Evaluation of SALTMED model in estimation of wheat yield under deficit irrigation and salinity stress in arid areas (Case study: Birjand)

Document Type : Research Paper


1 Assistant Professor, Water Engineering Department, Minab higher education center, and member of Research Group of Agro-ecology in Dry land Areas, University of Hormozgan, Minab, I.R. of Iran.

2 Assistant Professor, Department of Water Engineering, College of Aburaihan, University of Tehran, Tehran, Iran.

3 Assistant Professor, Department of Water Sciences and Engineering, Faculty of Agriculture and Environment, Arak University, Arak, Iran.


The application of modeling is an appropriate alternative for field experiments that save time and cost. SALTMED is a generic model for modeling plants response to water and salinity stress. This study was done to evaluate the performance of SALTMED model for wheat plant in an arid area in Birjand, South Khorasan Province. The treatments include water stress (50, 75, 100 and 120 percent of water requirement) and salinity stress (1.4, 4.5 and 9.6 dS/m) in three replications. The statistical indices of measured and predicted yield showed the normalized root mean square error (NRMSE) less than 10 percent and the coefficient of determination (R2) equal to 0.99 and 0.96 for model calibration and validation, respectively. The model could also simulate the temporal variation of evapotranspiration and soil salinity profile during the growing season accurately. Therefore, according to the results, SALTMED is an accurate model to predict the yield and plant reactions of wheat under different water and salinity stress levels in the arid areas.


