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The Impact of Uncertainty Factors on Optimal Sizing and Costs of Low-Impact Development: a Case Study from Beijing, China

Author

Listed:
  • Jinjin Gu

    (Hefei University of Technology)

  • Quan Zhang

    (Hefei University of Technology)

  • Dazhi Gu

    (Hefei University of Technology)

  • Qingguo Zhang

    (Anhui Agricultural University)

  • Xiao Pu

    (Capital Normal University)

Abstract

The facility allocation optimization of Low-impact development (LID) optimization has been used widely to prevent and tackle urban storm water pollution. However, uncertainties existing in nature and human society would influence the size and total cost of LID. To study the influence of the uncertainties on LID optimization allocation, the research develops the model of LID optimization allocation under uncertainty. The principle of the model is establishing primarily the LID optimization model based on certain numbers and identifying the uncertainties. Hence, the model integrates the uncertainty programming, including interval programming, fuzzy programming, stochastic programming, chance constraint programming (CCP) and scenario programming. The model of LID optimization allocation under uncertainty is established with the conditions. The developed uncertainty model tackles multiple types of uncertainties, and the results of the model are in the interval form in multiple scenarios. The model analyses the effects of uncertainties on the size and total cost of LID in this way. The study shows that the uncertainties in rainfall, infiltration rate, release coefficient, funds and unit price all have a significant influence on the size and total cost of LID when these uncertainty factors overlay. A higher violation probability of CCP corresponding to LID sizing results to a wider interval number of the corresponding uncertainty. The developed method of the study is universal, and the method could be extended to other cases of LID optimization allocation to speculate the influence of uncertainties.

Suggested Citation

  • Jinjin Gu & Quan Zhang & Dazhi Gu & Qingguo Zhang & Xiao Pu, 2018. "The Impact of Uncertainty Factors on Optimal Sizing and Costs of Low-Impact Development: a Case Study from Beijing, China," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(13), pages 4217-4238, October.
    • Handle: RePEc:spr:waterr:v:32:y:2018:i:13:d:10.1007_s11269-018-2040-3
    DOI: 10.1007/s11269-018-2040-3
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    References listed on IDEAS

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    1. Wu, C.B. & Huang, G.H. & Li, W. & Xie, Y.L. & Xu, Y., 2015. "Multistage stochastic inexact chance-constraint programming for an integrated biomass-municipal solid waste power supply management under uncertainty," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 1244-1254.
    2. A. Charnes & W. W. Cooper, 1983. "Response to "Decision Problems Under Risk and Chance Constrained Programming: Dilemmas in the Transition"," Management Science, INFORMS, vol. 29(6), pages 750-753, June.
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    Cited by:

    1. Jinjin Gu & Yuan Cao & Min Wu & Min Song & Lin Wang, 2022. "A Novel Method for Watershed Best Management Practices Spatial Optimal Layout under Uncertainty," Sustainability, MDPI, vol. 14(20), pages 1-18, October.
    2. Jinjin Gu & Hui Hu & Lin Wang & Wei Xuan & Yuan Cao, 2020. "Fractional Stochastic Interval Programming for Optimal Low Impact Development Facility Category Selection under Uncertainty," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(5), pages 1567-1587, March.

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