Uniformity and Heuristics-Based DeNSE Method for Sectorization of Water Distribution Networks
Publication: Journal of Water Resources Planning and Management
Volume 146, Issue 3
Abstract
Sectorization of a water distribution network (WDN) into district metered areas (DMAs) is a proven solution for proactive leakage control. Traditionally, WDN sectorization is conducted by local experts using a trial-and-error approach, often resulting in the identification of arbitrary solutions. Some recently published methods try to improve WDN sectorization by automating the process, especially by using optimization. Various sectorization criteria, constraints, and limitations are introduced, which often fail to consider the issues faced by poorly managed WDNs such as limited funds and shortage of water balance data. These methods also have poor computational efficiency imposed by optimization methods used. This paper presents a new distribution network sectorization method (DeNSE), that overcomes these deficiencies. This method is based on a heuristic procedure in which WDN sectorization is driven by efficient tracking of water balance data and determining the lowest cost investment needed to maintain the same level of operational performance. The above-mentioned set of criteria is particularly well suited for initial sectorization of WDNs when major uncertainties in water balance data often lead to poor management decisions. The DeNSE method is validated and benchmarked against other sectorization methodologies in a case study of a large, real-world WDN. The results show that DeNSE can identify sound, realistic sectorization solutions that are in some respects better than corresponding solutions reported in the literature. DeNSE also enables high computational efficiency, ensuring its applicability to real-world WDNs.
Get full access to this article
View all available purchase options and get full access to this article.
Data Availability Statement
Some or all data, models, or code generated or used during the study are available in a repository or online in accordance with funder data retention policies (EPANET input file for case study network is available online at http://emps.exeter.ac.uk/engineering/research/cws/downloads/benchmarks/). Some or all data, models, or code generated or used during the study are available from the corresponding author by request (source code developed for implementation of DeNSE method for sectorization).
References
Alvisi, S. 2015. “A new procedure for optimal design of district metered areas based on the multilevel balancing and refinement algorithm.” Water Resour. Manage. 29 (12): 4397–4409. https://doi.org/10.1007/s11269-015-1066-z.
Alvisi, S., and M. Franchini. 2014a. “A heuristic procedure for the automatic creation of district metered areas in water distribution systems.” Urban Water J. 11 (2): 137–159. https://doi.org/10.1080/1573062X.2013.768681.
Alvisi, S., and M. Franchini. 2014b. “Water distribution systems: Using linearized hydraulic equations within the framework of ranking-based optimization algorithms to improve their computational efficiency.” Environ. Modell. Software 57 (Jul): 33–39. https://doi.org/10.1016/j.envsoft.2014.03.012.
Babić, B., M. Stanić, D. Prodanović, B. Džodanović, and A. Dukić. 2014. “Reducing uncertainty of infrastructure leakage index—A case study.” Procedia Eng. 89: 1577–1584. https://doi.org/10.1016/j.proeng.2014.11.459.
Brentan, B. M., E. Campbell, G. L. Meirelles, E. Luvizotto, and J. Izquierdo. 2017. “Social network community detection for DMA creation: Criteria analysis through multilevel optimization.” Math. Prob. Eng. 2017: 1–12. https://doi.org/10.1155/2017/9053238.
Burrows, R., G. Crowder, and J. Zhang. 2000. “Utilisation of network modelling in the operational management of water distribution systems.” Urban Water 2 (2): 83–95. https://doi.org/10.1016/S1462-0758(00)00046-7.
Butler, D. 2000. Leakage detection and management. Cwambran, UK: Palmer Environmental Ltd.
Campbell, E., J. Izquierdo, I. Montalvo, and R. Perez-Garcia. 2016. “A novel water supply network sectorization methodology based on a complete economic analysis, including uncertainties.” Water 8 (5): 179. https://doi.org/10.3390/w8050179.
Chianese, S., A. D. Nardo, M. D. Natale, C. Giudicianni, D. Musmarra, and D. Ingegneria. 2017. “DMA optimal layout for protection of water distribution networks from malicious attack.” In Vol. 1 of Proc., CRITIS 2017: Int. Conf. on Critical Information Infrastructures Security, 84–96. New York: Springer.
Ciaponi, C., E. Murari, and S. Todeschini. 2016. “Modularity-based procedure for partitioning water distribution systems into independent districts.” Water Resour. Manage. 30 (6): 2021–2036. https://doi.org/10.1007/s11269-016-1266-1.
