations with rainfall onset, continuation, and the first post-rain hour. Three station ridership-rhythm types were identified from non-rain weekday entry–exit profiles: destination-oriented, balanced bidirectional, and origin-oriented. A Bayesian hierarchical negative binomial model estimated stage-specific associations while accounting for station-hour baseline ridership, hourly temperature, peak periods, and station- and date-level heterogeneity. During off-peak periods, rainfall onset and continuation were associated with 4.95% and 6.82% reductions in expected entry ridership at balanced bidirectional stations. Continuation associations were more negative in the primary model, but this difference was substantially attenuated after accounting for cumulative precipitation and elapsed episode duration. Origin-oriented stations generally showed more negative onset and continuation associations, while negative first-post-rain associations were observed across all three station types. These findings demonstrate that routine rainfall responses vary across both event stages and station ridership rhythms, supporting more stage-specific and station-sensitive passenger-flow monitoring.

SystemsVol. 14(9)
City University of Hong Kong (HK), Hebei University of Technology (CN), Suzhou Polytechnic Institute of Agriculture (CN), Southeast University (BD), Ministry of Transport (CN), Southeast University (CN)
National Key Research and Development Program of China
Climate action
Openalex Percentile: Top 7%
Transportation Planning and Optimization
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