Localization and Quantification of Blockages in Water Distribution Networks Using a Mathematical Model
Publication: Journal of Water Resources Planning and Management
Volume 150, Issue 5
Abstract
Blockage, which arises from accumulated materials like sand, stones, sediment, uncontrolled growth of tree roots within pipes, and the inadvertent partial closure of in-line valves, poses a pervasive challenge in the operational sphere of water distribution networks (WDNs). This results in significant head loss in the pipes, leading to disruptions in the water supply. Identifying such blockages conventionally requires specialized human resources and is often encumbered by cost and time challenges. This paper introduces a method for precisely determining the location and magnitude of blockages within WDNs. This methodology is firmly grounded in a calibration-optimization framework, harnessing a specially crafted hybrid optimization algorithm known as PSOHS, which combines the strengths of particle swarm optimization (PSO) and harmony search (HS) algorithms. Detailed comparisons are drawn between simulated pressure data (derived from the hydraulic network model) and corresponding field data at multiple points to minimize disparities, thereby facilitating the precise identification of potential blockages in a WDN. The proposed method undergoes rigorous evaluation across two benchmark networks (modified Poulakis and Hanoi) under diverse scenarios as well as on an actual WDN. Results from over 60,000 simulated blockage scenarios underscore the method’s remarkable proficiency, achieving blockage localization accuracy of 99.9% and magnitude estimation with a maximum absolute error (MAE) of less than 3%. Particularly noteworthy is the superior performance of the PSOHS algorithm as proposed, surpassing the PSO algorithm by enhancing blockage localization accuracy by a minimum of 10.5% and reducing MAE by 3%. Further, adopting the proposed algorithm over the HS algorithm yields improvements of 27.5% and 3.5%, respectively. Applying the proposed method in an actual network effectively pinpointed its blockage. Consequently, this algorithm presents a valuable tool for WDN operators, augmenting their capacity for effective network management.
Get full access to this article
View all available purchase options and get full access to this article.
Data Availability Statement
All data, benchmark network models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
The technical support and resources from the Center for High Performance Computing at Shahid Beheshti University of Iran are gratefully acknowledged. The authors express their gratitude to the anonymous reviewers for their meticulous and constructive feedback, which has significantly enhanced the quality of the manuscript.
References
Brunone, B., F. Maietta, C. Capponi, H.-F. Duan, and S. Meniconi. 2023. “Detection of partial blockages in pressurized pipes by transient tests: A review of the physical experiments.” Fluids 8 (1): 19. https://doi.org/10.3390/fluids8010019.
Cao, H., S. Hopfgarten, A. Ostfeld, E. Salomons, and P. Li. 2019. “Simultaneous sensor placement and pressure reducing valve localization for pressure control of water distribution systems.” Water 11 (7): 1352. https://doi.org/10.3390/w11071352.
Clerc, M., and J. Kennedy. 2002. “The particle swarm—Explosion, stability, and convergence in a multidimensional complex space.” IEEE Trans. Evol. Comput. 6 (1): 58–73. https://doi.org/10.1109/4235.985692.
Datta, S., N. K. Gautam, and S. Sarkar. 2018. “Pipe network blockage detection by frequency response and genetic algorithm technique.” J. Water Supply Res. Technol. AQUA 67 (6): 543–555. https://doi.org/10.2166/aqua.2018.046.
Do, N. C., A. R. Simpson, J. W. Deuerlein, and O. Piller. 2018. “Locating inadvertently partially closed valves in water distribution systems.” J. Water Resour. Plann. Manage. 144 (8): 04018039. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000958.
Duan, H. F. 2016. “Sensitivity analysis of a transient-based frequency domain method for extended blockage detection in water pipeline systems.” J. Water Resour. Plann. Manage. 142 (4): 04015073. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000625.
Duan, H.-F., P. J. Lee, M. S. Ghidaoui, and Y.-K. Tung. 2012. “Extended blockage detection in pipelines by using the system frequency response analysis.” J. Water Resour. Plann. Manage. 138 (1): 55–62. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000145.
Duan, H.-F., P. J. Lee, A. Kashima, J. Lu, M. S. Ghidaoui, and Y.-K. Tung. 2013. “Extended blockage detection in pipes using the system frequency response: Analytical analysis and experimental verification.” J. Hydraul. Eng. 139 (7): 763–771. https://doi.org/10.1061/(ASCE)HY.1943-7900.0000736.
Eliades, D. G., M. Kyriakou, S. Vrachimis, and M. M. Polycarpou. 2017. “EPANET-MATLAB toolkit: An open-source software for interfacing EPANET with MATLAB.” In Proc., 14th Int. Conf. on Computing and Control for the Water Industry (CCWI). Amsterdam, Netherlands: Zenodo. https://doi.org/10.5281/zenodo.831493.
