Technical Papers
Jun 10, 2020

Multiphase DMA Design Methodology Based on Graph Theory and Many-Objective Optimization

Publication: Journal of Water Resources Planning and Management
Volume 146, Issue 8

Abstract

Partitioning a water distribution system (WDS) into district metered areas (DMAs) is a difficult task due to the complex WDS structure and simultaneous consideration of multiple constraints. Further, alternative metrics can define DMA goals, and expressing and quantifying those objectives in an efficient algorithm is also challenging. To address the multifaceted set of objectives, a multiphase DMA design method is developed. DMA feed pipes are identified as the primary flow paths in a branched network. In the methodology presented here, the feed pipe network is first laid out by determining node clusters and boundary pipes that maximize the dissimilarity of pressures and modularities between clusters and minimize the number of cuts between clusters while defining the number of DMAs closest to the desired number. In the methodology’s second phase, secondary DMA feed pipes are identified by minimizing the number of secondary feed pipes and maximizing the nodal excess energy while maintaining desired pressure. Finally, a postoptimization analysis compares the performance of the Pareto solutions based on their availability, water quality, and daily leakage. System availability is calculated based on the minimum cut-set method combined with a new pressure-driven analysis method. To accelerate the optimization algorithm, two strategies are applied: step-by-step optimization and reducing the decision variable searching space by considering desirable DMA characteristics. The effectiveness of the methods is examined by applying it to the C-Town and real B-Town water distribution networks. Results demonstrate that the search space reduction method effectively decomposes the full network into DMAs in the face of multiple hydraulic and water quality metrics.

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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.

Acknowledgments

This work was supported by the National Natural Science Foundation of China (No. 51508492). The first author gratefully acknowledge the China Scholarship Council for providing funds for his visit to the University of Arizona.

