Research Article
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Year 2020, Volume: 38 Issue: 3, 1481 - 1494, 05.10.2021

Abstract

References

  • [1] Fares, H.A., (2008). Evaluating the Risk of Water Main Failure Using a Hierarchical Fuzzy Expert System. Masters thesis, Concordia University. 1–11.
  • [2] Sargaonkar, A., (2009). Risk assessment study for water supply network using GIS. Aqua - Journal of Water Supply: Research and Technology, 57: 355–360.
  • [3] Tanyimboh, T.T and Kalungi, P., (2009). Multicriteria assessment of optimal design, rehabilitation and upgrading schemes for water distribution networks. Civil Engineering and Environmental Systems, 26: 117–140.
  • [4] Francisque, A., (2009). Prioritizing monitoring locations in a water distribution network: A fuzzy risk approach. Journal of Water Supply: Research and Technology - AQUA, 58: 488–509.
  • [5] Morais, D.C and Almeida, A.T. (2010). Water network rehabilitation : A group decision-making approach. WaterSA, 36: 487–494.
  • [6] Tsitsifli, S, Kanakoudis, V and Bakouros, I., (2011). Pipe Networks Risk Assessment Based on Survival Analysis. Water Resources Management, 25: 3729–3746.
  • [7] Ammar, M.A, Moselhi, O and Zayed, T.M., (2012). Decision support model for selection of rehabilitation methods of water mains. Structure and Infrastructure Engineering. 8: 847–855.
  • [8] Ennaouri, I and Fuamba, M., (2013). New Integrated Condition-Assessment Model for Combined Storm-Sewer Systems. Journal of Water Resources Planning and Management, 139: 53–64.
  • [9] Francisque, A., (2014). A decision support tool for water mains renewal for small to medium sized utilities: A risk index approach. Journal of Water Supply: Research and Technology - AQUA, 63: 281–302.
  • [10] Li, Z., (2014). Water pipe condition assessment: A hierarchical beta process approach for sparse incident data. Machine Learning, 95: 11–26.
  • [11] Kim, E.S, Baek, C.W and Kim, J.H., (2005). Estimate of pipe deterioration and optimal scheduling of rehabilitation. Water Science and Technology: Water Supply, 5: 39–46.
  • [12] Le Gauffre, P., (2007). A Multicriteria Decision Support Methodology for Annual Rehabiliation Programs of Water Networks. Computer-Aided Civil and Infrastrucuture Engineering, 22: 478–488.
  • [13] Shahata, K and Zayed, T., (2010). Integrated decision-support framework for municipal infrastructure asset. ASCE Pipelines Proceedings, 514, 1492–1502.
  • [14] Tabesh, M and Saber, H., (2012). A Prioritization Model for Rehabilitation of Water Distribution Networks Using GIS. Water Resources Management, 26: 225–241.
  • [15] Atkinson, S., (2014). Reliability indicators for water distribution system design: Comparison. Water Resources Planning and Management, 140: 160–168.
  • [16] Choi, T and Koo, J., (2015). A water supply risk assessment model for water distribution network. Desalination and Water Treatment, 54: 1410–1420.
  • [17] Kabir, G., (2015). Evaluating risk of water mains failure using a Bayesian belief network model. European Journal of Operational Research, 240: 220–234.
  • [18] Al-Zahrani, M., Abo-Monasar, A., Sadiq, R. (2015). Risk-based prioritization of water main failure using fuzzy synthetic evaluation technique. Journal of Water Supply: Research and Technology – AQUA. 65, jws2015051.
  • [19] El-Abbasy, M.S., (2016). Integrated performance assessment model for water distribution networks. Structure and Infrastructure Engineering, 2479: 1–20.
  • [20] Kessili, A and Benmamar, S., (2016). Prioritizing sewer rehabilitation projects using AHP-PROMETHEE II ranking method. Water Science and Technology, 73: 283–291.
  • [21] Tunca, P.M.Z. (2016). Evaluating the Performances of the Opec Countries By Using Entropi and Maut Multi Criteria Decision Making Methods. Suleyman Demirel University The Journal of Visionary, 7, 1–12.
  • [22] Roy, B., ( 1991) The outranking approach and the foundations of ELECTRE methods. Theory and Decision 31: 49-73.
  • [23] Scholten, L., (2014). Strategic rehabilitation planning of piped water networks using multi-criteria decision analysis. Water Research, 49, 124–143.
  • [24] Haider, H, Sadiq, R and Tesfamariam, S., (2015). Selecting performance indicators for small and medium sized water utilities: Multi-criteria analysis using ELECTRE method. Urban Water Journal, 12: 305–327.
  • [25] Roozbahani, A, Zahraie, B and Tabesh, M., (2012). PROMETHEE with Precedence Order in the Criteria (PPOC) as a New Group Decision Making Aid: An Application in Urban Water Supply Management. Water Resources Management, 26: 3581–3599.
  • [26] MASKİ (2018). Malatya Water and Sewerage Administration General Directorate. Water Supply Unit Report.
  • [27] Gül, Ş. (2018). Determination of Priority Regions for Rehabilitation in Water Distribution Systems. Master of Science Thesis, İnönü University. (in Turkish)
  • [28] Boztaş, F. (2017). Analysis of Leakages on Building (Service) Connections at Water Distribution Systems and Its Effects to Water Losses. Master of Science Thesis, İnönü University. (in Turkish).
  • [29] Marzouk, M, Hamid, S.A and El-Said, M., (2015). A methodology for prioritizing water mains rehabilitation in Egypt. HBRC Journal, 11: 114–128.

