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<p>Under rainstorm conditions, urban roads are expected to fulfill the dual functions of transportation and drainage. To effectively reduce the impact of using roads as drainage conveyances, it is imperative to optimize the overloaded road drainage sections (ORDS). In this study, rainstorm scenarios with return periods of 20, 100, and 500 years were established, and a novel optimization framework for ORDS was proposed. This framework integrates three key components: the identification of ORDS in urban areas through a dual-drainage Storm Water Management Model (SWMM) coupled with ArcGIS; a multi-dimensional evaluation of these sections considering risk, economic importance, and hydrological connectivity; and the classification of retrofitting priorities to inform corresponding strategies. The upstream area of the Shiwuli River in Hefei City was selected as a case study to analyze road drainage overload conditions and scoring under the three rainstorm scenarios. The effects of optimizing the top-priority ORDS were preliminarily simulated by adjusting the dual-drainage SWMM model. The results indicate that the existing road system is most sensitive to the 100-year return period rainstorm, under which optimizing top-priority ORDS yields higher overall efficacy. Furthermore, most ORDS in the study area carry important transportation functions and exhibit distinct spatial distribution characteristics. The systematic optimization framework proposed in this study has the potential for broader application, enabling decision-makers to more accurately identify ORDS with greater optimization potential. The outcomes also provide a more comprehensive basis for alleviating drainage pressure on urban roads.</p>

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Roads in Rainstorms: A Systematic Optimization Framework for Overloaded Road Drainage Sections

  • 期刊论文

  • 发表日期：

    2026年4月2日

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  • Buyun Fang,
  • Jinjin Gu

摘要

Under rainstorm conditions, urban roads are expected to fulfill the dual functions of transportation and drainage. To effectively reduce the impact of using roads as drainage conveyances, it is imperative to optimize the overloaded road drainage sections (ORDS). In this study, rainstorm scenarios with return periods of 20, 100, and 500 years were established, and a novel optimization framework for ORDS was proposed. This framework integrates three key components: the identification of ORDS in urban areas through a dual-drainage Storm Water Management Model (SWMM) coupled with ArcGIS; a multi-dimensional evaluation of these sections considering risk, economic importance, and hydrological connectivity; and the classification of retrofitting priorities to inform corresponding strategies. The upstream area of the Shiwuli River in Hefei City was selected as a case study to analyze road drainage overload conditions and scoring under the three rainstorm scenarios. The effects of optimizing the top-priority ORDS were preliminarily simulated by adjusting the dual-drainage SWMM model. The results indicate that the existing road system is most sensitive to the 100-year return period rainstorm, under which optimizing top-priority ORDS yields higher overall efficacy. Furthermore, most ORDS in the study area carry important transportation functions and exhibit distinct spatial distribution characteristics. The systematic optimization framework proposed in this study has the potential for broader application, enabling decision-makers to more accurately identify ORDS with greater optimization potential. The outcomes also provide a more comprehensive basis for alleviating drainage pressure on urban roads.