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Water Quality Sensor Placement: A Multi-Objective and Multi-Criteria Approach

Author

Listed:
  • Bruno Brentan

    (Federal University of Minas Gerais)

  • Silvia Carpitella

    (Czech Academy of Sciences)

  • Daniel Barros

    (Federal University of Minas Gerais)

  • Gustavo Meirelles

    (Federal University of Minas Gerais)

  • Antonella Certa

    (Università degli Studi di Palermo)

  • Joaquín Izquierdo

    (Universitat Politècnica de València)

Abstract

To satisfy their main goal, namely providing quality water to consumers, water distribution networks (WDNs) need to be suitably monitored. Only well designed and reliable monitoring data enables WDN managers to make sound decisions on their systems. In this belief, water utilities worldwide have invested in monitoring and data acquisition systems. However, good monitoring needs optimal sensor placement and presents a multi-objective problem where cost and quality are conflicting objectives (among others). In this paper, we address the solution to this multi-objective problem by integrating quality simulations using EPANET-MSX, with two optimization techniques. First, multi-objective optimization is used to build a Pareto front of non-dominated solutions relating contamination detection time and detection probability with cost. To assist decision makers with the selection of an optimal solution that provides the best trade-off for their utility, a multi-criteria decision-making technique is then used with a twofold objective: 1) to cluster Pareto solutions according to network sensitivity and entropy as evaluation parameters; and 2) to rank the solutions within each cluster to provide deeper insight into the problem when considering the utility perspectives.The clustering process, which considers features related to water utility needs and available information, helps decision makers select reliable and useful solutions from the Pareto front. Thus, while several works on sensor placement stop at multi-objective optimization, this work goes a step further and provides a reduced and simplified Pareto front where optimal solutions are highlighted. The proposed methodology uses the NSGA-II algorithm to solve the optimization problem, and clustering is performed through ELECTRE TRI. The developed methodology is applied to a very well-known benchmarking WDN, for which the usefulness of the approach is shown. The final results, which correspond to four optimal solution clusters, are useful for decision makers during the planning and development of projects on networks of quality sensors. The obtained clusters exhibit distinctive features, opening ways for a final project to prioritize the most convenient solution, with the assurance of implementing a Pareto-optimal solution.

Suggested Citation

  • Bruno Brentan & Silvia Carpitella & Daniel Barros & Gustavo Meirelles & Antonella Certa & Joaquín Izquierdo, 2021. "Water Quality Sensor Placement: A Multi-Objective and Multi-Criteria Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(1), pages 225-241, January.
    • Handle: RePEc:spr:waterr:v:35:y:2021:i:1:d:10.1007_s11269-020-02720-3
    DOI: 10.1007/s11269-020-02720-3
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    References listed on IDEAS

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    1. Bouyssou, Denis & Marchant, Thierry, 2015. "On the relations between ELECTRE TRI-B and ELECTRE TRI-C and on a new variant of ELECTRE TRI-B," European Journal of Operational Research, Elsevier, vol. 242(1), pages 201-211.
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    5. Symeon Christodoulou & Anastasis Gagatsis & Savvas Xanthos & Sofia Kranioti & Agathoklis Agathokleous & Michalis Fragiadakis, 2013. "Entropy-Based Sensor Placement Optimization for Waterloss Detection in Water Distribution Networks," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(13), pages 4443-4468, October.
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    Cited by:

    1. Mohammadi, Kamran, 2023. "Improved strategy management for WDNs: Integrated prioritization SWOT QSPM (IPSQ) method – Application to passive defense," Socio-Economic Planning Sciences, Elsevier, vol. 88(C).
    2. Seyed Farhan Moosavian & Daryoosh Borzuei & Abolfazl Ahmadi, 2022. "Cost Analysis of Water Quality Assessment Using Multi-Criteria Decision-Making Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(12), pages 4843-4862, September.
    3. Tianwei Mu & Yaqi Li & Ziyi Li & Luyue Wang & Haoqiang Tan & Chengzhi Zheng, 2021. "Improved Network Reliability Optimization Model with Head Loss for Water Distribution System," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(7), pages 2101-2114, May.
    4. Zukang Hu & Wenlong Chen & Beqing Chen & Debao Tan & Yu Zhang & Dingtao Shen, 2021. "Robust Hierarchical Sensor Optimization Placement Method for Leak Detection in Water Distribution System," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(12), pages 3995-4008, September.

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