Journal of Arid Regions Geographic Studies

Journal of Arid Regions Geographic Studies

Evaluation and Calibration of Makkink Model in Estimating Reference Evapotranspiration in Windy Areas of Iran

Document Type : Original Article

Authors
1 Water Engineering Department, Faculty of water and soil, University of Zabol, Zabol, Iran
2 Department of Water Engineering, Faculty of Water and Soil, University of Zabol, Zabol, Iran
Abstract
Aim: The aim of this research was to investigate the impact of wind speed on the accuracy of the Makkink (MK) method in calculating reference evapotranspiration (ET0) and to modify the model coefficient for windy regions.
Materials & Methods: Long-term meteorological data from the Ardabil, Aligoudarz, Bijar, Torbat-e Jam, Rafsanjan, Zabol, and Manjil stations were utilized. The ET0 values obtained using the MK method were evaluated against those calculated using the FAO Penman-Monteith (PM) method. Finally, the MK model was calibrated, and its coefficient (α) was adjusted for the studied stations.
Finding: For the examined stations, the long-term average monthly ratio of ET0 estimated by the MK model to that estimated by the PM model versus the average monthly wind speed over the statistical period showed that as wind speed increased, the MK model estimated lower ET0 values compared to the PM model. The results revealed that the Zabol station, with an NRMSE higher than 5.5 and d less than 0.65, had the least agreement with the PM model, likely due to its high average wind speed. Ardabil station, with d greater than 0.97, provided the best results and could use the MK model without calibration to represent reference evapotranspiration.
Conclusion: A polynomial regression relationship between parameter α and wind speed was obtained for the Torbat-e Jam, Rafsanjan, and Zabol stations, with correlation coefficients of 0.79, 0.72, and 0.90, respectively. For the Ardabil, Aligoudarz, and Bijar stations, the model adjustment coefficient was derived by minimizing the sum of squared errors.
Innovation: The modified MK model developed in this study shows good agreement with the PM model for the examined stations and can therefore be used as a simpler alternative to the standard PM model, which requires extensive meteorological data.
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Articles in Press, Corrected Proof
Available Online from 01 May 2026

  • Receive Date 18 April 2025
  • Revise Date 12 June 2025
  • Accept Date 12 June 2025
  • Publish Date 01 May 2026