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Water Sciences and Hydroinformatics Research CenterAboutMissionPublicationsMembersNewsContacts

Publications

  • Feizi, H., Sattari, M.T. Streamflow Forecasting Based on PatchTST, LSTM, and Ensemble Learning Approaches. Water Resources Management, 40, 44 (2026).
    https://doi.org/10.1007/s11269-025-04397-y(Q1, WOS)

  • Seifian, Z., Hooshyaripor, F., Saghafian, B., Mirabbasi, R. (2026). Investigating meteorological drought propagation to soil moisture drought: insights from Iran’s diverse climate regions. Theoretical and Applied Climatology, 157, 15.
    https://doi.org/10.1007/s00704-025-05924-y(Q2, Scopus)

  • 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, WOS)

  • Monavvar Sabegh, S., Zarehaghi, D., Samadianfard, S. Enhancing reference evapotranspiration prediction with biological ensemble support vector regression and MODIS data integration. Sustainable Water Resources Management, 12, 5 (2026).
    https://doi.org/10.1007/s40899-025-01317-1(Q2, Scopus)

  • Feizi, H., Sattari, M.T., Milewski, A. Improving stage-discharge relationship modeling accuracy using a hybrid ViT-CNN framework. Scientific Reports, 15, 38031 (2025).
    https://doi.org/10.1038/s41598-025-21926-2(Q1, WOS)

  • 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 and Applied Geophysics (2025).
    https://doi.org/10.1007/s00024-025-03876-y(Q2, WOS)

  • 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, Scopus)

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