Clauset, A., M. Newman, and C. Moore. 2004. “Finding community structure in very large networks.” Phys. Rev. E: Stat. Nonlinear Soft Matter Phys. 70 (6): 1–6. https://doi.org/10.1103/PhysRevE.70.066111.
De Paola, F., N. Fontana, E. Galdiero, M. Giugni, D. Savic, and G. Sorgenti Degli Uberti. 2014. “Automatic multi-objective sectorization of a water distribution network.” Procedia Eng. 89: 1200–1207. https://doi.org/10.1016/j.proeng.2014.11.250.
Deuerlein, J. W. 2008. “Decomposition model of a general water supply network graph.” J. Hydraul. Eng. 134 (6): 822–832. https://doi.org/10.1061/(ASCE)0733-9429(2008)134:6(822).
Diao, K., Y. Zhou, and W. Rauch. 2013. “Automated creation of district metered area boundaries in water distribution systems.” J. Water Resour. Plann. Manage. 139 (2): 184–190. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000247.
Di Nardo, A., and M. Di Natale. 2011. “A heuristic design support methodology based on graph theory for district metering of water supply networks.” Eng. Optim. 43 (2): 193–211. https://doi.org/10.1080/03052151003789858.
Di Nardo, A., M. Di Natale, C. Giudicianni, G. F. Santonastaso, V. Tzatchkov, and M. Rodriguez. 2017. “Economic and energy criteria for district meter areas design of water distribution networks.” Water 9 (7): 463. https://doi.org/10.3390/w9070463.
Di Nardo, A., M. Di Natale, G. F. Santonastaso, and S. Venticinque. 2013. “An automated tool for smart water network partitioning.” Water Resour. Manage. 27 (13): 4493–4508. https://doi.org/10.1007/s11269-013-0421-1.
Di Nardo, A., C. Giudicianni, R. Greco, and G. F. Santonastaso. 2018. “Applications of graph spectral techniques to water distribution network management.” Water 10 (1): 1–16. https://doi.org/10.3390/w10010045.
Farley, M. 2001. “Leakage management and control: A best practice training manual.” Accessed November 21, 2019. http://whqlibdoc.who.int/hq/2001/WHO_SDE_WSH_01.1_pp1-98.pdf.
Ferrari, G., D. Savic, and G. Becciu. 2014. “A graph theoretic approach and sound engineering principles for design of district metered areas.” J. Water Resour. Plann. Manage. 140 (12): 1–13. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000424.
Fortunato, S. 2010. “Community detection in graphs.” Phys. Rep. 486 (3–5): 75–174. https://doi.org/10.1016/j.physrep.2009.11.002.
Gabow, H. N. 2000. “Path-based depth-rst search for strong and biconnected components 1 introduction 2 strong components.” Inf. Process. Lett. 74 (3–4): 107–114. https://doi.org/10.1016/S0020-0190(00)00051-X.
Giudicianni, C., A. D. Nardo, M. D. Natale, R. Greco, G. F. Santonastaso, and A. S. Id. 2018. “Topological taxonomy of water distribution networks.” Water 10 (4): 1–19. https://doi.org/10.3390/w10040444.
Giustolisi, O., and L. Ridolfi. 2014. “New modularity-based approach to segmentation of water distribution networks.” J. Hydraul. Eng. 140 (10): 04014049 https://doi.org/10.1061/(ASCE)HY.1943-7900.0000916.
Gomes, R., S. S. Marques, and S. Joaquim. 2012. “Decision support system to divide a large network into suitable district metered areas.” Water Sci. Technol. 65 (9): 1667–1675. https://doi.org/10.2166/wst.2012.061.
Grayman, W., R. Murray, and D. Savic. 2009. “Effects of redesign of water systems for security and water quality factors.” In Proc., World Environmental and Water Resources Congress 2009, 504–514. Reston, VA: ASCE.
Hajebi, S., E. Roshani, N. Cardozo, S. Barrett, A. Clarke, and S. Clarke. 2016. “Water distribution network sectorisation using graph theory and many-objective optimization.” J. Hydroinf. 18 (1): 77–95. https://doi.org/10.2166/hydro.2015.144.
Herrera, M., S. Canu, A. Karatzoglou, and J. Izquierdo. 2010a. “An approach to water supply clusters by semi-supervised learning.” In Proc., Int. Environmental Modelling and Software Society (iEMSs) 2010 Int. Congress on Environmental Modelling and Software. Reston, VA: United States Geological Survey.
