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<p>Urban design storm analysis is the foundational determinant of the hydraulic efficacy and socio-economic viability of drainage infrastructure. This study establishes a rigorous framework for storm characterization in Nanjing, China, utilizing high-resolution rainfall series (1988–2015) from seven stations. We evaluate the sensitivity of Pearson Type III (P-III) distribution modeling to four parameter estimation techniques: curve-fitting, double weight function (DWF), L-moments, and probability weighted moments (PWM), alongside a comparative assessment of annual maximum versus annual multiple sampling protocols. Statistical diagnoses reveal that while sampling divergence is attenuated at high return periods, the annual multiple method provides a superior representation of the frequent, lower-magnitude events critical for urban resilience. In parameterization, the DWF method demonstrated optimal unbiasedness and goodness-of-fit, whereas L-moments exhibited the highest structural robustness against outliers. For temporal discretization, fuzzy pattern recognition identified three dominant regional hyetotypes: single-peak, uniform, and multi-peak. To mitigate the limitations of individual synthetic patterns, we propose an integrated multi-scale construction framework: the Chicago method for medium-duration (180–1440&#xa0;min) parametric standardization; the Pilgrim &amp; Cordery method for preserving short-duration (3-h) stochastic peak complexities; and same-frequency scaling for 24-h watershed-scale flood control. This hybridized approach ensures a continuous, scale-appropriate representation of storm dynamics. These findings advance the methodological rigor of urban flood risk assessments and provide a scientifically substantiated technical standard for climate-adaptive municipal engineering and disaster mitigation strategies.</p>

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Analysis of urban design rainstorm patterns based on parameter estimation and model approaches

  • 期刊论文

  • 发表日期：

    2026年4月1日

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  • Jun Zhao,
  • Lin Yang,
  • Long Zhu,
  • Cuishan Liu,
  • Zhenxin Bao,
  • Min Liu,
  • Qiyan Huang,
  • Sadashiv Chaturvedi,
  • Yu Liu,
  • Yuhan Zhao

摘要

Urban design storm analysis is the foundational determinant of the hydraulic efficacy and socio-economic viability of drainage infrastructure. This study establishes a rigorous framework for storm characterization in Nanjing, China, utilizing high-resolution rainfall series (1988–2015) from seven stations. We evaluate the sensitivity of Pearson Type III (P-III) distribution modeling to four parameter estimation techniques: curve-fitting, double weight function (DWF), L-moments, and probability weighted moments (PWM), alongside a comparative assessment of annual maximum versus annual multiple sampling protocols. Statistical diagnoses reveal that while sampling divergence is attenuated at high return periods, the annual multiple method provides a superior representation of the frequent, lower-magnitude events critical for urban resilience. In parameterization, the DWF method demonstrated optimal unbiasedness and goodness-of-fit, whereas L-moments exhibited the highest structural robustness against outliers. For temporal discretization, fuzzy pattern recognition identified three dominant regional hyetotypes: single-peak, uniform, and multi-peak. To mitigate the limitations of individual synthetic patterns, we propose an integrated multi-scale construction framework: the Chicago method for medium-duration (180–1440 min) parametric standardization; the Pilgrim & Cordery method for preserving short-duration (3-h) stochastic peak complexities; and same-frequency scaling for 24-h watershed-scale flood control. This hybridized approach ensures a continuous, scale-appropriate representation of storm dynamics. These findings advance the methodological rigor of urban flood risk assessments and provide a scientifically substantiated technical standard for climate-adaptive municipal engineering and disaster mitigation strategies.