Open Access
Issue
E3S Web Conf.
Volume 671, 2025
3rd International Symposium on Environmental and Energy Policy (ISEEP 2025)
Article Number 04005
Number of page(s) 11
Section Renewable Energy and Sustainable Resource Management
DOI https://doi.org/10.1051/e3sconf/202567104005
Published online 01 December 2025
  1. D. Medoukali, Feasibility and effectiveness of metaheuristic algorithms in optimizing valve placement for water distribution networks (PhD thesis, 2025). [Online]. Available: https://tesidottorato.depositolegale.it/bitstream/20.500.14242/214087/1/PhD_Thesis_M edoukali.pdf [Google Scholar]
  2. A.V. Serafeim, N.T. Fourniotis, R. Deidda, G. Kokosalakis, A. Langousis, “Leakages in water distribution networks: Estimation methods, influential factors, and mitigation strategies—A comprehensive review,” Water 16(11), 1534 (2024). https://doi.org/10.3390/w16111534 [Google Scholar]
  3. K. Makanda, S. Nzama, T. Kanyerere, “Assessing the role of water resources protection practice for sustainable water resources management: A review,” Water 14(19), 3153 (2022). https://doi.org/10.3390/w14193153 [Google Scholar]
  4. S.R. Krishnan, M.K. Nallakaruppan, R. Chengoden, S. Koppu, M. Iyapparaja, J. Sadhasivam, S. Sethuraman, “Smart water resource management using artificial intelligence—A review,” Sustainability 14(20), 13384 (2022). https://doi.org/10.3390/su142013384 [CrossRef] [Google Scholar]
  5. J.F.P. Ausina, J. Francesc, NRW-Smart: A simulation-based tool for managing non-revenue water in urban and rural systems (PhD thesis, 2025). https://doi.org/10.4995/thesis/10251/224174 [Google Scholar]
  6. C. Cui, Z. Dong, Y. Han, L. Ren, X. Wang, S. Si, “Modelling and assessment of the impact of water network construction on mitigating regional water supply–demand conflicts: Strategic approaches for water resources planning and management,” Water Resour. Manag. (online first), 1–27 (2025). https://doi.org/10.1007/s11269-025-04118-5 [Google Scholar]
  7. Department of Public Works and Highways (Philippines), Guidelines for the design of rural water supply for Level II and Level III (domestic and potable use) (2023). [Online]. Available: https://www.dpwh.gov.ph/dpwh [Google Scholar]
  8. J. Vysocký, L. Foltyn, D. Brkić, R. Praksová, P. Praks, “Steady-state analysis of electrical networks in pandapower software: Computational performances of Newton– Raphson, Newton–Raphson with Iwamoto multiplier, and Gauss–Seidel methods,” Sustainability 14(4), 2002 (2022). https://doi.org/10.3390/su14042002 [Google Scholar]
  9. M.G. Hiben, A.G. Awoke, A.A. Ashenafi, “Future potable water supply demand projection under climate change and socioeconomic scenarios: A case of Gshba sub-basin, northern Ethiopia,” Int. Res. J. Multidiscip. Technovation 6(1), 51–64 (2024). https://doi.org/10.54392/irjmt2415 [Google Scholar]
  10. R. Chen, Q. Wang, A. Javanmardi, “A review of the application of machine learning for pipeline integrity predictive analysis in water distribution networks,” Arch. Comput. Methods Eng. 32(6), 3821–3849 (2025). https://doi.org/10.1007/s11831-025-10251-6 [Google Scholar]
  11. B. Duan, J. Gao, H. Cao, S. Hu, “Energy-efficient management of urban water distribution networks under hydraulic anomalies: A review of technologies and challenges,” Energies 18(11) (2025). https://doi.org/10.3390/en18112877 [Google Scholar]
  12. E. Farah, I. Shahrour, “Water leak detection: A comprehensive review of methods, challenges, and future directions,” Water 16(20), 2975 (2024). https://doi.org/10.3390/w16202975 [Google Scholar]
  13. H. Kim, K.J. Jung, S. Lee, E.H. Jeong, “Rapid response to pressure variations in water distribution networks through machine learning-enhanced data acquisition,” AQUA— Water Infrastruct. Ecosyst. Soc. 73(7), 1358–1371 (2024). https://doi.org/10.2166/aqua.2024.030 [Google Scholar]
  14. Z. Liu, Y. Shi, K. Wu, H. Zhao, G. Pan, “Experimental study on load characteristics of a vehicle during high-speed water entry,” Ocean Eng. 288, 116052 (2023). https://doi.org/10.1016/j.oceaneng.2023.116052 [Google Scholar]
  15. S.I. Abba, Q.B. Pham, A. Malik, R. Costache, M.S. Gaya, J. Abdullahi, … G. Saini, “Optimization of extreme learning machine with metaheuristic algorithms for modelling water quality parameters of Tamburawa water treatment plant in Nigeria,” Water Resour. Manag. 39(3), 1377–1401 (2025). https://doi.org/10.1007/s11269-024-04027-z [Google Scholar]

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