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2026 Articles

  1. Bagherzadeh, M., Kilic, Z., Daneshfaraz, R.,Yilmaz, E., & Ejel, A. T. (2026). Inclined gabion drops improve hydraulic performance relative to conventional USBR stilling basins under variable flow conditions. Scientific Reports.  https://doi.org/10.1038/s41598-026-66398-0
  2. Salmasi, F., & Abraham, J. (2026). Discussion of “Comparison of analytical, multiple polynomial regression, and artificial neural networks to estimate wetting parameters for surface and buried drip irrigation across three different soil textures.” Journal of Irrigation and Drainage Engineering, 152(5). https://doi.org/10.1061/JIDEDH.IRENG-10787
  3. Azari, M., Sadeghfam, S., Kashi, S.M.H. (2026). Sustainable urban growth scenario for climate-vulnerable coastal cities: An analysis based on ubiquitous big data and a hybrid fuzzy-cellular automata, Land Use Policy, 171, 108260. https://doi.org/10.1016/j.landusepol.2026.108260
  4. Rousta, Z., Samadianfard, S., Delirhasannia, R., & Karimzadeh, S. (2026). Optimized deep learning frameworks for evapotranspiration modeling: Integrating MODIS satellite data and stochastic fractal search. Modeling Earth Systems and Environment, 12, 211.   https://doi.org/10.1007/s40808-026-02846-0
  5. Roushangar, K., Panahi, A., & Farajpour, I. (2026). Simultaneous prediction of discharge coefficients for sharp and broad crested trapezoidal side weirs using machine learning models. Flow Measurement and Instrumentation, 103473. https://doi.org/10.1016/j.flowmeasinst.2026.103473
  6. Roushangar, K., Aalami, M. T., & Akhoundzadeh, A. (2026). Hybrid analysis of river training structures: integration of 3D numerical modeling with field-scale hydrodynamic assessment. Environmental Earth Sciences, 85(11), 252.‏ https://doi.org/10.1007/s12665-026-12943-z
  7. Abbaszadeh, H., Tarinejad, R., Roushangar, K., & Daneshfaraz, R. (2026). Investigation of the effects of internal structure and material properties on the hydraulic performance of rectangular gabion weirs: experimental and numerical study. Water Resources Management, 40(8), 376.‏ https://doi.org/10.1007/s11269-026-04667-3
  8. Sadeghfam, S., Mousavi, S.B., Moazamnia, M., Daneshfaraz, R. , Sume, V. (2026). Formulating cultivation potential index under uncertainty for wheat and canola by incorporating remotely sensed and big data, Heliyon, 12, e45133. https://doi.org/10.1016/j.heliyon.2026.e45133.
  9. Pourian, P., Ehsanitabar, A., Khatibi, R., Süme, V., & Sadeghfam, S.(2026). Investigating the resilience of the basin of Lake Urmia in terms of precipitation and drought using climate change scenarios. Environmental Challenges, 101564. https://doi.org/10.1016/j.envc.2026.101564.
  10. Sharafi, M., Samadianfard, S., & Majnooni-Heris, A. (2026). Innovative integration of recurrent neural networks and an improved atom search algorithm for predicting suspended sediment concentration in rivers. Water, Air, & Soil Pollution, 237(1075). https://doi.org/10.1007/s11270-026-09756-y
  11. Vafaei, A., Ibrahim, O. R., Abdi, E., & Asadi, E. (2026). Enhancing groundwater level prediction through DeepMVI aided interpolation and transformer-based modeling. Earth Science Informatics, 19(7), 101. https://doi.org/10.1007/s12145-026-02153-3
  12. Ibrahim, O. R., Valizadeh, G., Meahrayen, M. A., Sarwari, S., & Abdi, E. (2026). A combination model based on sequential general variational mode decomposition method for improving lake water level prediction. Environmental Processes, 13(2), 36. https://doi.org/10.1007/s40710-026-00846-x
  13. Samadianfard, S., & Gündüz, O. (2026). Decoding cross-correlated hydrochemical drivers for robust nutrient concentration prediction. Water, Air, & Soil Pollution, 237(951). https://doi.org/10.1007/s11270-026-09630-x
