Risk-Informed Framework for Sewerage System Rehabilitation Management
Publication: Journal of Pipeline Systems Engineering and Practice
Volume 12, Issue 2
Abstract
The increasing storm frequency and severity due to climate change, and sewer system degradation due to aging and corrosion impose a greater risk of failure and overflooding to drainage systems. This paper proposes a new risk-informed framework in order to identify optimal strategies for drainage system rehabilitation under limited rehabilitation budgets. The proposed Hydraulics and Risk Combined Model (HRCM) dynamically couples the Storm Water Management Model (SWMM) and a risk model through a multiobjective optimization to maximize hydraulic performance while minimizing the risk of failure of the sewer system. The sensitivity analysis shows that with a small population size in a genetic algorithm the HRCM is capable of solving complex test cases. In addition, with increasing population size, the Pareto front converges with several rehabilitation strategies having the same objective function values. The model is examined in the context of several simple and complex scenarios, and the results demonstrate the model’s validity and robustness. The results also show that the proposed model is capable of identifying satisfactory rehabilitation strategies that can inform the optimal drainage system rehabilitation.
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Data Availability Statement
Some or all data, models, or code generated or used during the study are available from the corresponding author by request: HRCM source code, input data files, and output results files.
Acknowledgments
The authors would like to acknowledge Zirou Qiu at the University of Virginia for his help in programming.
References
Adamowski, J., K. Adamowski, and J. Bougadis. 2010. “Influence of trend on short duration design storms.” Water Resour. Manage. 24 (3): 401–413. https://doi.org/10.1007/s11269-009-9452-z.
Akan, A. O., and R. J. Houghtalen. 2003. Urban hydrology, hydraulics, and stormwater quality. New York: Wiley.
Altarabsheh, A., A. Kandil, and M. Ventresca. 2018. “New multiobjective optimization approach to rehabilitate and maintain sewer networks based on whole lifecycle behavior.” J. Comput. Civ. Eng. 32 (1): 04017069. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000715.
ASCE. 2017. ASCE Infrastructure Report 2017. Reston, VA: ASCE.
Baah, K., B. Dubey, R. Harvey, and E. McBean. 2015. “A risk-based approach to sanitary sewer pipe asset management.” Sci. Total Environ. 505 (Feb): 1011–1017. https://doi.org/10.1016/j.scitotenv.2014.10.040.
Bennis, S., J. Bengassem, and P. Lamarre. 2003. “Hydraulic performance index of a sewer network.” J. Hydraul. Eng. 129 (7): 504–510. https://doi.org/10.1061/(ASCE)0733-9429(2003)129:7(504).
Bi, W., G. C. Dandy, and H. R. Maier. 2016. “Use of domain knowledge to increase the convergence rate of evolutionary algorithms for optimizing the cost and resilience of water distribution systems.” J. Water Resour. Plann. Manage. 142 (9): 04016027. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000649.
Bush, E., and D. S. Lemmen, eds. 2019. Canada’s Changing Climate Report. Ottawa: Government of Canada.
Buttle, J. M., D. M. Allen, D. Caissie, B. Davison, M. Hayashi, D. L. Peters, J. W. Pomeroy, S. Simonovic, A. St-Hilaire, and P. H. Whitfield. 2016. “Flood processes in Canada: Regional and special aspects.” Can. Water Resour. J. 41 (1–2): 7–30. https://doi.org/10.1080/07011784.2015.1131629.
Buttle, J. M., and P. M. Lafleur. 2007. “Anatomy of an extreme event: The July 14–15, 2004 Peterborough rainstorm.” Can. Water Resour. J. 32 (1): 59–74. https://doi.org/10.4296/cwrj3201059.
CIRC (Canadian Infrastructure Report Card). 2019. Monitoring the State of Canada’s core public infrastructure: Canadian infrastructure report card 2019. Ottawa: CIRC.
Dawson, R. J., L. Speight, J. W. Hall, S. Djordjevic, D. Savic, and J. Leandro. 2008. “Attribution of flood risk in urban areas.” J. Hydroinf. 10 (4): 275–288. https://doi.org/10.2166/hydro.2008.054.
Deb, K., A. Pratap, S. Agarwal, and T. Meyarivan. 2002. “A fast and elitist multiobjective genetic algorithm: NSGA-II.” IEEE Trans. Evol. Comput. 6 (2): 182–197. https://doi.org/10.1109/4235.996017.
