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Automatic Multiscale Approach for Water Networks Partitioning into Dynamic District Metered Areas

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Abstract

Water distribution systems (WDSs) today are expected to continuously provide clean water while meeting users demand, and pressure requirements. To accomplish these targets is not an easy task due to extreme weather events, operative accidents and intentional attacks; as well as the progressive deterioration of the WDS assets. Therefore, water utilities should be ready to deal with a range of disruption scenarios such as abrupt variations on the water demand e.g. caused by pipe bursts or topological changes in the water network. This paper presents a novel methodology to automatically split a WDS into self-adapting district metered areas (DMAs) of different size in response to such scenarios. Complex Networks Theory is proposed for creating novel multiscale network layouts for a WDS. This makes it possible to automatically define the dynamic partitioning of WDSs to support further DMA aggregation / disaggregation operations. A real, already partitioned, water utility network shows the usefulness of an adaptive partitioning when the network is affected by an abnormal increase of the peak demand of up to 15%. The dynamic DMA reuses the assets of the static partitioning and, in this case, up to the 82% of resilience is restored using 94% of the assets already installed. The results also show that the overall computational and economic management costs are reduced compared to the static DMA partition while the hydraulic performance of the WDS is simultaneously preserved.

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References

  • Alvisi S (2015) A new procedure for optimal design of district metered areas based on the multilevel balancing and refinement algorithm. Water Resour Manag 29 (12):4397–4409

    Article  Google Scholar 

  • Azevedo BB, Saurin TA (2018) Losses in water distribution systems: a complexity theory perspective. Water Resour Manag 32(9):2919–2936

    Article  Google Scholar 

  • Bair E (2013) Semi-supervised clustering methods. Wiley Interdisciplinary Reviews: Computational Statistics 5(5):349–361

    Article  Google Scholar 

  • Charalambous B (2008) Use of district metered areas coupled with pressure optimisation to reduce leakage. Water Sci Technol Water Supply 8(1):57–62

    Article  Google Scholar 

  • Ciaponi C, Murari E, Todeschini S (2016) Modularity-based procedure for partitioning water distribution systems into independent districts. Water Resour Manag 30(6):2021–2036

    Article  Google Scholar 

  • Ciaponi C, Creaco E, Di Nardo A, Di Natale M, Giudicianni C, Musmarra D, Santonastaso GF (2019) Reducing impacts of contamination in water distribution networks: a combined strategy based on network partitioning and installation of water quality sensors. Water 11(6):1315

    Article  Google Scholar 

  • Deuerlein JW (2008) Decomposition model of a general water supply network graph. J Hydraul Eng 134(6):822–832

    Article  Google Scholar 

  • Di Nardo A, Di Natale M, Gargano R, Giudicianni C, Greco R, Santonastaso GF (2018) Performance of partitioned water distribution networks under spatial-temporal variability of water demand. Environmental Modelling & Software 101:128–136

    Article  Google Scholar 

  • Farah E, Shahrour I (2017) Leakage detection using smart water system: combination of water balance and automated minimum night flow. Water Resour Manag 31(15):4821–4833

    Article  Google Scholar 

  • Feng J, Zhang H (2006) Algorithm of pipeline leak detection based on discrete incremental clustering method. In: International conference on intelligent computing. Springer, pp 602–607

  • Ferrari G, Savic D, Becciu G (2013) Graph-theoretic approach and sound engineering principles for design of district metered areas. J Water Resour Plan Manag 140(12):04014036

    Article  Google Scholar 

  • Fortunato S, Hric D (2016) Community detection in networks: a user guide. Phys Rep 659:1–44

    Article  Google Scholar 

  • Girvan M, Newman M (2002) Community structure in social and biological networks. Proc Natl Acad Sci USA 99:7821–7826

    Article  Google Scholar 

  • Giudicianni C, Di Nardo A, Di Natale M, Greco R, Santonastaso GF, Scala A (2018) Topological taxonomy of water distribution networks. Water 10 (4):444

    Article  Google Scholar 

  • Goldberg DE, Holland JH (1988) Genetic algorithms and machine learning. Machine Learning 3(2):95–99

    Article  Google Scholar 

  • Gomes R, Marques AS, Sousa J (2013) District metered areas design under different decision makers’ options: cost analysis. Water Resour Manag 27(13):4527–4543

    Article  Google Scholar 

  • Grayman WM, Murray R, Savic DA (2009) Effects of redesign of water systems for security and water quality factors. In: World environmental and water resources congress 2009: Great Rivers, pp 1–11