  14. Samadianfard, S., Aras, E., Çelik, D. Y., Sattari, M. T., & Gündüz, O. (2026). Hybrid CEEMDAN–GRU framework optimized with an MOOTLBO enables accurate real-time prediction of chemical oxygen demand (COD) in wastewater treatment. Environmental Science: Water Research & Technology. https://doi.org/10.1039/D6EW00014B
  15. Safari, S., Sharafati, A., Mosaferi, M., et al. (2026). Alternative urban drinking water supply scenarios under climate change: Evaluation of carbon footprint and energy demands. Journal of Environmental Health Science and Engineering, 24, 10. https://doi.org/10.1007/s40201-026-00977-
  16. Monavvar Sabegh, S., Zarehaghi, D., Samadianfard, S., Sattari, M. T., & Ahmad, S. (2026). Enhanced Pedotransfer Functions Through Optuna-Optimized Extreme Gradient Boosting: Application to Soil Water Retention Modeling. Earth, 7(3), 94. https://doi.org/10.3390/earth7030094
  17. Ghayurdoost, F., Zarghami, M., Sadeghfam, S., Jabraili-Andaryan, N., Nikmaram, S., Baba, A., Asgari Lajayer, B., & Mosaferi, M. (2026). Hydrogeochemical assessment and health risks of groundwater in Sahand volcanic foreland (NW Iran): Arsenic speciation and heavy metal risk indicators. Ecotoxicology and Environmental Safety, 310, Article 119746. https://doi.org/10.1016/j.ecoenv.2026.119746
  18. Feizi, H., & Sattari, M. T. (2026). Streamflow forecasting based on PatchTST, LSTM, and ensemble learning approaches. Water Resources Management, 40, 44. https://doi.org/10.1007/s11269-025-04397-y
  19. 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
  20. Roushangar, K., & Panahi, A. (2026). Development of hybrid metaheuristic-kernel based models for accurate discharge coefficient prediction in side weirs with various geometries. Flow Measurement and Instrumentation, 107, Article 103092. https://doi.org/10.1016/j.flowmeasinst.2025.103092
  21. Monavvar Sabegh, S., Zarehaghi, D., & Samadianfard, S. (2026). Enhancing reference evapotranspiration prediction with biological ensemble support vector regression and MODIS data integration. Sustainable Water Resources Management,  12, 5. https://doi.org/10.1007/s40899-025-01317-1
  22. Abdi, E., Sattari, M. T., Samadianfard, S., & Ahmad, S. (2026). Decomposition–quantum hybrid model for accurate reservoir inflow prediction: A case study on Khoda Afarin Dam. Earth, 7(2), 35. https://doi.org/10.3390/earth7020035
  23. Allahverdipour, P., & Fakheri-Fard, A. (2026). Copula-based mapping of compound climate risks to rainfed wheat yield in semi-arid Iran. Earth Systems and Environment. Advance online publication. https://doi.org/10.1007/s41748-026-01080-z
  24. Roushangar, K., Shahnazi, S., & Hashemi, H. (2026). Groundwater artificial recharge with unconventional water: Global opportunities and challenges. In Hydrosystem Restoration Handbook(Vol. 4, pp. 199-224). Elsevier. https://doi.org/10.1016/B978-0-443-29811-0.00023-6
  25. Shahnazi, S., Roushangar, K., Farshbaf, A., et al. (2026). A novel implementation of a decomposition-enhanced hybrid GWO–KELM model with LUBE for constructing prediction intervals of groundwater drought. Earth Science Informatics, *19*, 31. https://doi.org/10.1007/s12145-026-02093-y

2025 Articles (Older)

  1. Feizi, H., Sattari, M. T., & Milewski, A. (2025). Improving stage-discharge relationship modeling accuracy using a hybrid ViT-CNN framework. Scientific Reports, *15*, 38031. https://doi.org/10.1038/s41598-025-21926-2
  2. Talebi, H., Citakoglu, H., Samadianfard, S., et al. (2025). 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. Advance online publication. https://doi.org/10.1007/s00024-025-03876-y
  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

 


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