DETERMINATION OF PRIORITY REGIONS FOR REHABILITATION IN WATER NETWORKS BY MULTIPLE CRITERIA DECISION MAKING METHODS

Year 2020, Volume: 38 Issue: 3, 1481 - 1494, 05.10.2021

Abstract

Network rehabilitation and pipe material management could be shown as an important economic load for the Water Utility. For this reason, detailed analysis should be made and the worst regions should be determined before applying the methods. In this study, it is aimed to determine the priority regions for rehabilitation in distribution systems in order to prevent water losses. For this aim, a total of 28 factors that can be measured, applied and representing the problem were determined in the application area. Weight coefficients were calculated with the ENTROPY method to determine the degree of influence of these factors in decision making. The highest weight coefficient was obtained for the unreported leakages determined by active leakage control. ELCETRE I and PROMETHEE II methods were applied in determining the priority regions in rehabilitation. According to the results obtained with the ELECTRE I method, DMA 13, DMA 11, DMA 12, DMA 14 and DMA 5 regions were determined as the first 5 regions with rehabilitation priority. On the other hand, according to the PROMETHEE II method, the first 5 regions with rehabilitation priority were DMA 13, DMA 11, DMA 12, DMA 8 and DMA 15. When the results obtained by these two methods are compared, it is seen that the first region with priority of rehabilitation is similar. Thus, it is possible to provide a solution that requires investment priority and aims to increase water resource and economic efficiency. It is thought that the results obtained in this study will serve as a reference in terms of network and water loss management.

