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Publication list

  • Jamshidi, S., Murgia, T., Morales‐Ona, A. G., Cerioli, T., Famoso, A. N., Cammarano, D., & Wang, D. R. Modeling interactions of planting date and phenology in Louisiana rice under current and future climate conditions. Crop Science.

  • Gu, X., Jamshidi, S., Qian, J., Hao, Y., Sun, H., & Niyogi, D. (2023). Quantifying the Effect of Driving Factors on Spring Discharge in an Industrialized Karst Watershed. Journal of Hydrologic Engineering, 28(7), 05023013.

  • Abbaszadeh, M., Bazrafshan, O., Mahdavi, R., Sardooi, E. R., & Jamshidi, S. (2023). Modeling Future Hydrological Characteristics Based on Land Use/Land Cover and Climate Changes Using the SWAT Model. Water Resources Management, 1-18.

  • Singh, M., Acharya, N., Jamshidi, S., Jiao, J., Yang, Z. L., Coudert, M., ... & Niyogi, D. (2023). DownScaleBench for developing and applying a deep learning based urban climate downscaling-first results for high-resolution urban precipitation climatology over Austin, Texas. Computational Urban Science, 3(1), 22.

  • Jahromi, M. N., Zand-Parsa, S., Razzaghi, F., Jamshidi, S., Didari, S., Doosthosseini, A., & Pourghasemi, H. R. (2023). Developing machine learning models for wheat yield prediction using ground-based data, satellite-based actual evapotranspiration and vegetation indices. European Journal of Agronomy, 146, 126820.

  • Fathian, M., Bazrafshan, O., Jamshidi, S., & Jafari, L. (2023). Impacts of climate change on water footprint components of rainfed and irrigated wheat in a semi-arid environment. Environmental Monitoring and Assessment, 195(2), 324.

  • Singh, M., Acharya, N., Patel, P., Jamshidi, S., Yang, Z. L., Kumar, B., ... & Niyogi, D. (2023). A modified deep learning weather prediction using cubed sphere for global precipitation. Frontiers in Climate, 4, 1022624.

  • Cammarano, D., Jamshidi, S., Hoogenboom, G., Ruane, A. C., Niyogi, D., & Ronga, D. (2022). Processing tomato production is expected to decrease by 2050 due to the projected increase in temperature. Nature Food, 1-8.

  • Patel, P., Jamshidi, S., Nadimpalli, R., Aliaga, D., Mills, G., Chen, F., Demuzere, M., & Niyogi, D. (2022). Modelling Large-Scale Heatwave by Incorporating Enhanced Urban Representation. Journal of Geophysical Research.

  • Jafari, E., Rezazadeh, M., Bazrafshan, O., & Jamshidi, S. (2022). Spatiotemporal variability of sand-dust storms and their influencing factors in the MENA region. Theoretical and Applied Climatology, 1-15.

  • Gu, X., Jamshidi, S., Sun, H., & Niyogi, D. (2021). Identifying multivariate controls of soil moisture variations using multiple wavelet coherence in the US Midwest. Journal of Hydrology, 126755.

  • Jamshidi, S., Zand-Parsa, S., & Niyogi, D. (2021). Assessing Crop Water Stress Index of Citrus Using In-Situ Measurements, Landsat, and Sentinel-2 Data. International Journal of Remote Sensing, 42(5), 1893-1916.

  • Bazrafshan, O., Ehteram, M., Moshizi, Z. G., & Jamshidi, S. (2022). Evaluation and uncertainty assessment of wheat yield prediction by multilayer perceptron model with bayesian and copula bayesian approaches. Agricultural Water Management, 273, 107881.

  • Bazarfshan, O., Yahyazadeh, M., Jamshidi, S., & Zamani, H. Spatial prioritization of tomato cultivation based on water footprint, land productivity, and economic indices. Irrigation and Drainage.

  • Jamshidi, S., Zand-Parsa, S., Kamgar-Haghighi, A. A., Shahsavar, A. R., & Niyogi, D. (2020). Evapotranspiration, crop coefficients, and physiological responses of citrus trees in semi-arid climatic conditions. Agricultural Water Management, 227, 105838.