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. 2014. “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.
Charalambous, B. 2008. “Use of district metered areas coupled with pressure optimisation to reduce leakage.” Water Sci. Technol. Water Supply 8 (1): 57–62. https://doi.org/10.2166/ws.2008.030.
Chondronasios, A., K. Gonelas, V. Kanakoudis, M. Patelis, and P. Korkana. 2017. “Optimizing DMAs formation in a water pipe network: The water aging and the operating pressure factors.” J. Hydroinf. 19 (6): 890–899. https://doi.org/10.2166/hydro.2017.156.
Creaco, E., M. Cunha, and M. Franchini. 2019. “Using heuristic techniques to account for engineering aspects in modularity-based water distribution network partitioning algorithm.” J. Water Resour. Plann. Manage. 145 (12): 04019062. https://doi.org/10.1061/(ASCE)WR.1943-5452.0001129.
Creaco, E., and H. Haidar. 2019. “Multiobjective optimization of control valve installation and dma creation for reducing leakage in water distribution networks.” J. Water Resour. Plann. Manage. 145 (10): 04019046. https://doi.org/10.1061/(ASCE)WR.1943-5452.0001114.
Cullinane, M. J., K. E. Lansey, and L. W. Mays. 1992. “Optimization-availability-based design of water-distribution networks.” J. Hydraul. Eng. 118 (3): 420–441. https://doi.org/10.1061/(ASCE)0733-9429(1992)118:3(420).
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., M. Di Natale, R. Gargano, C. Giudicianni, R. Greco, and G. F. Santonastaso. 2018. “Performance of partitioned water distribution networks under spatial-temporal variability of water demand.” Environ. Model. Software 101 (Mar): 128–136. https://doi.org/10.1016/j.envsoft.2017.12.020.
Di Nardo, A., M. Di Natale, G. F. Santonastaso, V. G. Tzatchkov, and V. H. Alcocer-Yamanaka. 2014. “Water network sectorization based on graph theory and energy performance indices.” J. Water Resour. Plann. Manage. 140 (5): 620–629. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000364.
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.
Ferrari, G., D. Savic, and G. Becciu. 2014. “Graph-theoretic approach and sound engineering principles for design of districted metered areas.” J. Water Resour. Plann. Manage. 140 (12): 04014036. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000424.
Gheisi, A., M. Forsyth, and Gh Naser. 2016. “Water distribution systems reliability: A review of research literature.” J. Water Resour. Plann. Manage. 142 (11): 04016047. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000690.
Giudicianni, C., M. Herrera, A. Di Nardo, and K. Adeyeye. 2020. “Automatic multiscale approach for water networks partitioning into dynamic district metered areas.” Water Resour. Manage. 34 (2) 835–848. https://doi.org/10.1007/s11269-019-02471-w.
Giustolisi, O., and L. Ridolfi. 2014a. “A novel infrastructure modularity index for the segmentation of water distribution networks.” Water Resour. Res. 50 (10): 7648–7661. https://doi.org/10.1002/2014WR016067.
Giustolisi, O., and L. Ridolfi. 2014b. “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.
Grayman, W. M., R. Murray, D. A. Savic, and R. Farmani. 2016. “Redesign of water distribution systems for passive containment of contamination.” J. Am. Water Works Assoc. 108 (7): E381–E391. https://doi.org/10.5942/jawwa.2016.108.0105.
Hadka, D., and P. Reed. 2012. “Diagnostic assessment of search controls and failure modes in many-objective evolutionary optimization.” Evol. Comput. 20 (3): 423–452. https://doi.org/10.1162/EVCO_a_00053.
Hadka, D., and P. Reed. 2013. “BORG: An auto-adaptive many-objective evolutionary computing framework.” Evol. Comput. 21 (2): 231–259. https://doi.org/10.1162/EVCO_a_00075.
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.
He, G., T. Zhang, F. Zheng, and Q. Zhang. 2018. “An efficient multi-objective optimization method for water quality sensor placement within water distribution systems considering contamination probability variations.” Water Res. 143 (Oct): 165–175. https://doi.org/10.1016/j.watres.2018.06.041.
Kang, D., and K. Lansey. 2009. “Real-time demand estimation and confidence limit analysis for water distribution system.” J. Hydraul. Eng. 135 (10): 825–837. https://doi.org/10.1061/(ASCE)HY.1943-7900.0000086.
Kruskal, J. B. 1956. “On the shortest spanning subtree of a graph and the traveling salesman problem.” Proc. Am. Math. Soc. 7 (1): 48. https://doi.org/10.1090/S0002-9939-1956-0078686-7.
Laucelli, D. B., A. Simone, L. Berardi, and O. Giustolisi. 2017. “Optimal design of district metering areas for the reduction of leakage.” J. Water. Resour. Plann. Manage. 143 (6): 04017017. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000768.
Liu, J., and R. Han. 2018. “Spectral clustering and multicriteria decision for design of district metered areas.” J. Water Resour. Plann. Manage. 144 (5): 04018013. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000916.
Liu, J., and K. E. Lansey. 2018. “Optimal design of district metered areas based on graph theory and multi-objective optimization.” In Proc., 1st Int. WDSA/CCWI 2018 Joint Conf. Kingston, ON, Canada: Queen’s Univ.
Liu, J., and G. Yu. 2013. “Iterative methodology of pressure-dependent demand based on EPANET for pressure-deficient water distribution analysis.” J. Water Resour. Plann. Manage. 139 (1): 23–33. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000223.
Mahmoud, H. A., D. Savic, and A. Kapelan. 2017. “New pressure-driven approach for modeling water distribution networks.” J. Water Resour. Plann. Manage. 143 (8): 04017031. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000781.
Marchi, A., et al. 2014. “Battle of the water networks II.” J. Water Resour. Plann. Manage. 140 (7): 04014009. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000378.
