Time-Series Analysis of Urban Precipitation and Waterlogging Risks in Railway Culvert Areas: A Case Study of Zhengzhou

Urban flooding has become an increasingly pressing issue under the combined influeces of climate change and urbanization. This study focues on Urban flood in Zhengzhou, a city as major transportation hub in China, where railway culverts represent critical infrastructure prone to waterlogging during extreme storm events. Utilizing ten years(2015-2024) of hourly precipitation data obtained from NASA, this study conducts a comprehensive time-series analysis to explore seasonal and interannual trends in rainfall intensity and frequency. A disaster model was developed to simulate flood formation processes in culvert areas, integrateing precipitation, land use, drainage, and terrain data. The model identifies a consistent temporal pattern: in most flood events, waterlogging occurred when 30–50% of the total rainfall duration had elapsed. The well-known July 20, 2021 (“7·20”) event was found to be an outlier, but overall, the frequency of extreme precipitation has shown signs of increase in recent years. These findings offer a new perspective for characterizing extreme rainfall and provide reference values for early warning systems and urban flood resilience planning.