Optimal selection of acoustic leak detection techniques for water pipelines using multi-criteria decision analysis

Sepideh Yazdekhasti, Kalyan Ram Piratla, John C. Matthews, Abdul Khan, Sez Atamturktur

Research output: Contribution to journalArticlepeer-review

12 Scopus citations


Purpose: There has been a sustained interest over the past couple of decades in developing sophisticated leak detection techniques (LDTs) that are economical and reliable. Majority of current commercial LDTs are acoustics based and they are not equally suitable to all pipe materials and sizes. There is also limited knowledge on the comparative merits of such acoustics-based leak detection techniques (ALDTs). The purpose of this paper is to review six commercial ALDTs based on four decisive criteria and subsequently develop guidance for the optimal selection of an ALDT. Design/methodology/approach: Numerous publications and field demonstration reports are reviewed for evaluating the performance of various ALDTs in this study to inform their optimal selection using an integrated multi-criteria decision analysis (MCDA) framework. The findings are validated using interviews of water utility experts. Findings: The study approach and the findings will have a broad impact on the water utility industry by identifying a suite of suitable ALDTs for a range of typical application scenarios. The evaluated ALDTs include listening devices, noise loggers, leak-noise correlators, free-swimming acoustic, tethered acoustic, and acoustic emissions. The evaluation criteria include cost, reliability, access requirements, and the ability to quantify leakage severity. The guidance presented in this paper will support efficient decision making in water utility management to minimize pipeline leakage. Originality/value: This study attempts to address the problem of severe dearth of performance data for pipeline inspection techniques. Performance data reported in the published literature on various ALDTs are appropriately aggregated and compared using a MCDA, while the uncertainty in performance data is addressed using the Monte Carlo simulation approach.

Original languageEnglish (US)
Pages (from-to)255-277
Number of pages23
JournalManagement of Environmental Quality: An International Journal
Issue number2
StatePublished - 2018

All Science Journal Classification (ASJC) codes

  • General Biochemistry, Genetics and Molecular Biology
  • Management, Monitoring, Policy and Law


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