Water Transmission Leakage and Its Correlation to Non-Revenue Water in Salalah Oman

Ts. Dr. Nurazim Ibrahim1, Abdullah Al-Hazar Al-Kathiri1 & Ir Ts Dr. Nor Azidawati Haron2
1Faculty of Civil Engineering, Infrastructure University Kuala Lumpur, Malaysia
2Faculty of Civil Engineering, Universiti Teknologi Malaysia, Malaysia
DOI – http://doi.org/10.37502/IJSMR.2025.8209

Full Text – PDF

Abstract

Non-Revenue Water (NRW) remains a persistent challenge in global water distribution, particularly in arid regions where water scarcity heightens the urgency of efficient resource management. This study investigates the magnitude of NRW in Salalah, Oman, with a focus on its sources, impact, and mitigation strategies. While previous research has explored NRW in urban water supply systems, limited studies have quantitatively analysed transmission pipeline losses in arid environments. Using a structured survey of 165 engineers, technicians, and project managers from ONEIC, this study applies a quantitative research design and statistical analysis through SPSS to evaluate the relationships between NRW sources, magnitude, and mitigation effectiveness. Results indicate that Salalah’s NRW levels exceed global benchmarks, with an estimated loss of 40% compared to the acceptable 10%. The study establishes a strong correlation (0.743) between NRW magnitude and its sources, particularly infrastructure deficiencies, unauthorized connections, and metering inaccuracies. Additionally, proactive leak detection, infrastructure upgrades, and advanced metering technologies contribute to a 59.3% reduction in NRW variation. This study fills critical gaps in NRW research by providing empirical evidence on transmission pipeline losses in an arid region and offering a data-driven framework for policymakers and water utilities. By addressing these inefficiencies, this research contributes to sustainable water management and provides a replicable model for similar water-scarce regions worldwide.

