Reliability Assessment Model for Water Distribution Networks
Publication: Journal of Pipeline Systems Engineering and Practice
Volume 11, Issue 2
Abstract
The aging water distribution networks in the US are approaching the end of their useful life, and more than 240,000 pipeline breaks are estimated to occur every year, which corresponds to an average of 25 breaks (or 100 mi) per year. Due to financial restrictions to maintain and rehabilitate their water distribution networks, many municipalities need to assess the reliability of their network and properly plan for their maintenance. Previous studies have mainly focused on the reliability assessment of individual network components such as pipes. Moreover, very limited network reliability models addressed the importance of network segments with customer accessibility to drinking water. Therefore, a model is developed in this study to evaluate the reliability of water distribution networks taking into consideration the weight of the importance of their segments. A modified Preference Ranking Organization METhod for Enrichment Evaluations (PROMETHEE) technique was applied to obtain the weight of the importance of segments using expert opinions. The working and failing states of pipes and segments were determined by developing the network’s failure tree, and their impacts on the network reliability were estimated. The evidential reasoning was applied to aggregate the effects of failure and working states of each component on the whole network and its segments. The failure rate and reliability of each component were determined based on what is available in the literature. Results obtained from PROMETHEE application showed that network segments of health care facilities are first in rank of the highest importance. Hence, maintenance and rehabilitation of these segments shall receive the top priority. A network in a Canadian city, which was evaluated using the proposed model, was found to have a reliability index of 0.93.
Get full access to this article
View all available purchase options and get full access to this article.
Data Availability Statement
All data, models, and code generated or used during the study appear in the published article.
Acknowledgments
This publication was made possible by NPRP Grant No. (NPRP4-529-2-193) from the Qatar National Research Fund (a member of The Qatar Foundation). The statements made in this study are solely the responsibility of the authors.
References
Abu-Taleb, M., and B. Mareschal. 1995. “Water resources planning in the Middle East: Application of the PROMETHEE V multicriteria method.” Eur. J. Oper. Res. 81 (3): 500–511. https://doi.org/10.1016/0377-2217(94)00007-Y.
Al-Barqawi, H., and T. Zayed. 2006a. “Assessment model of water main conditions.” In Proc., Pipeline Division Specialty Conf, 1–8. Reston, VA: ASCE.
Al-Barqawi, H., and T. Zayed. 2006b. “Condition rating model for underground infrastructure sustainable water mains.” J. Perform. Constr. Facil. 20 (2): 126–135. https://doi.org/10.1061/(ASCE)0887-3828(2006)20:2(126).
Al-Barqawi, H., and T. Zayed. 2008. “Infrastructure management: Integrated AHP/ANN model to evaluate municipal water mains’ performance.” J. Infrastruct. Syst. 14 (4): 305–318. https://doi.org/10.1061/(ASCE)1076-0342(2008)14:4(305).
Al-Kloub, B., T. Al-Shemmeri, and A. Pearman. 1997. “The role of weights in multi-criteria decision aid and the ranking of water projects in Jordan.” Eur. J. Oper. Res. 99 (2): 278–288. https://doi.org/10.1016/S0377-2217(96)00051-3.
Al-Rashdan, D., B. Al-Kloub, A. Dean, and T. Al-Shemmeri. 1999. “Environmental impact assessment and ranking the environmental projects in Jordan.” Eur. J. Oper. Res. 118 (1): 30–45. https://doi.org/10.1016/S0377-2217(97)00079-9.
ASCE. 2017. “Report card for America’s infrastructure.” Accessed December 5, 2018. http://www.infrastructurereportcard.org.
AWWA (American Water Works Association). 2012. “Buried no longer: Confronting America’s water infrastructure challenge.” Accessed June 5, 2019. http://www.allianceforwaterefficiency.org/uploadedFiles/Resource_Center/Landing_Pages/AWWA-BuriedNoLonger-2012.pdf.