Herrera, M., J. Izquierdo, R. Pérez-García, and D. Ayala-Cabrera. 2010b. “Water supply clusters by multi-agent based approach.” In Proc., Water Distribution System Analysis 2010–WDSA 2010, 861–869. Reston, VA: ASCE.
Ivetić, D., Ž. Vasilić, M. Stanić, and D. Prodanović. 2013. “Optimizacija mreža pod pritiskom modeliranih ΔQ metodom.” Vodoprivreda 264–266 (4–6): 265–274.
Jungnickel, D. 2005. Graphs, networks and algorithms. 2nd ed. Edited by M. Bronstein, A. Cohen, H. Cohen, D. Eisenbud, and B. Sturmfels. Berlin: Springer.
Laucelli, D. B., A. Simone, L. Berardi, and O. Giustolisi. 2016. “Optimal design of district metering areas.” Procedia Eng. 162 (2014): 403–410. https://doi.org/10.1016/j.proeng.2016.11.081.
Morrison, J., S. Tooms, and D. Rogers. 2007. DMA management guidance notes. London: International Water Association.
Newman, M. E. J., and M. Girvan. 2004. “Finding and evaluating community structure in networks.” Phys. Rev. E: Stat. Nonlinear Soft Matter Phys. 69 (2): 1–15. https://doi.org/10.1103/PhysRevE.69.026113.
Ostfeld, A., et al. 2008. “The battle of the water sensor networks (BWSN): A design challenge for engineers and algorithms.” J. Water Resour. Plann. Manage. 134 (6): 556–568. https://doi.org/10.1061/(ASCE)0733-9496(2008)134:6(556).
Perelman, L., M. Allen, A. Preis, M. Iqbal, and A. J. Whittle. 2015. “Automated sub-zoning of water distribution systems.” Environ. Modell. Software 65 (Mar): 1–14. https://doi.org/10.1016/j.envsoft.2014.11.025.
Perelman, L., and A. Ostfeld. 2012. “Water-distribution systems simplifications through clustering.” J. Water Resour. Plann. Manage. 138 (3): 218–229. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000173.
Scarpa, F., A. Lobba, and G. Becciu. 2016. “Elementary DMA design of looped water distribution networks with multiple sources.” J. Water Resour. Plann. Manage. 142 (6): 04016011. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000639.
Sedgewick, R., and K. Wayne. 2011. Algorithms. 4th ed. Boston: Addison-Wesley.
Tarjan, R. 1972. “Depth-first search and linear graph algorithms.” SIAM J. Comput. 1 (2): 146–160. https://doi.org/10.1137/0201010.
Todini, E. 2000. “Looped water distribution networks design using a resilience index based heuristic approach.” Urban Water 2 (2): 115–122. https://doi.org/10.1016/S1462-0758(00)00049-2.
Tzatchkov, V., V. Alcocer-Yamanaka, and V. Bourguett Ortíz. 2006. “Graph theory based algorithms for water distribution network sectorization projects.” In Proc., Water Distribution Systems Analysis Symp. 2006, 1–15. Reston, VA: ASCE.
UK Water Industry Research. 1999. A manual of DMA practice. London: UK Water Industry Research Limited.
Vasilic, Z. 2018. “Decision support algorithms for sectorization of water distribution networks.” Ph.D. thesis, Faculty of Civil Engineering, Dept. for Hydraulic and Environmental Engineering, Univ. of Belgrade.
Vasilić, Ž., M. Stanić, D. Prodanović, and Z. Kapelan. 2016. “Network sectorisation through aggregation of strong connected components.” In Proc., 18th Conf. on Water Distribution System Analysis, WDSA 2016. Amsterdam, Netherlands: Elsevier.
WAA and WRC (Water Authorities Association and Water Research Centre). 1985. Leakage control policy & practice. London: Water Authorities Association.
Zhang, K., H. Yan, H. Zeng, K. Xin, and T. Tao. 2019. “A practical multi-objective optimization sectorization method for water distribution network.” Sci. Total Environ. 656 (Mar): 1401–1412. https://doi.org/10.1016/j.scitotenv.2018.11.273.
Zhang, Q., Z. Wu, M. Zhao, and J. Qi. 2017. “Automatic partitioning of water distribution networks using multiscale community detection and multiobjective optimization.” J. Water Resour. Plann. Manage. 143 (9): 1–14. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000819.
Information & Authors
Information
Published In
Copyright
©2019 American Society of Civil Engineers.
History
Received: Dec 10, 2018
Accepted: Jul 23, 2019
Published online: Dec 21, 2019
Published in print: Mar 1, 2020
Discussion open until: May 21, 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.