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Water Sciences and Hydroinformatics Research CenterAboutMissionPublicationsMembersNewsContacts

Publications

  1. Feizi, H., Sattari, M.T. & Milewski, A. Improving stage-discharge relationship modeling accuracy using a hybrid ViT-CNN framework. Scientific Report15, 38031 (2025). https://doi.org/10.1038/s41598-025-21926-2, Q1 in WOS
  2. Talebi, H., Citakoglu, H., Samadianfard, S. et al. Advanced Hybrid Machine Learning for Precise Short-Term Drought Prediction: A Comparative Study of SPI and SPEI Indices in Iran's Arid and Semi-Arid Regions. Pure Appl. Geophys. (2025). https://doi.org/10.1007/s00024-025-03876-y, Q2 in WOS
  3. Abdi, E., Sattari, M.T., Samadianfard, S., & Ahmad, S. (2025). Advancing Hydrological Prediction with Hybrid Quantum Neural Networks: A Comparative Study for Mile Mughan Dam. Water, 17(24), 3592.Https://doi.org/10.3390/w17243592, Q1 in Scopus
  4. Seifian, Z., Hooshyaripor, F., Saghafian, B., Mirabbasi, R. (2026). Investigating meteorological drought propagation to soil moisture drought: insights from Iran’s diverse climate regions. Theor Appl Climatol157, 15. https://doi.org/10.1007/s00704-025-05924-y, Q2 in Scopus
  5. Roushangar, K., Panahi, A. Development of hybrid metaheuristic-kernel based models for accurate discharge coefficient prediction in side weirs with various geometries. Flow Measurement and Instrumentation. 107 (2026). https://doi.org/10.1016/j.flowmeasinst.2025.103092, Q2 in WOS
  6. Monavvar Sabegh, S., Zarehaghi, D. & Samadianfard, S. Enhancing reference evapotranspiration prediction with biological ensemble support vector regression and MODIS data integration. Sustain. Water Resour. Manag. 12, 5 (2026).Https://doi.org/10.1007/s40899-025-01317-1, Q2 in Scopus
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