References

  • [1] Fares, H.A., (2008). Evaluating the Risk of Water Main Failure Using a Hierarchical Fuzzy Expert System. Masters thesis, Concordia University. 1–11.
  • [2] Sargaonkar, A., (2009). Risk assessment study for water supply network using GIS. Aqua - Journal of Water Supply: Research and Technology, 57: 355–360.
  • [3] Tanyimboh, T.T and Kalungi, P., (2009). Multicriteria assessment of optimal design, rehabilitation and upgrading schemes for water distribution networks. Civil Engineering and Environmental Systems, 26: 117–140.
  • [4] Francisque, A., (2009). Prioritizing monitoring locations in a water distribution network: A fuzzy risk approach. Journal of Water Supply: Research and Technology - AQUA, 58: 488–509.
  • [5] Morais, D.C and Almeida, A.T. (2010). Water network rehabilitation : A group decision-making approach. WaterSA, 36: 487–494.
  • [6] Tsitsifli, S, Kanakoudis, V and Bakouros, I., (2011). Pipe Networks Risk Assessment Based on Survival Analysis. Water Resources Management, 25: 3729–3746.
  • [7] Ammar, M.A, Moselhi, O and Zayed, T.M., (2012). Decision support model for selection of rehabilitation methods of water mains. Structure and Infrastructure Engineering. 8: 847–855.
  • [8] Ennaouri, I and Fuamba, M., (2013). New Integrated Condition-Assessment Model for Combined Storm-Sewer Systems. Journal of Water Resources Planning and Management, 139: 53–64.
  • [9] Francisque, A., (2014). A decision support tool for water mains renewal for small to medium sized utilities: A risk index approach. Journal of Water Supply: Research and Technology - AQUA, 63: 281–302.
  • [10] Li, Z., (2014). Water pipe condition assessment: A hierarchical beta process approach for sparse incident data. Machine Learning, 95: 11–26.
  • [11] Kim, E.S, Baek, C.W and Kim, J.H., (2005). Estimate of pipe deterioration and optimal scheduling of rehabilitation. Water Science and Technology: Water Supply, 5: 39–46.
  • [12] Le Gauffre, P., (2007). A Multicriteria Decision Support Methodology for Annual Rehabiliation Programs of Water Networks. Computer-Aided Civil and Infrastrucuture Engineering, 22: 478–488.
  • [13] Shahata, K and Zayed, T., (2010). Integrated decision-support framework for municipal infrastructure asset. ASCE Pipelines Proceedings, 514, 1492–1502.
  • [14] Tabesh, M and Saber, H., (2012). A Prioritization Model for Rehabilitation of Water Distribution Networks Using GIS. Water Resources Management, 26: 225–241.
  • [15] Atkinson, S., (2014). Reliability indicators for water distribution system design: Comparison. Water Resources Planning and Management, 140: 160–168.
  • [16] Choi, T and Koo, J., (2015). A water supply risk assessment model for water distribution network. Desalination and Water Treatment, 54: 1410–1420.
  • [17] Kabir, G., (2015). Evaluating risk of water mains failure using a Bayesian belief network model. European Journal of Operational Research, 240: 220–234.
  • [18] Al-Zahrani, M., Abo-Monasar, A., Sadiq, R. (2015). Risk-based prioritization of water main failure using fuzzy synthetic evaluation technique. Journal of Water Supply: Research and Technology – AQUA. 65, jws2015051.
  • [19] El-Abbasy, M.S., (2016). Integrated performance assessment model for water distribution networks. Structure and Infrastructure Engineering, 2479: 1–20.
  • [20] Kessili, A and Benmamar, S., (2016). Prioritizing sewer rehabilitation projects using AHP-PROMETHEE II ranking method. Water Science and Technology, 73: 283–291.
  • [21] Tunca, P.M.Z. (2016). Evaluating the Performances of the Opec Countries By Using Entropi and Maut Multi Criteria Decision Making Methods. Suleyman Demirel University The Journal of Visionary, 7, 1–12.
  • [22] Roy, B., ( 1991) The outranking approach and the foundations of ELECTRE methods. Theory and Decision 31: 49-73.
  • [23] Scholten, L., (2014). Strategic rehabilitation planning of piped water networks using multi-criteria decision analysis. Water Research, 49, 124–143.
  • [24] Haider, H, Sadiq, R and Tesfamariam, S., (2015). Selecting performance indicators for small and medium sized water utilities: Multi-criteria analysis using ELECTRE method. Urban Water Journal, 12: 305–327.
  • [25] Roozbahani, A, Zahraie, B and Tabesh, M., (2012). PROMETHEE with Precedence Order in the Criteria (PPOC) as a New Group Decision Making Aid: An Application in Urban Water Supply Management. Water Resources Management, 26: 3581–3599.
  • [26] MASKİ (2018). Malatya Water and Sewerage Administration General Directorate. Water Supply Unit Report.
  • [27] Gül, Ş. (2018). Determination of Priority Regions for Rehabilitation in Water Distribution Systems. Master of Science Thesis, İnönü University. (in Turkish)
  • [28] Boztaş, F. (2017). Analysis of Leakages on Building (Service) Connections at Water Distribution Systems and Its Effects to Water Losses. Master of Science Thesis, İnönü University. (in Turkish).
  • [29] Marzouk, M, Hamid, S.A and El-Said, M., (2015). A methodology for prioritizing water mains rehabilitation in Egypt. HBRC Journal, 11: 114–128.
There are 29 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Research Articles
Authors

Şeymanur Gül This is me 0000-0002-3773-9058

Mahmut Fırat This is me 0000-0002-8010-9289

Publication Date October 5, 2021
Submission Date February 17, 2020
Published in Issue Year 2020 Volume: 38 Issue: 3

Cite

Vancouver Gül Ş, Fırat M. DETERMINATION OF PRIORITY REGIONS FOR REHABILITATION IN WATER NETWORKS BY MULTIPLE CRITERIA DECISION MAKING METHODS. SIGMA. 2021;38(3):1481-94.

IMPORTANT NOTE: JOURNAL SUBMISSION LINK https://eds.yildiz.edu.tr/sigma/