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<p>This study investigates compound flooding in the Taipei metropolitan area by examining urban flood events recorded between 2001 and 2024. A multi-source observational dataset—including flood incident records, rainfall measurements, tidal levels, and flood depth sensor data—was utilized to characterize the joint effects of rainfall and tide. A copula-based statistical framework was applied, identifying the Gaussian copula as the optimal model to capture the dependence structure between variables (Spearman ρ =  − 0.433). Using this dependence, dynamic flood thresholds were developed by integrating tidal variations with 1-h and 3-h accumulated rainfall. Evaluation results reveal that compound indicators substantially outperform rainfall-only thresholds, increasing detection rates in Taipei City from 59 to 82.2% for 1-h rainfall and from 72 to 82% for 3-h rainfall. In New Taipei City, the 3-h compound indicator improved detection from 64.6 to 84.3%. These findings underscore the critical role of tidal interaction in urban flood dynamics and demonstrate the potential of copula-based compound indicators for enhancing early warning systems in tide-influenced metropolitan regions.</p>

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Pluvial flood warnings in a tidally influenced basin enhanced by rainfall–tide compound indicators: Taipei case study

  • 期刊论文

  • 发表日期：

    2025年11月20日

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  • Mei-Ying Lin,
  • Wen-Yih Sun,
  • Huei-Syuan Fu,
  • Chih-Hsin Chang,
  • Wei-Bo Chen,
  • Chieh-Ju Wang,
  • Hsuan-Wei Wang,
  • Yi-Chiang Yu,
  • Yen-Wei Li

摘要

This study investigates compound flooding in the Taipei metropolitan area by examining urban flood events recorded between 2001 and 2024. A multi-source observational dataset—including flood incident records, rainfall measurements, tidal levels, and flood depth sensor data—was utilized to characterize the joint effects of rainfall and tide. A copula-based statistical framework was applied, identifying the Gaussian copula as the optimal model to capture the dependence structure between variables (Spearman ρ =  − 0.433). Using this dependence, dynamic flood thresholds were developed by integrating tidal variations with 1-h and 3-h accumulated rainfall. Evaluation results reveal that compound indicators substantially outperform rainfall-only thresholds, increasing detection rates in Taipei City from 59 to 82.2% for 1-h rainfall and from 72 to 82% for 3-h rainfall. In New Taipei City, the 3-h compound indicator improved detection from 64.6 to 84.3%. These findings underscore the critical role of tidal interaction in urban flood dynamics and demonstrate the potential of copula-based compound indicators for enhancing early warning systems in tide-influenced metropolitan regions.