Brans, J. 1982. Lingenierie de la decision. Elaboration d’instruments daide a la decision. Methode PROMETHEE. Laide a la Decision: Nature, Instruments et Perspectives Davenir, 183–214. Quebec: Presses de Universite Laval.
Brans, J., and B. Mareschal. 1992. “PROMETHEE V-MCDM problems with segmentation constraints.” INFOR: Inf. Sys. Oper. Res. 30 (2): 85–96. https://doi.org/10.1080/03155986.1992.11732186.
Brans, J., and B. Mareschal. 1995. “The PROMETHEE VI procedure. How to differentiate hard from soft multicriteria problems.” J. Decis. Syst. 4 (3): 213–223. https://doi.org/10.1080/12460125.1995.10511652.
Brans, J., and P. Vincke. 1985. “Note—A preference ranking organization method (the PROMETHEE method for multiple criteria decision making).” Manage. Sci. 31 (6): 647–656. https://doi.org/10.1287/mnsc.31.6.647.
El Chanati, H. 2014. “Performance assessment of water network infrastructure.” Master thesis, Dept. of Building, Civil and Environmental Engineering, Construction Management Program, Concordia Univ.
El Chanati, H., M. El-Abbasy, F. Mosleh, A. Senouci, M. Abouhamad, I. Gkountis, and T. Zayed. 2016. “Multi-criteria decision making models for water pipelines.” J. Perform. Constr. Facil. 30 (4): 04015090. https://doi.org/10.1061/(ASCE)CF.1943-5509.0000842.
Fares, H., and T. Zayed. 2010. “Hierarchical fuzzy expert system for risk of failure of water mains.” J. Pipeline Syst. Eng. Pract. 1 (1): 53–62. https://doi.org/10.1061/(ASCE)PS.1949-1204.0000037.
Geem, Z. 2003. “Window-based decision support system for the water pipe condition assessment using artificial neural network.” In Proc., World Water and Environmental Resources Congress, 1–6. Reston, VA: ASCE.
Geem, Z., C. Tseng, J. Kim, and C. Bae. 2007. “Trenchless water pipe condition assessment using artificial neural network.” In Proc., Int. Conf. on Pipeline Engineering and Construction, 1–9. Reston, VA: ASCE.
Giustolisi, O., D. Laucelli, and A. Dragan. 2006. “Development of rehabilitation plans for water mains replacement considering risk and cost-benefit assessment.” J. Civ. Eng. Environ. Syst. 23 (3): 175–190. https://doi.org/10.1080/10286600600789375.
Hokkanen, J., and P. Salminen. 1997. “Locating a waste treatment facility by multicriteria analysis.” J. Multi-Criteria Decis. Anal. 6 (3): 175–184. https://doi.org/10.1002/(SICI)1099-1360(199705)6:3%3C175::AID-MCDA150%3E3.0.CO;2-%23.
Kabir, G., R. Sadiq, and S. Tesfamariam. 2013. “A review of multi-criteria decision-making methods for infrastructure management.” Struct. Infrastruct. Eng. 10 (9): 1176–1210. https://doi.org/10.1080/15732479.2013.795978.
Kanakoudis, V. 2004. “A troubleshooting manual for handling operational problems in water pipe networks.” J. Water Supply Res. Technol. Aqua. 53 (2): 109–124. https://doi.org/10.2166/aqua.2004.0010.
Kanakoudis, V., and D. Tolikas. 2004. “Assessing the performance level of a water system.” Water Air Soil Pollut.: Focus. 4 (4–5): 307–318. https://doi.org/10.1023/B:WAFO.0000044807.41719.c7.
Kanakoudis, V., and S. Tsitsifli. 2012. “Water pipe network reliability assessment using the DAC method.” Desalin. Water Treat. 33 (1–3): 97–106. https://doi.org/10.5004/dwt.2011.2631.
