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

Springer Science and Business Media LLC - Tập 32 - Trang 4561-4573 - 2018
J. Yazdi1
1Faculty of Civil, Water and Environmental Engineering, Shahid Beheshti University, Tehran, Iran

Tóm tắt

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.

Tài liệu tham khảo

Barati R (2011) Parameter estimation of nonlinear Muskingum models using Nelder-Mead simplex algorithm. J Hydrol Eng 16(11):946–954 Deb K, Pratap A, Agarwal S, Meyarivan T (2002) A fast and elitist multiobjective genetic algorithm: NSGA-II.” IEEE Trans Evol Comput 6(2):182–197 Delelegn SW, Pathirana A, Gersonius B, Adeogun AG, Vairavamoorthy K (2011) Multi-objective optimisation of cost-benefit of urban flood management using a 1D2D coupled model. Water Sci Technol 63(5):1053–1059 Fu G, Butler D (2014) Copula-based frequency analysis of overflow and flooding in urban drainage systems. J Hydrol 510:49–58 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 Hosseini K, Nodoushan EJ, Barati R, Shahheydari H (2016) Optimal design of labyrinth spillways using meta-heuristic algorithms. KSCE J Civ Eng 20(1):468–477 Mahab Ghods Consultant Engineers (2011a) Tehran stormwater management master plan, Vol. 4: existing main drainage network, Part 2: Hydraulic Modeling and Capacity Assessment, December 2011, Technical and development deputy of Tehran municipality, Tehran, Iran Mahab Ghods Consultant Engineers (2011b) Tehran Stormwater Management Master Plan, Vol. 2, part 3: Urban Food Hydrology & Sediment Load, December 2011, Technical and development deputy of Tehran municipality, Tehran, Iran Marlow DR, Boulaire F, Beale DJ, Grundy C, Moglia M (2011) Sewer performance reporting: factors that influence blockages. J Infrastruct Syst. https://doi.org/10.1061/(ASCE)IS.1943-555X.0000041 Moosavian N, Lence BJ (2016) Nondominated sorting differential evolution algorithms for multiobjective optimization of water distribution systems. J Water Resour Plan Manag 143:04016082 Mugume SN, Gomez DE, Fu G, Farmani R, Butler D (2015) A global analysis approach for investigating structural resilience in urban drainage systems. Water Res 81:15–26 Park M, Chung G, Yoo C, Kim J-H (2012) optimal design of stormwater detention basin using the genetic algorithm. KSCE J Civ Eng 16(4):660–666 Reddy M, Kumar D (2006) Optimal reservoir operation using multi-objective evolutionary algorithm. Water Resour Manag 20(6):861–878 Rossman L (2008) Storm water management model user’s manual: version 5.0., EPA/600/R-05/040. National Risk Management Research Laboratory, Cincinnati Streftaris G, Wallerstein NP, Gibson GJ, Arthur S (2013) Modeling probability of blockage at culvert trash screens using Bayesian approach. J Hydraul Eng. https://doi.org/10.1061/(ASCE)HY.1943-7900.0000723 Sun SA, Djordjević S, Khu S-T (2011) A general framework for flood risk-based storm sewer network design. Urban Water J 8(1):13–27 Sweetapple C, Fu G, Farmani R, Meng F, Ward S, Butler D (2018) Attribute-based intervention development for increasing resilience of urban drainage systems. Water Sci Technol 77(6):1757–1764 USACE (US Army Corps of Engineers) (2010) Hydrologic modeling system HEC-HMS, quick start guide (version 3.5, 2010). Institute for Water Resources, Hydrologic Engineering Centre, Davis Vojinovic Z, Sahlu S, Torres AS, Seyoum SD, Anvarifar F, Matungulu H, Barreto W, Savic D, Kapelan Z (2014) Multi-objective rehabilitation of urban drainage systems under uncertainties. J Hydroinf 16(5):1044 Wallerstein NP, Arthur S (2012) Improved methods for predicting trash delivery to culverts protected by trash screens. J Flood Risk Manage 5(1):23–36. https://doi.org/10.1111/j.1753-318x.2011.01122.x Xu K, Bin L, Lian J, Liu R (2018) Staged optimization Design for Updating Urban Drainage Systems in a City of China. Water 10(1):66 Yazdi J (2016) Decomposition based multi objective evolutionary algorithms for design of large-scale water distribution networks. Water Resour Manag 30(8):2749–2766 Yazdi J (2018) Rehabilitation of urban drainage systems using a resilience-based approach. Water Resour Manag 32(2):721–734 Yazdi J, Kim JH (2015) Intelligent pump operation and river diversion systems for urban storm management. J Hydrol Eng ASCE 20(11):04015031 Yazdi J, Yoo DG, Kim JH (2016) Comparative study of multi-objective evolutionary algorithms for hydraulic rehabilitation of urban drainage networks. Urban Water J 14(5):483–492