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Improving Urban Drainage Systems Resiliency Against Unexpected Blockages: A Probabilistic Approach

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  • J. Yazdi

    (Shahid Beheshti University)

Abstract

Considering the increase of flood hazards in many large cities, the rehabilitation of hydro-urban infrastructures is an important concern for the municipal authorities. A probabilistic approach based on Monte Carlo Simulation (MCS) is presented in this study to improve the resiliency of urban drainage systems when they are subject to unexpected structural blockages. The approach is integrated with SWMM simulation model and an evolutionary search algorithm to find the best set of rehabilitation measures under a significant number of blockage scenarios. Experimental results on the west zone of main drainage system in Tehran city indicate that proposed approach outperforms the conventional hydraulic-based methodology in terms of cost effectiveness and functionality. Results also show that adding the redundancy to the system by bypass lines in bottlenecks is considerably more efficient for flood mitigation and the increase of system resiliency under blockage incidents rather than using conventional methods such as detention ponds and enlargement of the channel sizes.

Suggested Citation

  • J. Yazdi, 2018. "Improving Urban Drainage Systems Resiliency Against Unexpected Blockages: A Probabilistic Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(14), pages 4561-4573, November.
    • Handle: RePEc:spr:waterr:v:32:y:2018:i:14:d:10.1007_s11269-018-2069-3
    DOI: 10.1007/s11269-018-2069-3
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    References listed on IDEAS

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    1. J. Yazdi, 2016. "Decomposition based Multi Objective Evolutionary Algorithms for Design of Large-Scale Water Distribution Networks," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(8), pages 2749-2766, June.
    2. J. Yazdi, 2018. "Rehabilitation of Urban Drainage Systems Using a Resilience-Based Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(2), pages 721-734, January.
    3. M. Reddy & D. Kumar, 2006. "Optimal Reservoir Operation Using Multi-Objective Evolutionary Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 20(6), pages 861-878, December.
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    Cited by:

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    2. Dongwei Qiu & Hao Xu & Dean Luo & Qing Ye & Shaofu Li & Tong Wang & Keliang Ding, 2020. "A rainwater control optimization design approach for airports based on a self-organizing feature map neural network model," PLOS ONE, Public Library of Science, vol. 15(1), pages 1-23, January.

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