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Optimal Operation of Urban Storm Detention Ponds for Flood Management

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Abstract

Operation of existing flood control facilities is one the efficient method for urban stormwater management. In order to quantitatively manage urban floods, operational policies of facilities should be adapted, before need to the enlargement of hydro-infrastructures with high expenditure. A new optimization based methodology is proposed in this paper for urban detention pond operation. The approach integrates an evolutionary algorithm known as Differential Evolution (DE) with EPA-SWMM simulation model to effectively manage detention storage capacities during flood periods. The proposed method is applied to in-line detention ponds at central part of Tehran Stormwater Drainage System (TSDS) to attain optimal rule curves of detention pond operation. Optimal rule curves are compared with the current method of operation and show that the proposed method can decrease network flooding of the smallest and largest extreme rainfall events more than75% and 30% respectively, and in average 55% considering all extreme rainfalls during 1979 to 2013. Therefore, the approach is recommended to replace with the current method of pond operating.

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References

  • Bogárdi I, Balogh E (2013) Floodway system operation along levee-protected rivers. J Water Resour Plan Manag 140(8):04014014

    Article  Google Scholar 

  • Chang FJ, Chang KY, Chang LC (2008) Counterpropagation fuzzy-neural network for city flood control system. J Hydrol 358(1):21–31

    Google Scholar 

  • Chiang YM, Chang LC, Tsai MJ, Wang YF, Chang FJ (2011) Auto-control of pumping operations in sewerage systems by rule-based fuzzy neural networks. Hydrol Earth Syst Sci 15(1):185–196

    Article  Google Scholar 

  • Darsono S, Labadie JW (2007) Neural-optimal control algorithm for real-time regulation of in-line storage in combined sewer systems. Environ Model Softw 22(9):1349–1361

    Article  Google Scholar 

  • Duchesne S, Mailhot A, Villeneuve JP (2004) Global predictive real-time control of sewers allowing surcharged flows. J Environ Eng 131(5):526–534

    Article  Google Scholar 

  • Elci A, Ayvaz MT (2014) Differential-evolution algorithm based optimization for the site selection of groundwater production wells with the consideration of the vulnerability concept. J Hydrol 115(16):736–749

    Article  Google Scholar 

  • EPA (2015) Storm Water Management Model User’s Manual Version 5.1, EPA- 600/R-14/413b

  • Gaborit E, Muschalla D, Vallet B, Vanrolleghem PA, Anctil F (2013) Improving the performance of stormwater detention basins by real-time control using rainfall forecasts. Urban Water J 10(4):230–246

    Article  Google Scholar 

  • Garofalo G, Giordano A, Piro P, Spezzano G, Vinci A (2017) A distributed real-time approach for mitigating CSO and flooding in urban drainage systems. J Netw Comput Appl 78:30–42. https://doi.org/10.1016/j.jnca.2016.11.004

  • Hsu NS, Huang CL, Wei CC (2013) Intelligent real-time operation of a pumping station for an urban drainage system. J Hydrol 489:85–97

    Article  Google Scholar 

  • Jafari F, Mousavi SJ, Yazdi J, Kim JH (2018) Real-time operation of pumping Systems for Urban Flood Mitigation: single-period vs. multi-period optimization. Water Resour Manag 32(14):4643–4660

    Article  Google Scholar 

  • Labadie, J. W. (1993). Optimal use of in-line storage for real-time urban stormwater control. Urban storm drainage. Water Resources Publications, Inc, Highlands Ranch, CO.

  • MGCE (2011) Tehran Stormwater Management Master Plan, Volume 4: Existing Main Drainage Network, Part 2: Hydraulic Modelling & Capacity Assessment, Mahab Ghods Consultant Engineers Company

  • Reddy M, Kumar D (2007) Multiobjective differential evolution with application to reservoir system optimization. J Comput Civ Eng:136–146

  • Moosavian N, Lence BJ (2017) Nondominated sorting differential evolution algorithms for multiobjective optimization of water distribution systems. J Water Resour Plan Manag 143(4). https://doi.org/10.1061/(ASCE)WR.1943-5452.0000741

  • Pleau M, Colas H, Lavallée P, Pelletier G, Bonin R (2005) Global optimal real-time control of the Quebec urban drainage system. Environ Model Softw 20(4):401–413

    Article  Google Scholar 

  • Sedki A, Ouazar D (2012) Hybrid particle swarm optimization and differential evolution for optimal design of water distribution systems. Adv Eng Inform 26(3):582–591

    Article  Google Scholar 

  • Storn, R., Price, K., (1995) DE a simple and efficient adaptive scheme for global optimization over continuous space, Technical Report TR-95-012, ICSI, 1995

  • Wei CC, Hsu NS, Huang CL (2014) Two-stage pumping control model for flood mitigation in inundated urban drainage basins. Water Resour Manag 28(2):425–444

    Article  Google Scholar 

  • Yagi S, Shiba S (1999) Application of genetic algorithms and fuzzy control to a combined sewer pumping station. Water Sci Technol 39(9):217–224

    Article  Google Scholar 

  • Vasan A, Simonovic SP (2010) Optimization of water distribution network design using differential evolution. J Water Resour Plan Manag 136(2). https://doi.org/10.1061/(ASCE)0733-9496(2010)136:2(279).

  • Xu DM, Qiu L, Chen SY (2012) Estimation of nonlinear Muskingum model parameter using differential evolution. J Hydrol Eng 17(2):348–353

    Article  Google Scholar 

  • Yazdi J (2016) Decomposition based multi objective evolutionary algorithms for Design of Large-Scale Water Distribution Networks. Water Resour Manag 30(8):2749–2766

    Article  Google Scholar 

  • Yazdi J, Yoo DG, Kim JH (2017) Comparative study of multi-objective evolutionary algorithms for hydraulic rehabilitation of urban drainage networks. Urban Water J 14(5):483–492

    Article  Google Scholar 

  • Yazdi J, Kim JH (2015) Intelligent pump operation and river diversion Systems for Urban Storm Management. J Hydrol Eng ASCE 20(11):04015031

    Article  Google Scholar 

  • Yazdi J, Doostparast Torshizi A, Zahraie B (2016a) Risk based optimal design of detention dams considering uncertain inflows. Stoch Environ Res Risk Assess 30(5):1457–1471

  • Yazdi J, Choi HS, Kim JH (2016b) A methodology for optimal operation of pumping stations in urban drainage systems. J Hydro Environ Res 11:101-112

  • Zoppou C (2001) Review of storm water models. Environ Model Softw 16:195–231

    Article  Google Scholar 

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Yazdi, J. Optimal Operation of Urban Storm Detention Ponds for Flood Management. Water Resour Manage 33, 2109–2121 (2019). https://doi.org/10.1007/s11269-019-02228-5

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