Ferreira, B., A. Antunes, N. Carriço, and D. Covas. 2022. “Multi-objective optimization of pressure sensor location for burst detection and network calibration.” Comput. Chem. Eng. 162 (Jun): 107826. https://doi.org/10.1016/j.compchemeng.2022.107826.
Ferreira, B., A. Antunes, N. Carriço, and D. Covas. 2023. “NSGA-II parameterization for the optimal pressure sensor location in water distribution networks.” Urban Water J. 20 (6): 738–750. https://doi.org/10.1080/1573062X.2023.2209553.
Ferreira, B., N. Carriço, and D. Covas. 2021. “Optimal number of pressure sensors for real-time monitoring of distribution networks by using the hypervolume indicator.” Water 13 (16): 2235. https://doi.org/10.3390/w13162235.
Fujiwara, O., and D. B. Khang. 1990. “A two-phase decomposition method for optimal design of looped water distribution networks.” Water Resour. Res. 26 (4): 539–549. https://doi.org/10.1029/WR026i004p00539.
Fujiwara, O., and D. B. Khang. 1991. “Correction to ‘A two-phase decomposition method for optimal design of looped water distribution networks’ by Okitsugu Fujiwara and Do Ba Khang.” Water Resour. Res. 27 (5): 985–986. https://doi.org/10.1029/91WR00368.
Geem, Z. W., J. H. Kim, and G. V. Loganathan. 2001. “A new heuristic optimization algorithm: Harmony search.” Simulation 76 (2): 60–68. https://doi.org/10.1177/003754970107600201.
Jafari, R., S. Razvarz, C. Vargas-Jarillo, and A. Gegov. 2020. “Blockage detection in pipeline based on the extended Kalman filter observer.” Electronics 9 (1): 91. https://doi.org/10.3390/electronics9010091.
Kennedy, J., and R. Eberhart. 1995. “Particle swarm optimization.” In Proc., ICNN’95–Int. Conf. on Neural Networks. New York: IEEE. https://doi.org/10.1109/ICNN.1995.488968.
Klapcsik, K., R. Varga, and C. Hős. 2018. “Optimal pressure measurement layout design in water distribution network systems.” Period. Polytech. Mech. Eng. 62 (1): 51–64. https://doi.org/10.3311/PPme.11409.
Kowalczuk, Z., and K. Gunawickrama. 2000. “Leak detection and isolation for transmission pipelines via nonlinear state estimation.” IFAC Proc. Vol. 33 (11): 921–926. https://doi.org/10.1016/S1474-6670(17)37479-7.
Kumar, P., and P. K. Mohapatra. 2022. “Partial blockage detection in pipelines by modified reconstructive method of characteristics technique.” J. Hydraul. Eng. 148 (4): 04022003. https://doi.org/10.1061/(ASCE)HY.1943-7900.0001971.
Massari, C., T. C. J. Yeh, M. Ferrante, B. Brunone, and S. Meniconi. 2013. “Detection and sizing of extended partial blockages in pipelines by means of a stochastic successive linear estimator.” J. Hydroinf. 16 (2): 248–258. https://doi.org/10.2166/hydro.2013.172.
Meier, R. W., and B. D. Barkdoll. 2000. “Sampling design for network model calibration using genetic algorithms.” J. Water Resour. Plann. Manage. 126 (4): 245–250. https://doi.org/10.1061/(ASCE)0733-9496(2000)126:4(245).
Meniconi, S., B. Brunone, M. Ferrante, and C. Capponi. 2016. “Mechanism of interaction of pressure waves at a discrete partial blockage.” J. Fluids Struct. 62 (Apr): 33–45. https://doi.org/10.1016/j.jfluidstructs.2015.12.010.
Meniconi, S., B. Brunone, M. Ferrante, and C. Massari. 2011. “Small amplitude sharp pressure waves to diagnose pipe systems.” Water Resour. Manage. 25 (1): 79–96. https://doi.org/10.1007/s11269-010-9688-7.
Moasheri, R., and M. R. Jalili Ghazizade. 2023. “Locating the average pressure zone point in water distribution networks through hydraulic analysis.” J. Water Wastewater Sci. Eng. https://doi.org/10.22112/jwwse.2023.404414.1368.
Nasraoui, S., M. Louati, and M. S. Ghidaoui. 2023. “Blockage detection in pressurized water-filled pipe using high frequency acoustic waves.” Mech. Syst. Signal Process. 185 (Feb): 109817. https://doi.org/10.1016/j.ymssp.2022.109817.
Peng, S., J. Cheng, X. Wu, X. Fang, and Q. Wu. 2022. “Pressure sensor placement in water supply network based on graph neural network clustering method.” Water 14 (2): 150. https://doi.org/10.3390/w14020150.
Piotrowski, A. P., J. J. Napiorkowski, and A. E. Piotrowska. 2020. “Population size in particle swarm optimization.” Swarm Evol. Comput. 58 (Nov): 100718. https://doi.org/10.1016/j.swevo.2020.100718.