Karimian, F., H. Elsawah, T. Zayed, O. Moselhi, and A. Al Hawari. 2015. “Forecasting breakage rate in water distribution networks using evolutionary polynomial regression.” In Proc., ICSC15—The Canadian Society for Civil Engineering’s 5th Int./11th Construction Specialty Conf., 1–10. Montreal: Canadian Society for Civil Engineering.
Kleiner, Y. and B. Rajani. 2000. “Considering time-dependent factors in the statistical prediction of water main breaks.” In Proc. American Water Works Association Infrastructure Conf., 1–12. Ottawa: National Research Council Canada.
Kleiner, Y., and B. Rajani. 2001. “Comprehensive review of structural deterioration of water mains: Physical models.” J. Urban Water. 3 (3): 151–164. https://doi.org/10.1016/S1462-0758(01)00032-2.
Laucelli, D., and O. Giustolisi. 2015. “Vulnerability assessment of water distribution networks under seismic actions.” J. Water Resour. Plann. Manage. 141 (6): 04014082. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000478.
Mareschal, B., and J. Brans. 1988. “Geometrical representations for MCDA.” Eur. J. Oper. Res. 34 (1): 69–77. https://doi.org/10.1016/0377-2217(88)90456-0.
NRC (National Research Council Canada). 2003. Deterioration and inspection of water distribution systems. Ottawa: National Guide to Sustainable Municipal Infrastructure.
Özelkan, E., and L. Duckstein. 1996. “Analysing water resources alternatives and handling criteria by multi criterion decision techniques.” J. Environ. Manage. 48 (1): 69–96. https://doi.org/10.1006/jema.1996.0066.
Parvizsedghy, L., I. Gkountis, A. Senouci, T. Zayed, M. Alsharqawi, H. El Chanati, M. El-Abbasy, and F. Mosleh. 2017. “Deterioration assessment models for water pipelines.” Int. J. Civ. Environ. Eng. 11 (7): 1013–1022. https://doi.org/10.5281/zenodo.1132579.
Raju, K., L. Duckstein, and C. Arondel. 2000. “Multicriterion analysis for sustainable water resources planning: A case study in Spain.” Water Resour. Manage. 14 (6): 435–456. https://doi.org/10.1023/A:1011120513259.
Semaan, N. 2006. “Subway station diagnosis index (SSDI): A condition assessment model.” Master thesis, Dept. of Building, Civil and Environmental Engineering, Construction Management Program, Concordia Univ.
Tsitsifli, S., and V. Kanakoudis. 2010. “Predicting the behavior of a pipe network using the “critical z-score” as its performance indicator.” Desalination. 250 (1): 258–265. https://doi.org/10.1016/j.desal.2009.09.042.
Wang, C., Z. Niu, H. Jia, and H. Zhang. 2010. “An assessment model of water pipe condition using bayesian inference.” J. Zhejiang Univ. Sci. A. 11 (7): 495–504. https://doi.org/10.1631/jzus.A0900628.
Wang, Y., T. Zayed, and O. Moselhi. 2009. “Prediction models for annual break rates of water mains.” J. Perform. Constr. Facil. 23 (1): 47–54. https://doi.org/10.1061/(ASCE)0887-3828(2009)23:1(47).
Yan, J. M., and K. Vairavamoorthy. 2003. “Fuzzy approach for pipe condition assessment.” In Proc., Pipeline Engineering and Construction Int. Conf., 466–476. Reston, VA: ASCE.
Zhou, Y., K. Vairavamoorthy, and F. Grimshaw. 2009. “Development of a fuzzy-based pipe condition assessment model using PROMETHEE.” In Proc., 29th World Environmental and Water Resources Congress, 1–10. Reston, VA: ASCE.
Information & Authors
Information
Published In
Copyright
©2019 American Society of Civil Engineers.
History
Received: Feb 9, 2019
Accepted: Aug 8, 2019
Published online: Dec 30, 2019
Published in print: May 1, 2020
Discussion open until: May 30, 2020
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.