Daily and Seasonal Pistachio Evapotranspiration in Saline Condition: Comparison of Satellite-Based and Ground-Based Results

  • Mohammad Hassan Rahimian
  • Mohammad ShayannejadEmail author
  • Saeid Eslamian
  • Mahdi Gheysari
  • Reza Jafari
Research Article


This study was conducted in 2015 to estimate pistachio (Pistacia vera L.) water use in Marvast region, central Iran. Daily and seasonal pistachio actual evapotranspiration (ETa) was first estimated by running the surface energy balance algorithm for land (SEBAL) model, using 12 Landsat 8 satellite images and other ancillary data. Finally, SEBAL estimates of daily and seasonal water use over three experimental sites of pistachio orchards were compared against ones based on performing water balance analysis for the top 150 cm of the soil layer. For this purpose, a simple funnel-shaped device was made and used to collect the beneath rootzone drainage water and determine the leaching fraction (LF) as well as deep percolation at three scattered points across the sub-sections of each experimental site. The results reveal that the LF varies from 0.16 to 0.34, leading to deep percolation from 95.0 to 334.0 mm of the irrigation water. Eventually, the differences between ground-based and SEBAL-based pistachio ETa were 11% (ranged from 5.7 to 14.0%) and 10% (ranged from 7.1 to 16.4%) for daily and seasonal time scales, respectively. Based on the obtained results, more than 60% of Marvast pistachio orchards have seasonal water use of 410.0 to 680.0 mm (with the average of 594.3 mm), while the cumulative ETo and cumulative pistachio ETc of the same period were 1558.0 mm and 920.0 mm, respectively. In other words, Marvast pistachio trees extract less water from the soil compared with their potential water demands. This is due to the effect of salinity on reducing evapotranspiration rate as well as deficit irrigation of pistachio trees in the water scarce area of Marvast region. In any case, the difference between pistachio ETc and ETa is reflected in declination of the pistachio yield.


SEBAL Salinity Leaching fraction Modified WFD Landsat 8 



This research was supported by the National Salinity Research Center, NSRC, Iran. Authors of this manuscript would like to appreciate from Mr. Falahati, Mr. Zaareh, and Mrs. Besharat for their assistance in conducting this research and laboratory analysis.