Poulakis, Z., D. Valougeorgis, and C. Papadimitriou. 2003. “Leakage detection in water pipe networks using a Bayesian probabilistic framework.” Probab. Eng. Mech. 18 (4): 315–327. https://doi.org/10.1016/S0266-8920(03)00045-6.
Rubio Scola, I., G. Besançon, and D. Georges. 2017. “Blockage and leak detection and location in pipelines using frequency response optimization.” J. Hydraul. Eng. 143 (1): 04016074. https://doi.org/10.1061/(ASCE)HY.1943-7900.0001222.
Salehi, S., M. Tabesh, and M. R. Jalili Ghazizade. 2019. “Development of a prioritization model for rehabilitation of pipes in water distribution systems with minimum structural data.” J. Water Wastewater 29 (6): 40–55. https://doi.org/10.22093/wwj.2017.91467.2447.
Sattar, A. M., M. H. Chaudhry, and A. A. Kassem. 2008. “Partial blockage detection in pipelines by frequency response method.” J. Hydraul. Eng. 134 (1): 76–89. https://doi.org/10.1061/(ASCE)0733-9429(2008)134:1(76).
Simone, A., O. Giustolisi, and D. B. Laucelli. 2016. “A proposal of optimal sampling design using a modularity strategy.” Water Resour. Res. 52 (8): 6171–6185. https://doi.org/10.1002/2016WR018944.
Smith, P., and R. W. Zappe. 2003. Valve selection handbook: Engineering fundamentals for selecting the right valve design for every industrial flow application. Burlington, NJ: Elsevier.
Sophocleous, S., D. Savic, Z. Kapelan, Y. Shen, and P. Sage. 2015. “Advances in water mains network modelling for improved operations.” In Proc., 13th Computer Control for Water Industry Conf., CCWI 2015. Amsterdam, Netherlands: Elsevier. https://doi.org/10.1016/j.proeng.2015.08.912.
Sophocleous, S., D. A. Savić, Z. Kapelan, and O. Giustolisi. 2017. “A two-stage calibration for detection of leakage hotspots in a real water distribution network.” In Proc., XVIII Int. Conf. on Water Distribution Systems Analysis, WDSA2016. Amsterdam, Netherlands: Elsevier. https://doi.org/10.1016/j.proeng.2017.03.223.
Verde, C. 2001. “Multi-leak detection and isolation in fluid pipelines.” Control Eng. Pract. 9 (6): 673–682. https://doi.org/10.1016/S0967-0661(01)00026-0.
Wan, W., X. Chen, B. Zhang, and J. Lian. 2021. “Transient simulation and diagnosis of partial blockage in long-distance water supply pipeline systems.” J. Pipeline Syst. Eng. Pract. 12 (3): 04021016. https://doi.org/10.1061/(ASCE)PS.1949-1204.0000562.
Wang, X.-J. 2002. “Leakage and blockage detection in pipelines and pipe network systems using fluid transients.” Ph.D. dissertation, Dept. of Civil and Environmental Engineering, Univ. of Adelaide.
Wang, X.-J., M. F. Lambert, and A. R. Simpson. 2005. “Detection and location of a partial blockage in a pipeline using damping of fluid transients.” J. Water Resour. Plann. Manage. 131 (3): 244–249. https://doi.org/10.1061/(ASCE)0733-9496(2005)131:3(244).
Wu, Z. Y., T. Walski, R. Mankowski, G. Herrin, R. Gurrieri, and M. Tryby. 2002. “Calibrating water distribution model via genetic algorithms.” In Proc., AWWA IMTech Conf. Kansas City, MI: Human Competitive.
Yang, G., and H. Wang. 2023. “Optimal pressure sensor deployment for leak identification in water distribution networks.” Sensors 23 (12): 5691. https://doi.org/10.3390/s23125691.
Zouari, F., E. Blåsten, M. Louati, and M. S. Ghidaoui. 2019. “Internal pipe area reconstruction as a tool for blockage detection.” J. Hydraul. Eng. 145 (6): 04019019. https://doi.org/10.1061/(ASCE)HY.1943-7900.0001602.
Information & Authors
Information
Published In
Journal of Water Resources Planning and Management
Volume 150 • Issue 5 • May 2024
Copyright
© 2024 American Society of Civil Engineers.
History
Received: Jul 14, 2023
Accepted: Dec 8, 2023
Published online: Feb 27, 2024
Published in print: May 1, 2024
Discussion open until: Jul 27, 2024
ASCE Technical Topics:
- Algorithms
- Business management
- Engineering fundamentals
- Hybrid methods
- Infrastructure
- Mathematics
- Methodology (by type)
- Models (by type)
- Optimization models
- Personnel management
- Pipe blockage
- Pipe materials
- Pipeline management
- Pipeline systems
- Pipelines
- Pipes
- Practice and Profession
- Water and water resources
- Water management
- Water pipelines
- Water supply
- Water supply systems
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.