Abstract

Abstract Punctuality monitoring and analysis aims to optimize resource allocation for enhancing rail traffic performance and quality. Adverse weather conditions, particularly heavy precipitation events, are recognized as significant drivers of delays and reduced punctuality of the rail system. This study addresses two key research questions using HSR as an example – what is the impact of rainfall on HSR’s delay, and to what extent are HSR vulnerable to rainstorms. The data for the study were collected from the HSR on the major lines of eastern China in the rainy season of 2015-2017 which lasted from May to October. High-resolution precipitation data is integrated with non-spatial HSR operational data using GIS to create composite grids covering buffer zones around HSR lines. These grids match the spatial scale of historical hourly precipitation data and enable regression analyses to assess how precipitation affects HSR operations. The results indicate that extreme rainfall significantly contributes to delays and reduced punctuality, with varying impacts observed across different HSR lines. Specifically, daily areal precipitation significantly delays services on the Hangzhou-Shenzhen and Nanjing-Hangzhou HSR lines. Rainfall intensity has a more pronounced impact on delay services of the Beijing-Shanghai HSR, while extreme precipitation most frequently affects the Shanghai-Nanjing and Jinhua-Wenzhou HSR lines. The case analysis enhances understanding of HSR vulnerability to heavy rainfall conditions and recommends regional adaptation strategies to manage climate-related uncertainties.

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