  1. ASCE-EWRI. (2005). The ASCE standardized reference evapotranspiration equation. Task committee of calculation of reference evapotranspiration. ASCE-EWRI. p. 70.Google Scholar
  2. Bastiaanssen, W. G. M., Ahmad, M. D., & Chemin, Y. (2002). Satellite surveillance of evaporative depletion across the Indus Basin. Water Resources Research, 38, 9-1–9-5.CrossRefGoogle Scholar
  3. Bastiaanssen, W. G. M., Menenti, M., Feddes, R. A., & Holtslang, A. A. (1998). A remote sensing surface energy balance algorithm for land (SEBAL): 1. Formulation. Journal of Hydrology, 212–213, 198–212.CrossRefGoogle Scholar
  4. Bastiaanssen, W. G. M., Noordman, E. J. M., Pelgrum, H., Davids, G., Thoreson, B. P., & Allen, R. G. (2005). SEBAL model with remotely sensed data to improve water-resources management under actual field conditions. Journal of Irrigation and Drainage Engineering, 131, 85–93.CrossRefGoogle Scholar
  5. Cheraghi S. A. M., Hasheminejhad Y., & Rahimian M. H. (2009). An overview of salinity problem in Iran: assessment and monitoring technology. In: Advances in the assessment and monitoring of salinization and status of biosaline agriculture. World Soil Resources Reports No. 104., Rome: FAO. ISBN: 978-92-5-106439-9.Google Scholar
  6. Du, J., Song, K., Wang, Z., Zhang, B., & Liu, D. (2013). Evapotranspiration estimation based on MODIS products and surface energy balance algorithms for land (SEBAL) model in Sanjiang Plain, Northeast China. Chinese Geographical Science, 23, 73–91.CrossRefGoogle Scholar
  7. FAOSTAT. (2017). FAO statistics database. Accessed 20 Jan 2017.
  8. Gibson, L. A., Jarmain, C., Su, Z., & Eckardt, F. (2013). Review: Estimating evapotranspiration using remote sensing and the surface energy balance system—A South African perspective. Water SA, 39, 477–483.Google Scholar
  9. Goldhamer D. A., Beede R., Moore J. M., Weinberger G., & Menezes J. J. (1983). Water use requirements and physiological response to water stress in pistachio, (pp. 53–57). Annual report of the California Pistachio Commission, Crop Year 1982–1983.Google Scholar
  10. Hemakumara, H., Chandrapala, L., & Moene, A. (2003). Evapotranspiration fluxes over mixed vegetation areas measured from a large aperture scintillometer. Agricultural Water Management, 58, 109–122.CrossRefGoogle Scholar
  11. Hendrickx, J. M. H., Vink, N. H., & Fayinke, T. (1986). Water requirement for irrigated rice in a semi-arid region in West Africa. Agricultural Water Management, 11, 75–90.CrossRefGoogle Scholar
  12. Kanber, R., Yazar, A., Onder, S., & Koksal, H. (1993). Irrigation response of pistachio (Pistacia vera L.). Irrigation Science, 14, 7–14.CrossRefGoogle Scholar
  13. Karimi, P., & Bastiaanssen, W. G. M. (2015). Spatial evapotranspiration, rainfall and land use data in water accounting—Part 1: Review of the accuracy of the remote sensing data. Hydrology and Earth System Sciences, 19, 507–532.CrossRefGoogle Scholar
  14. Kite, G. W., & Droogers, P. (2000). Comparing evapotranspiration estimates from satellites, hydological models and field data. Journal of Hydrology, 229, 3–18.CrossRefGoogle Scholar
  15. Kizer, M. A., & Elliott, R. L. (1991). Eddy correlation systems for measuring evapotranspiration. Transactions of American Society of Agricultural Engineers, 34, 387–392.CrossRefGoogle Scholar
  16. Kleissl, J., Gomez, J. D., Hong, S. H., & Hendrickx, J. M. H. (2008). Large aperture scintillometer intercomparison study. Boundary-Layer Meteorology, 128, 133–150.CrossRefGoogle Scholar
  17. Moran, M. S., & Jackson, R. B. (1991). Assessing the spatial distribution of evapotranspiration using remotely sensed inputs. Journal of Environmental Quality, 20, 725–735.CrossRefGoogle Scholar
  18. Parlange, M. B., Eichinger, W. E., & Albertson, J. D. (1995). Regional scale evaporation and the atmosphere boundary layer. Reviews of Geophysics, 33, 99–124.CrossRefGoogle Scholar
  19. Poormohammadi, S., Rahimian, M. H., & Taghvaeian, S. (2012). Applying remotely-sensed energy balance models in Iran: potentials and limitations. In C. M. U. Neale & M. H. Cosh (Eds.), Remote sensing and hydrology (Vol. 352, pp. 141–144). Wallingford: IAHS Publ.Google Scholar
  20. Rahimian M. H., Taghvaeian S., Nouri M. R., Tabatabaei S. H., Mokhtari M. H., Hasheminejhad Y., & Neshat E. (2014). Estimating pistachio evapotranspiration using MODIS imagery: A case study from Ardakan, Iran, (pp. 1784–1794). World Environmental and Water Resources Congress 2014, ASCE, USA.Google Scholar
  21. Scott, R. L., Shuttleworth, J. W., Goodrich, D. C., & Maddock, T. (2000). The water use of two dominant vegetation communities in a semiarid riparian ecosystem. Agricultural and Forest Meteorology, 105, 241–256.CrossRefGoogle Scholar
  22. Stirzaker, R. (2003). When to turn the water off: Scheduling micro-irrigation with a wetting front detector. Irrigation Science, 22, 177–185.CrossRefGoogle Scholar
  23. Taghvaeian, S., & Neale, C. M. U. (2011). Water balance of irrigated areas: A remote sensing approach. Hydrological Processes, 25, 4132–4141.CrossRefGoogle Scholar
  24. Tasumi, M. (2003). Progress in operational estimation of regional evapotranspiration using satellite imagery. Ph.D. thesis, University of Idaho, Moscow, Idaho.Google Scholar
  25. Trezza, R. (2002). Evapotranspiration using a satellite-based surface energy balance with standardized ground control. Ph.D. thesis, Utah State University: Logan, Utah.Google Scholar
  26. Wright, J. L. (1982). New evapotranspiration crop coefficients. Journal of Irrigation and Drainage Engineering, 108, 57–74.Google Scholar
  27. Zwart, S. J., & Leclert, L. M. C. (2010). A remote sensing-based irrigation performance assessment: a case study of the Office du Niger in Mali. Irrigation Science, 28, 371–385.CrossRefGoogle Scholar

Copyright information

© Indian Society of Remote Sensing 2019

Authors and Affiliations

  • Mohammad Hassan Rahimian
    • 1
  • Mohammad Shayannejad
    • 2
    Email author
  • Saeid Eslamian
    • 2
  • Mahdi Gheysari
    • 2
  • Reza Jafari
    • 3
  1. 1.Agricultural Research Education and Extension Organization (AREEO), National Salinity Research Center (NSRC)YazdIran
  2. 2.Department of Water Engineering, College of AgricultureIsfahan University of TechnologyIsfahanIran
  3. 3.Department of Natural ResourcesIsfahan University of TechnologyIsfahanIran

Personalised recommendations