Keywords: NRW, Salalah City, ONEIC, SPSS, Mitigation Strategies

References

  • Al-Bulushi, M. M., Sulti, M. M. A., & Abushammala, M. F. (2018). Investigation of Water Losses in Water Supply System: Muscat as a Case Study. MATEC Web of Conferences, 203, 07004. https://doi.org/10.1051/matecconf/201820307004
  • Al-Ghafri, A. (2018, October). Overview about the Aflaj of Oman. In Proceeding of the International Symposium of Khattaras and Aflaj, Erachidiya, Morocco 9 October 2018 Overview, no. October (pp. 1-22).
  • Al-Jabri, K. (2018). Assessing the resilience of water supply systems in Oman (Doctoral dissertation, Abertay University).
  • Al-Qurashi, A. M. A. S. (2019). The Water Resources Management Importance in the Sultanate of Oman. Indian Ocean Tropical Cyclones and Climate Change. https://doi.org/245-252
  • Al-Siyabi, Y., & Expert, O. P. (2019). Reduction of the technical losses component of the NRW in water networks in Sultanate of Oman. Desalination and Water Treatment, 176, 300-309.
  • Al-turki, R. (2021). Research onion for smart IoT-enabled mobile applications. Scientific Programming, 2021, 1-9.
  • Al-Washali, T., Sharma, S. K., Al-Nozaily, F., Haidera, M., & Kennedy, M. D. (2019). Monitoring Nonrevenue Water Performance in Intermittent Supply. Water, 11(6), 1220. https://doi.org/10.3390/w11061220
  • Awe, O. M., Okolie, S. T. A., & Fayomi, O. S. I. (2019, December). Review of water distribution systems modelling and performance analysis softwares. In Journal of physics: conference series (Vol. 1378, No. 2, p. 022067). IOP Publishing.
  • Ayad, A., Khalifa, A., Fawy, M., & Moawad, A. H. (2021). An integrated approach for non-revenue water reduction in water distribution networks based on field activities, optimisation, and GIS applications. Ain Shams Engineering Journal, 12(4), 3509–3520. https://doi.org/10.1016/j.asej.2021.04.007
  • Kingdom, R. Liemberger, P. Marin, The Challenge of Reducing Non-Revenue Water (NRW) in Developing Countries How the Private Sector Can Help: A Look at Performance Based Service Contracting, Water supply and sanitation sector board discussion paper series, 2006, pp. 1–152.
  • Bhagat, S. K., Tiyasha, Welde, W. L., Tesfaye, O., Tung, T. T., Al-Ansari, N., Salih, S. Q., & Yaseen, Z. M. (2019). Evaluating physical and fiscal water leakage in water distribution system. Water, 11(10), 2091. https://doi.org/10.3390/w11102091
  • Bujang, M. A., Omar, E. D., & Baharum, N. A. (2018). A review on sample size determination for Cronbach’s alpha test: a simple guide for researchers. The Malaysian journal of medical sciences: MJMS, 25(6), 85.
  • Cassidy, J. D., Barbosa, B., Damião, M., Ramalho, P., Ganhão, A., Santos, A. C. F., & Feliciano, J. (2021). Taking water efficiency to the next level: digital tools to reduce non-revenue water. Journal of Hydroinformatics, 23(3), 453–465. https://doi.org/10.2166/hydro.2020.072
  • Crilly, P., Patel, N., Ogunrinde, A., Berko, D., & Kayyali, R. (2017). Community pharmacists’ involvement in research in the United Kingdom. Pharmacy, 5(3), 48.
  • Forero, C. G. (2024). Cronbach’s alpha. In Encyclopedia of quality of life and well-being research (pp. 1505-1507). Cham: Springer International Publishing.
  • W. Choi, Y.G. Jang, S.W. Lee, Effect of Estimation Method of Demand Water on the Analysis of Water Distribution System -Proceedings of the Korea Water Resources Association Conference | Korea Science [WWW Document], in: Proc.Korea Water Resour. Assoc. Conf. Daejeon, Korea, 2006, pp. 1425–1430.
  • Geldreich, E. E. (2020). Microbial Quality of Water Supply in Distribution Systems. CRC Press.
  • Gheisi, A., Forsyth, M., & Naser, G. (2016). Water distribution systems reliability: A review of research literature. Journal of Water Resources Planning and Management, 142(11), 04016047.
  • Güngör-Demirci, G., Lee, J., Keck, J., Guzzetta, R., & Yang, P. (2018). Determinants of non-revenue water for a water utility in California. Aqua, 67(3), 270–278. https://doi.org/10.2166/aqua.2018.152
  • Guo, G., Yu, X., Liu, S., Ma, Z., Wu, Y., Xu, X., Wang, X., Smith, K. A., & Wu, X. (2021). Leakage Detection in Water Distribution Systems Based on Time–Frequency Convolutional Neural Network. Journal of Water Resources Planning and Management, 147(2). https://doi.org/10.1061/(asce)wr.1943-5452.0001317
  • Gupta, A. K., & Kulat, K. (2018). A Selective Literature Review on Leak Management Techniques for Water Distribution System. Water Resources Management, 32(10), 3247–3269. https://doi.org/10.1007/s11269-018-1985-6
  • Elkharbotly, M. R., Seddik, M., & Khalifa, A. (2022). Toward sustainable water: prediction of non-revenue water via artificial neural network and multiple linear regression modelling approach in Egypt. Ain Shams Engineering Journal, 13(5), 101673.
  • Journal of Engg. Research Vol, 8(4), 16-28.
  • Izah, S. C., Sylva, L., & Hait, M. (2023). Cronbach’s Alpha: A Cornerstone in Ensuring Reliability and Validity in Environmental Health Assessment. ES Energy & Environment, 23, 1057.
  • Jang, D. (2018). A Parameter Classification System for Nonrevenue Water Management in Water Distribution Networks. Advances in Civil Engineering, 2018, 1–10. https://doi.org/10.1155/2018/3841979
  • Kamrani, K., Roozbahani, A., & Shahdany, S. M. H. (2020). Using Bayesian networks to evaluate how agricultural water distribution systems handle the water-food-energy nexus. Agricultural Water Management, 239, 106265. https://doi.org/10.1016/j.agwat.2020.106265
  • Kaur, P., Stoltzfus, J., & Yellapu, V. (2018). Descriptive statistics. International Journal of Academic Medicine, 4(1), 60-63.
  • Lai, C. S., Tan, D. S., Roy, R., Chan, N. H., & Zakaria, N. A. (2020). Systems thinking approach for analysing non-revenue water management reform in Malaysia. Water Policy, 22(2), 237–251. https://doi.org/10.2166/wp.2020.165
  • Liemberger R, Farley M. Developing a non-revenue water reduction strategy: planning and implementing the strategy. Water Supply 2005;5(1):41–50.
  • Liemberger, R., & Wyatt, A. (2018). Quantifying the global non-revenue water problem. Water Science & Technology: Water Supply, 19(3), 831–837. https://doi.org/10.2166/ws.2018.129
  • McIntosh AC. Asian water supplies: reaching the urban poor: a guide and sourcebook on urban water supplies in Asia for governments, utilities, consultants, development agencies, and non-government organizations. Asian Development Bank, International Water Association; 2003. p. 1–139.
  • Mishra, P., Pandey, C. M., Singh, U., Gupta, A., Sahu, C., & Keshri, A. (2019). Descriptive statistics and normality tests for statistical data. Annals of cardiac anaesthesia, 22(1), 67-72.
  • Naamani, A. A., & Sana, A. (2021). Operational and technical performance of a water distribution network in Oman. Water Supply, 21(8), 4593-4607.
  • Noman, N., Orakzai, T. O., Zafar, D., & Khan, A. (2023). Distribution of Cataract by Age groups, Sex, Residency and Literality in Population of District Dera Ismail Khan. BMC Journal of Medical Sciences, 4(2), 96-99.
  • Selek, B., Adigüzel, A., İritaş, Ö., Karaaslan, Y., Kinaci, C., Muhammetoğlu, A., & Muhammetoğlu, H. (2018). Management of water losses in water supply and distribution networks in Turkey. Turkish Journal of Water Science and Management, 2(1), 58-75.
  • Sullivan, L. (2020). Power and sample size determination.