  • Jamshidi, S., Zand-parsa, S., Pakparvar, M., & Niyogi, D. (2019). Evaluation of evapotranspiration over a semiarid region using multiresolution data sources. Journal of Hydrometeorology, 20(5), 947-964.

  • Jamshidi, S., Baniasad, M., & Niyogi, D. (2020). Global to USA County Scale Analysis of Weather, Urban Density, Mobility, Homestay, and Mask Use on COVID-19. International journal of environmental research and public health, 17(21), 7847.

  • Jamshidi, S., Zand-Parsa, S., Naghdyzadegan Jahromi, M., & Niyogi, D. (2019). Application of a simple Landsat-MODIS fusion model to estimate evapotranspiration over a heterogeneous sparse vegetation region. Remote Sensing, 11(7), 741.

  • Niyogi, D., Jamshidi, S., Smith, D., & Kellner, O. (2020). Evapotranspiration Climatology of Indiana Using In Situ and Remotely Sensed Products. Journal of Applied Meteorology and Climatology, 59 (12), 2093-2111.

  • Jamshidi, S., Zand-Parsa, S., & Niyogi, D. (2020) Physiological responses of orange trees subject to regulated deficit irrigation and partial root drying. Irrigation Science, 1-15.

  • Zare, M., Pakparvar, M., Jamshidi, S., Bazrafshan, O., & Ghahari, G. (2021). Optimizing the Runoff Estimation with HEC-HMS Model Using Spatial Evapotranspiration by the SEBS Model. Water Resources Management, 1-16.

  • M. Noshadi and S. Jamshidi, “Modification of water movement equations in the PRZM3 for simulating pesticides in soil profile,” Agric. Water Manag., vol. 143, pp. 38–47, 2014.

  • Baniasad., M, Golrokh Mofrad, M., Bahmanabadi, B., and Jamshidi, S., (2021). “COVID-19 in Asia: Transmission Factors, Re-Opening Policies, and Vaccination Simulation.” Environmental Research, July 8, 2021, 111657.

  • Jahromi, M. N., Miralles, D., Koppa, A., Rains, D., Zand-Parsa, S., Mosaffa, H., & Jamshidi, S. (2022). Ten Years of GLEAM: A Review of Scientific Advances and Applications. Computational Intelligence for Water and Environmental Sciences, 525-540.

  • Naghdyzadegan Jahromi, M., Zand-Parsa, S., Doosthosseini, A., Razzaghi, F., & Jamshidi, S. (2022). Enhancing Vegetation Indices from Sentinel-2 Using Multispectral UAV Data, Google Earth Engine and Machine Learning. In Computational Intelligence for Water and Environmental Sciences (pp. 507-523). Springer.

  • Jahromi, M. N., Jahromi, M. N., Pourghasemi, H. R., Zand-Parsa, S., & Jamshidi, S. (2021). Chapter 12: 12: Accuracy assessment of forest mapping in MODIS land cover dataset using fuzzy set theory in Forest Resources Resilience and Conflicts. In Forest Resources Resilience and Conflicts (pp. 165-183). Elsevier.

  • Jamshidi, S., Nayak, H. P., Patel, P., Cammarano, D., & Niyogi, D. (2020, December). Assessment of Agricultural Feedbacks in Noah-MP-Crop Land Surface Model Under Drought Condition. In AGU Fall Meeting 2020. AGU.

  • Jamshidi, S., & Niyogi, D. (2020, January). Assessment of Agricultural Feedbacks in Noah-MP-Crop Land Surface Model on Regional Crop-Yield Simulations. In 100th American Meteorological Society Annual Meeting. AMS.

  • Tiwari, A., Busireddy, N. K. R., Patel, P., Merwade, V., Jamshidi, S., Marks, F., ... & Niyogi, D. (2019). Assessing Variability in Multi-sensor Tropical Cyclone Rainfall Estimates and the Impact on Urban Flood Simulation for Hurricane Florence (2018). AGUFM, 2019, H31D-03.

  • S.Jamshidi, Sh. Zand-Parsa and M. Pakparvar, “Evaluation of estimated actual evapotranspiration of spring wheat using METRIC and SEBS models in Gareh Bygone Plain, southern Iran” The 1st National Conference on GIS & RS Modeling. Shiraz, Iran.

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