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 69 (2): 026113. https://doi.org/10.1103/PhysRevE.69.026113.
Paez, D., Y. Fillion, and M. Hulley. 2018. “Battle of post-disaster response and restauration (BPDRR): Problem description and rules.” Accessed June 6, 2018. https://www.queensu.ca/wdsa-ccwi2018/problem-description-and-files.
Pesantez, J. E., E. Z. Berglund, and G. Mahinthakumar. 2019. “Multiphase procedure to design district metered areas for water distribution networks.” J. Water Resour. Plann. Manage. 145 (8): 04019031. https://doi.org/10.1061/(ASCE)WR.1943-5452.0001095.
Qi, Z., F. Zheng, D. Guo, T. Zhang, Y. Shao, T. Yu, K. Zhang, and H. R. Maier. 2018. “A Comprehensive framework to evaluate hydraulic and water quality impacts of pipe breaks on water distribution systems.” Water Resour. Res. 54 (10): 8174–8195. https://doi.org/10.1029/2018WR022736.
Rahman, A., and Z. Y. Wu. 2018. “Multistep simulation-optimization modeling approach for partitioning water distribution system into district meter areas.” J. Water Resour. Plann. Manage. 144 (5): 04018018. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000927.
Saldarriaga, J., J. Bohorquez, D. Celeita, L. Vega, D. Paez, D. Savic, G. Dandy, Y. Filion, W. Grayman, and Z. Kapelan. 2019. “Battle of the water networks district metered areas.” J. Water Resour. Plann. Manage. 145 (4): 04019002. https://doi.org/10.1061/(ASCE)WR.1943-5452.0001035.
Saldarriaga, J., D. Páez, J. Bohórquez, N. Páez, J. P. París, D. Rincón, C. Salcedo, and D. Vallejo. 2016. “Rehabilitation and leakage reduction on C-town using hydraulic criteria.” J. Water Resour. Plann. Manage. 142 (5): C4015013. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000600.
Santonastaso, G. F., A. Di Nardo, and E. Creaco. 2019. “Dual topology for partitioning of water distribution networks considering actual valve locations.” Urban Water J. 16 (7): 469–479. https://doi.org/10.1080/1573062X.2019.1669201.
Sayyed, M. A. H. A., R. Gupta, and T. T. Tanyimboh. 2015. “Noniterative application of EPANET for pressure dependent modelling of water distribution systems.” Water Resour. Manage. 29 (9): 3227–3242. https://doi.org/10.1007/s11269-015-0992-0.
Shinstine, D. S., I. Ahmed, and K. E. Lansey. 2002. “Reliability/availability analysis of municipal water distribution networks: Case studies.” J. Water Resour. Plann. Manage. 128 (2): 140–151. https://doi.org/10.1061/(ASCE)0733-9496(2002)128:2(140).
Siew, C., and T. T. Tanyimboh. 2012. “Pressure-dependent EPANET extension.” Water Resour. Manage. 26 (6): 1477–1498. https://doi.org/10.1007/s11269-011-9968-x.
Su, Y. C., L. W. Mays, N. Duan, and K. E. Lansey. 1987. “Reliability-based optimization model for water distribution systems.” J. Hydraul. Eng. 114 (12): 1539–1556. https://doi.org/10.1061/(ASCE)0733-9429(1987)113:12(1539).
Ulanicki, B., S. L. Prescott, and N. Shipley. 2003. “Analysis of district metered areas (DMAs) performance.” In Proc., CCWI 2003, Advances in Water Supply Management, 59–67. Lisse, Netherlands: Swets & Zeitlinger.
USEPA. 2002. Effects of water age on distribution system water quality. Washington, DC: USEPA.
Vasilic, Ž., M. Stanic, Z. Kapelan, D. Prodanovic, and B. Babic. 2020. “Uniformity and heuristics-based DeNSE method for sectorization of water distribution networks.” J. Water Resour. Plann. Manage. 146 (3): 04019079. https://doi.org/10.1061/(ASCE)WR.1943-5452.0001163.
Wagner, B. J. M., U. Shamir, and D. H. Marks. 1988. “Water distribution reliability: Simulation method.” J. Water Resour. Plann. Manage. 114 (3): 276–294. https://doi.org/10.1061/(ASCE)0733-9496(1988)114:3(276).
Wang, Q., M. Guidolin, D. Savic, and Z. Kapelan. 2015. “Two-objective design of benchmark problems of a water distribution system via MOEAs: Towards the best-known approximation of the true Pareto front.” J. Water Resour. Plann. Manage. 141 (3): 04014060. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000460.
Zhang, Q., Z. Y. Wu, M. Zhao, J. Qi, Y. Huang, and H. Zhao. 2017. “Automatic partitioning of water distribution networks using multiscale community detection and multiobjective optimization.” J. Water Resour. Plann. Manage. 143 (9): 04017057. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000819.
Zheng, F., A. R. Simpson, and A. C. Zecchin. 2011. “A combined NLP-differential evolution algorithm approach for the optimization of looped water distribution systems.” Water Resour. Res. 47 (8): W08531. https://doi.org/10.1029/2011WR010394.
Zheng, F., A. Zecchin, H. Maier, and A. Simpson. 2016. “Comparison of the searching behavior of NSGA-II, SAMODE, and Borg MOEAs applied to water distribution system design problems.” J. Water Resour. Plann. Manage. 142 (7): 04016017. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000650.

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Go to Journal of Water Resources Planning and Management
Journal of Water Resources Planning and Management
Volume 146Issue 8August 2020

History

Received: Sep 10, 2019
Accepted: Mar 16, 2020
Published online: Jun 10, 2020
Published in print: Aug 1, 2020
Discussion open until: Nov 10, 2020

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Associate Professor, Key Laboratory of Green Construction and Intelligent Maintenance for Civil Engineering of Hebei Province, Hebei Province Low-Carbon and Clean Building Heating Technology Innovation Center, Yanshan Univ., Qinhuangdao 066004, China (corresponding author). ORCID: https://orcid.org/0000-0002-9333-3415. Email: [email protected]
Kevin E. Lansey [email protected]
Professor, Dept. of Civil and Architectural Engineering and Mechanics, Univ. of Arizona, Tucson, AZ 85721. Email: [email protected]

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