Duchesne, S., G. Beardsell, J.-P. Villeneuve, B. Toumbou, and K. Bouchard. 2013. “A survival analysis model for sewer pipe structural deterioration: A sewer deterioration model.” Comput.-Aided Civ. Infrastruct. Eng. 28 (2): 146: 160. https://doi.org/10.1111/j.1467-8667.2012.00773.x.
Girones, R., M. A. Ferrús, J. L. Alonso, J. Rodriguez-Manzano, B. Calgua, A. de Abreu Corrêa, A. Hundesa, A. Carratala, and S. Bofill-Mas. 2010. “Molecular detection of pathogens in water—The pros and cons of molecular techniques.” Water Res. 44 (15): 4325–4339. https://doi.org/10.1016/j.watres.2010.06.030.
Guo, Y., G. A. Walters, S. T. Khu, and E. Keedwell. 2007. “A novel cellular automata based approach to storm sewer design.” Eng. Optim. 39 (3): 345–364. https://doi.org/10.1080/03052150601128261.
Huang, D., X. Liu, S. Jiang, H. Wang, J. Wang, and Y. Zhang. 2018. “Current state and future perspectives of sewer networks in urban China.” Front. Environ. Sci. Eng. 12 (3): 2. https://doi.org/10.1007/s11783-018-1023-1.
Irfan, M., M. B. Khurshid, S. Labi, and W. Flora. 2009. “Evaluating the cost effectiveness of flexible rehabilitation treatments using different performance criteria.” J. Transp. Eng. 135 (10): 753–763. https://doi.org/10.1061/(ASCE)TE.1943-5436.0000041.
Jeffers, S., and F. Montalto. 2018. “Modeling urban sewers with artificial fractal geometries.” J. Water Manage. Model. 26: C455. https://doi.org/10.14796/JWMM.C455.
Jegatheesan, V. 2019. Urban stormwater and flood management: Enhancing the liveability of cities. New York: Springer.
Kleiner, Y., and B. Rajani. 2001. “Comprehensive review of structural deterioration of water mains: Statistical models.” Urban Water 3 (3): 131–150. https://doi.org/10.1016/S1462-0758(01)00033-4.
Kleiner, Y., R. Sadiq, and B. Rajani. 2004. “Modeling failure risk in buried pipes using fuzzy Markov deterioration process.” In Proc., Pipeline Engineering and Construction, Presented at the Pipeline Division Specialty Congress 2004, 1–12. Reston, VA: ASCE. https://doi.org/10.1061/40745(146)7.
Maharjan, M., A. Pathirana, B. Gersonius, and K. Vairavamoorthy. 2009. “Staged cost optimization of urban storm drainage systems based on hydraulic performance in a changing environment.” Hydrol. Earth Syst. Sci. 13 (4): 481–489. https://doi.org/10.5194/hess-13-481-2009.
MathWorks Support Team. 2018. “Is it possible to solve a mixed-integer multi-objective optimization problem using Global Optimization Toolbox?” Accessed April 18, 2018. https://www.mathworks.com/matlabcentral/answers/103369-is-it-possible-to-solve-a-mixed-integer-multi-objective-optimization-problem-using-global-optimizati.
Mohammadi, M. M., M. Najafi, V. Kaushal, R. Serajiantehrani, N. Salehabadi, and T. Ashoori. 2019. “Sewer pipes condition prediction models: A state-of-the-art review.” Infrastruct. 4 (4): 64. https://doi.org/10.3390/infrastructures4040064.
Moussavi, A., H. M. V. Samani, and A. Haghighi. 2017. “A framework for optimal reliability-based storm sewer network design in flat areas.” Can. J. Civ. Eng. 44 (3): 139–150. https://doi.org/10.1139/cjce-2016-0244.
Ogidan, O., and M. Giacomoni. 2016. “Multiobjective genetic optimization approach to identify pipe segment replacements and inline storages to reduce sanitary sewer overflows.” Water Resour. Manage. 30 (11): 3707–3722. https://doi.org/10.1007/s11269-016-1373-z.
Rossman, L. A. 2015. Storm Water Management Model user’s manual version 5.1, 353. Washington, DC: USEPA.