  • Herrera M, Canu S, Karatzoglou A, Pérez-García R, Izquierdo J (2010) An approach to water supply clusters by semi-supervised learning. In: Congress on environmental modelling and software, 5th 409 biennial meeting, Ottawa, Canada, BYU ScholarsArchive, p 190

  • Herrera M, Izquierdo J, Pérez-García R, Montalvo I (2012) Multi-agent adaptive boosting on semi-supervised water supply clusters. Advances in Engineering Software 50:131–136

    Article  Google Scholar 

  • Herrera M, Abraham E, Stoianov I (2016) A graph-theoretic framework for assessing the resilience of sectorised water distribution networks. Water Resour Manag 30(5):1685–1699

    Article  Google Scholar 

  • Housh M, Ohar Z (2018) Model-based approach for cyber-physical attack detection in water distribution systems. Water Research 139:132–143

    Article  Google Scholar 

  • Kirstein JK, Albrechtsen HJ, Rygaard M (2014) Simplification of water distribution network simulation by topological clustering-investigation of its potential use in copenhagen’s water supply monitoring and contamination contingency plans. Procedia Eng 89:1184–1191

    Article  Google Scholar 

  • Klise KA, Phillips CA, Janke RJ (2013) Two-tiered sensor placement for large water distribution network models. J Infrastruct Syst 19(4):465–473

    Article  Google Scholar 

  • Kulis B, Basu S, Dhillon I, Mooney R (2009) Semi-supervised graph clustering: a kernel approach. Machine Learning 74(1):1–22

    Article  Google Scholar 

  • Perelman L, Ostfeld A (2011) Topological clustering for water distribution systems analysis. Environmental Modelling & Software 26(7):969–972

    Article  Google Scholar 

  • Perelman LS, Allen M, Preis A, Iqbal M, Whittle AJ (2015) Automated sub-zoning of water distribution systems. Environmental Modelling & Software 65:1–14

    Article  Google Scholar 

  • Pesantez JE, Berglund EZ, Mahinthakumar G (2019) Multiphase procedure to design district metered areas for water distribution networks. J Water Resour Plan Manag 145(8):04019031

    Article  Google Scholar 

  • Saldarriaga J, Bohorquez J, Celeita D, Vega L, Paez D, Savic D, Dandy G, Filion Y, Grayman W, Kapelan Z (2019) Battle of the water networks district metered areas. J Water Resour Plan Manag 145(4):040 19002

    Article  Google Scholar 

  • Scarpa F, Lobba A, Becciu G (2016) Elementary dma design of looped water distribution networks with multiple sources. J Water Resour Plan Manag 142 (6):04016011

    Article  Google Scholar 

  • Taillefond N, Wolkenhauer O (2002) Fuzzy clustering and classification for automated leak detection systems. IFAC Proceedings 35(1):407–411

    Article  Google Scholar 

  • Taormina R, Galelli S (2018) Deep-learning approach to the detection and localization of cyber-physical attacks on water distribution systems. J Water Resour Plan Manag 144(10):04018065

    Article  Google Scholar 

  • Todini E (2000) Looped water distribution networks design using a resilience index based heuristic approach. Urban Water 2(2):115–122

    Article  Google Scholar 

  • Water Industry Research Ltd (1999) A manual of dma practice. London, UK Water Industry Research

  • Wright R, Stoianov I, Parpas P (2014a) Dynamic topology in water distribution networks. Procedia Engineering 70:1735–1744

  • Wright R, Stoianov I, Parpas P, Henderson K, King J (2014b) Adaptive water distribution networks with dynamically reconfigurable topology. J Hydroinf 16 (6):1280–1301

  • Wu Y, Liu S, Wu X, Liu Y, Guan Y (2016) Burst detection in district metering areas using a data driven clustering algorithm. Water research 100:28–37

    Article  Google Scholar 

  • Xin K, Tao T, Li S, Yan H (2017) Contamination accidents in China’s drinking water distribution networks: status and countermeasures. Water Policy 19 (1):13–27

    Article  Google Scholar 

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Acknowledgements

The authors wish to express their gratitude to Water Efficiency Network (http://www.watefnetwork.co.uk) for supporting this research.

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Correspondence to Carlo Giudicianni.

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Giudicianni, C., Herrera, M., di Nardo, A. et al. Automatic Multiscale Approach for Water Networks Partitioning into Dynamic District Metered Areas. Water Resour Manage 34, 835–848 (2020). https://doi.org/10.1007/s11269-019-02471-w

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  • DOI: https://doi.org/10.1007/s11269-019-02471-w

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