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Cost-Benefit Analysis and Uncertainty Analysis of Water Loss Reduction Measures: Case Study of the Gothenburg Drinking Water Distribution System

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  • Annika Malm
  • Frida Moberg
  • Lars Rosén
  • Thomas Pettersson

Abstract

Methods for controlling leakage from water distribution systems vary with respect to cost and personnel requirements. The benefits of leakage reduction should be compared to the cost of alternative management options to determine which is the most cost effective. This study presents a new method for evaluating leakage from water distribution systems via combined cost benefit analysis (CBA) and uncertainty analysis. The case study considers four alternatives for leakage control. The results show that the inclusion of uncertainty analysis represents an improvement over traditional CBA where there is a high degree of uncertainty in the input data. Moreover, a clearer understanding of the available alternatives is obtained in situations where multiple alternatives show similar performances and there is no clear best choice. It was determined that in the case study distribution system, it is significantly more cost-effective to reduce leakage volumes by reactively repair broken pipes than to proactively replace them, despite large leakage losses. Copyright Springer Science+Business Media Dordrecht 2015

Suggested Citation

  • Annika Malm & Frida Moberg & Lars Rosén & Thomas Pettersson, 2015. "Cost-Benefit Analysis and Uncertainty Analysis of Water Loss Reduction Measures: Case Study of the Gothenburg Drinking Water Distribution System," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(15), pages 5451-5468, December.
    • Handle: RePEc:spr:waterr:v:29:y:2015:i:15:p:5451-5468
    DOI: 10.1007/s11269-015-1128-2
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    References listed on IDEAS

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    1. L. Araujo & H. Ramos & S. Coelho, 2006. "Pressure Control for Leakage Minimisation in Water Distribution Systems Management," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 20(1), pages 133-149, February.
    2. M. Tabesh & A. Yekta & R. Burrows, 2009. "An Integrated Model to Evaluate Losses in Water Distribution Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 23(3), pages 477-492, February.
    3. Morimoto, Risako, 2010. "Estimating the benefits of effectively and proactively maintaining infrastructure with the innovative Smart Infrastructure sensor system," Socio-Economic Planning Sciences, Elsevier, vol. 44(4), pages 247-257, December.
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    Cited by:

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    2. Tri Heryanto & Saroj K. Sharma & D. Daniel & Maria Kennedy, 2021. "Estimating the Economic Level of Water Losses (ELWL) in the Water Distribution System of the City of Malang, Indonesia," Sustainability, MDPI, vol. 13(12), pages 1-15, June.
    3. Sou-Sen Leu & Quang-Nha Bui, 2016. "Leak Prediction Model for Water Distribution Networks Created Using a Bayesian Network Learning Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(8), pages 2719-2733, June.
    4. Ahmed Sattar & B. Gharabaghi & Edward McBean, 2016. "Prediction of Timing of Watermain Failure Using Gene Expression Models," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(5), pages 1635-1651, March.
    5. Bárbara Brzezinski Azevedo & Tarcísio Abreu Saurin, 2018. "Losses in Water Distribution Systems: A Complexity Theory Perspective," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(9), pages 2919-2936, July.
    6. Farid Saberi-Movahed & Mohammad Najafzadeh & Adel Mehrpooya, 2020. "Receiving More Accurate Predictions for Longitudinal Dispersion Coefficients in Water Pipelines: Training Group Method of Data Handling Using Extreme Learning Machine Conceptions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(2), pages 529-561, January.
    7. Moslehi, Iman & Jalili Ghazizadeh, Mohammadreza & Yousefi-Khoshqalb, Ehsan, 2020. "An economic valuation model for alternative pressure management schemes in water distribution networks," Utilities Policy, Elsevier, vol. 67(C).
    8. Jinliang Gao & Kunyi Li & Wenyan Wu & Jianxun Chen & Tiantian Zhang & Liqun Deng & Ping Xin, 2022. "Innovative Water Supply Network Pressure Management Method—The Establishment and Application of the Intelligent Pressure-Regulating Vehicle," Energies, MDPI, vol. 15(5), pages 1-15, March.

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