Main Subjects

  1. Abdelraouf, R. E., El-Shawadfy, M. A., Dewedar, O. M., & Hozayn, M. (2021). Field and modelling study for deficit irrigation strategy on roots volume and water productivity of wheat. Journal of Water and Land Development, 49(4-6), 129-138.
  2. Abdelraouf, R. E., Ghanem, H. G., Bukhari, N. A., & El-Zaidy, M. )2020(. Field and modeling study on manual and automatic irrigation scheduling under deficit irrigation of greenhouse cucumber. Sustainability, 12(23), pp.9819.
  3. Abtahi, )2001(. Response of seedlings of two pistachio cultivars to quantity and composition of soil salinity under greenhouse conditions. Journal of Water and Soil Science, 5(1), 93-101. (In Persian).
  4. Aly, A. A., Al-Omran, A. M., & Khasha, A. )2015(. Greenhouse experiment in Saudi Arabia and modeling study using SALTMED model. Soil and Water Conservation Journal, 70, 1-11.
  5. Aggarwal, P. K., & Karla, N. )1994(. Simulating the effect of climatic factors, genotype and management on productivity of wheat in India. New Delhi: IARI Publication.
  6. Allen, R. G., Pereira, L. S., Raes, D., & Smith, M. (1998). Crop evapotranspiration: FAO Irrigation and drainage paper 56. FAO, Rome, Italy.
  7. Basiri, M., Ghamarnia, H., Ghobadi, M., & Ragab, R. (2019). Study of SALTMED model performance to predict peppermint (Mentha piperita) yield production under various deficit irrigation and salinity management conditions. Journal of water and irrigation management, 9(1), 69-79. (In Persian).
  8. Cardon, G. E., & Letey, J. )1992a(. Plant water uptake terms evaluated for soil water and solute movement models. Soil Science Society of American Journal, 56, 1876-1880.
  9. Cardon, G. E., & Letey, J. )1992b(. Soil-based irrigation and salinity management model. I. Plant water uptake calculations. Soil Science Society of American Journal, 56, 1881-1887.
  10. (2017). Faostat. (Accessed 19 August 2021). http://www.fao.org/faostat/en/#data/QCL.
  11. Ferrer, F., & Stockle, C. )1996(. A model for assessing crop response and water management in saline conditions. In: Irrigation Scheduling: From Theory to Practice, Proceeding ICID/FAO Workshop, September, Water Reports No. 8, FAO, Rome.
  12. Hirich, A., Choukr-Allah, R., Ragab, R., Jacobsen, E., El Youssfi, L., & El-Omari, H. )2011(. The SALTMED model calibration and validation using field data from Morocco. Materials Environmental Science Journal, 3(2), 342-359.
  13. Hasanli, M., Afrasyab, P., & Ebrahimiyan, H. )2016(. Evaluation of AquaCrop model and SALTMED model in estimating the yield of maize and soil salinity. Iranian Journal of Soil and Water Research, 46(3), 487-498. (In Persian).
  14. Kaya, C. I., Yazar, A., & Metin Sezen, S. )2015(. SALTMED model performance on simulation of soil moisture and crop yield for Quinoa irrigated using different irrigation systems, irrigation strategies and water qualities in Turkey. Agriculture and Agricultural Science Journal, 4, 108-118.
  15. Kroes, J. G., van Dam, J. C., Huygen, J., & Vervoort, R. W. )1999(. Users guide of SWAP version 2.0. simulation of water flow, solute transport and plant growth in the soil-water-atmosphere-plant environment, Technical Document 53. DLOW in and Staring Centre, Wageningen.
  16. Mohammadi, E., Hassanli, M., Gharahdaghi, M. M., & Mohammadi, M. )2014(. Soil moisture and salinity assessment using SALTMED model in Sistan climatic conditions. In: 2nd Iranian Conference on Agricultural Soil and Water Management, 20-21 May, Karaj, Iran. (In Persian).
  17. Mostafazadeh-Fard, B., Mansouri, H., Mousavi, S. F., & Feizi M. (2008). Application of SWAP model to predict yield and soil salinity for sustainable agriculture in an arid region. International Journal of Sustainable Development and Planning, 3(4), 334-342.
  18. Nahvinia, M., Moaveni, B., & Shahidi, A. (2018). Assessment of SWAP model in estimating the salinity and soil moisture content (Case study: Birjand). Iranian Journal of Irrigation and Drainage, 12(5), 1174-1188. (In Persian).
  19. Nahvinia, M., Shahidi, A., Parsinejad, M., & Karimi, B. (2010). Assessing the performance of SWAP model in estimating the production of wheat under salinity and water stress (Case study: Birjand, Iran). Iranian Water Research Journal, 4(6), 43-58. (In Persian).
  20. Nasrollahi, A., Boroomand Nasab, S., Hooshmand, A., & Heydarinia, M. (2016). Evaluation of the SALTMED model under different managements of drip irrigation with saline water. Iranian Journal of Soil and Water Research, 47(3), 561-567. (In Persian).
  21. Noshadi, M., Fahandej-Saadi, S., & Sepaskhah, A. R. (2020). Application of SALTMED and HYDRUS-1D models for simulations of soil water content and soil salinity in controlled groundwater depth. Journal of Arid Land, 12, 447-461.
  22. Ragab, R. )2002(. A holistic generic integrated approach for irrigation, crop and field management: the SALTMED model. Environmental Modelling and Software, 17, 345-361.
  23. Reddy, K. R., Boone, M. L., Reddy, A. R., Hodges, H. F., Turner, S. B., & McKinion, J. M. (1995). Developing and validating a model for a plant growth regulator. Agronomy Journal, 87(6), 1100-1105.
  24. Ragab, R., Malash, N., Abdel Gawad, G., Arslan, A., & Ghaibeh, A. )2005(. A holistic generic integrated approach for irrigation, crop and field management: The SALTMED model validation using field data of five growing seasons from Egypt and Syria. Agricultural Water Management, 78, 89-107.
  25. Razzaghi, F., & Ghannadi, T. )2016(. Assessing SALTMED model for wheat experiments irrigated with basin and sprinkler systems. International Journal of Plant Production, 10(2), 233-250.
  26. Singh, P., & Virmani, S. M. )1996(. Modeling growth and yield of chickpea (Cicer arietinum). Field Crops Research, 46, 41–59.
  27. Šimůnek, J., Sejna, M., & van Genuchten, M. T. )1998(. The Hydrus-1D software package for simulating the one-dimensional movement of water, heat, and multiple solutes in variably saturated media. User’s Manual, Version 2.0, U.S. Salinity Laboratory, Agricultural Research Service, pp 178.
  28. Steduto, P., Hsiao, T.C., Raes, D., & Fereres, E. )2009(. AquaCrop-The FAO crop model to simulate yield response to water: I. Concepts and underlying principles. Agronomy Journal, 101, 426-437.