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A Framework for Quantifying Stormwater Control Measures’ Hydrologic Performance with Analytical Stochastic Models

Author

Listed:
  • Jiachang Wang

    (Shandong University)

  • Jun Wang

    (Shandong University)

  • Shengle Cao

    (Shandong University)

  • Chuanqi Li

    (Shandong University)

  • Shouhong Zhang

    (Beijing Forestry University)

  • Yiping Guo

    (McMaster University)

Abstract

Previously developed analytical stochastic models (ASMs) have the limitations in that they can only be individually applied for specific end-of-pipe or low impact development facilities. This paper proposed a framework of ASMs that can be used for easily analyzing different types of storm water control measures (SCMs). The effective storage capacity for either storage-based or infiltration-based control measures was defined and formulated. Various inflow and outflow patterns of specific SCMs were also considered and analyzed. This framework also provides better insights into the similarities and differences among the model structures of different SCMs. Case studies with six climatically different locations in China and the U.S., different soil properties and six types of SCMs demonstrated the effects of various factors on runoff reduction ratios. Despite the limitations of the proposed framework such as the assumption of exponential distribution for rainfall event characteristics and the unavailability to perform single rainfall event simulation, it can still be used as a convenient toolkit to make fast and comprehensive decisions in selecting different SCMs for a specific runoff control target in design practices.

Suggested Citation

  • Jiachang Wang & Jun Wang & Shengle Cao & Chuanqi Li & Shouhong Zhang & Yiping Guo, 2024. "A Framework for Quantifying Stormwater Control Measures’ Hydrologic Performance with Analytical Stochastic Models," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 38(13), pages 5385-5402, October.
    • Handle: RePEc:spr:waterr:v:38:y:2024:i:13:d:10.1007_s11269-024-03919-4
    DOI: 10.1007/s11269-024-03919-4
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    References listed on IDEAS

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    1. Francesco Pugliese & Carlo Gerundo & Francesco Paola & Gerardo Caroppi & Maurizio Giugni, 2022. "Enhancing the Urban Resilience to Flood Risk Through a Decision Support Tool for the LID-BMPs Optimal Design," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(14), pages 5633-5654, November.
    2. Shouhong Zhang & Yiping Guo, 2014. "Stormwater Capture Efficiency of Bioretention Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(1), pages 149-168, January.
    3. Jun Wang & Yiping Guo, 2020. "Proper Sizing of Infiltration Trenches Using Closed-Form Analytical Equations," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(12), pages 3809-3821, September.
    4. Haowen Xie & Mark Randall & Kwok-wing Chau, 2022. "Green Roof Hydrological Modelling With GRU and LSTM Networks," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(3), pages 1107-1122, February.
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