Salman, B., and O. Salem. 2012. “Risk assessment of wastewater collection lines using failure models and criticality ratings.” J. Pipeline Syst. Eng. Pract. 3 (3): 68–76. https://doi.org/10.1061/(ASCE)PS.1949-1204.0000100.
Shao, Z., X. Zhang, S. Li, S. Deng, and H. Chai. 2017. “A novel SWMM based algorithm application to storm sewer network design.” Water 9 (10): 747. https://doi.org/10.3390/w9100747.
Tran, D. H., A. W. M. Ng, K. J. Mcmanus, and S. Burn. 2008. “Prediction models for serviceability deterioration of stormwater pipes.” Struct. Infrastruct. Eng. 4 (4): 287–295. https://doi.org/10.1080/15732470600792236.
Tran, D. H., B. J. C. Perera, and A. W. M. Ng. 2009. “Comparison of structural deterioration models for stormwater drainage pipes.” Comput.-Aided Civ. Infrastruct. Eng. 24 (2): 145: 156. https://doi.org/10.1111/j.1467-8667.2008.00577.x.
Tran, D. H., B. J. C. Perera, and A. W. M. Ng. 2010. “Hydraulic deterioration models for storm-water drainage pipes: Ordered probit versus probabilistic neural network.” J. Comput. Civ. Eng. 24 (2): 140–150. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000020.
United Nations Climate Change. 2015. The Paris Agreement. Paris: United Nations Climate Change.
Valizadeh, N., A. Y. Shamseldin, and L. Wotherspoon. 2019. “Quantification of the hydraulic dimension of stormwater management system resilience to flooding.” Water Resour. Manage. 33 (13): 4417–4429. https://doi.org/10.1007/s11269-019-02361-1.
Vasconcelos, J., Y. Eldayih, Y. Zhao, and J. A. Jamily. 2018. “Evaluating storm water management model accuracy in conditions of mixed flows.” J. Water Manage. Model. 26: C451. https://doi.org/10.14796/JWMM.C451.
Vasiljevic, B., E. McBean, and B. Gharabaghi. 2012. “Trends in rainfall intensity for stormwater designs in Ontario.” J. Water Clim. Change 3 (1): 1–10. https://doi.org/10.2166/wcc.2012.125.
Wirahadikusumah, R., D. Abraham, and J. Castello. 1999. “Markov decision process for sewer rehabilitation.” J. Eng. Constr. Archit. Manage. 6 (4): 358: 370. https://doi.org/10.1108/eb021124.
Yao, L., Q. Dong, F. Ni, J. Jiang, X. Lu, and Y. Du. 2019. “Effectiveness and cost-effectiveness evaluation of pavement treatments using life-cycle cost analysis.” J. Transp. Eng., Part B: Pavements 145 (2): 04019006. https://doi.org/10.1061/JPEODX.0000106.
Yazdi, J., A. Sadollah, E. H. Lee, D. G. Yoo, and J. H. Kim. 2017a. “Application of multi-objective evolutionary algorithms for the rehabilitation of storm sewer pipe networks: Comparison of MOEAs.” J. Flood Risk Manage. 10 (3): 326–338. https://doi.org/10.1111/jfr3.12143.
Yazdi, J., D. G. Yoo, and J. H. Kim. 2017b. “Comparative study of multi-objective evolutionary algorithms for hydraulic rehabilitation of urban drainage networks.” Urban Water J. 14 (5): 483–492. https://doi.org/10.1080/1573062X.2016.1223319.
Yin, X., Y. Chen, A. Bouferguene, H. Zaman, M. Al-Hussein, and L. Kurach. 2020. “A deep learning-based framework for an automated defect detection system for sewer pipes.” Autom. Constr. 109 (Jan): 102967. https://doi.org/10.1016/j.autcon.2019.102967.
Zhao, J. Q., S. E. McDonald, and Y. Kleiner. 2001. Guidelines for condition assessment and rehabilitation of large sewers. Ottawa: Institute for Research in Construction National Research Council Canada.
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Published In
Journal of Pipeline Systems Engineering and Practice
Volume 12 • Issue 2 • May 2021
Copyright
© 2020 American Society of Civil Engineers.
History
Received: Apr 29, 2020
Accepted: Sep 4, 2020
Published online: Dec 31, 2020
Published in print: May 1, 2021
Discussion open until: May 31, 2021
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