Application of Shuffled Frog Leaping Algorithm for calibration of several solar radiation models with the aim of improving the accuracy of estimating reference evapotranspiration in two climatic samples of Iran

Document Type : Original Article

Authors

1 PhD Candidate in Water Structural Engineering, Department of Water Engineering, Faculty of Agriculture, Shahid Bahonar University of Kerman, Kerman, Iran

2 Water Eng. Department, Faculty of Agriculture, Shahid Bahonar University of kerman

3 Water engineering department, Agriculture faculty, Bahonar university of Kerman, Kerman, Iran.

4 Department of Water Engineering, Faculty of Agriculture, Shahid Bahonar University of Kerman, Kerman, Iran;

Abstract

The FAO Penman-Monteith (FAO-56 PM) model is proposed as a standard model to estimate reference evapotranspiration (ETO) in various climates. Different models are used to estimate the total solar radiation (Rs) as one of the essential inputs of this model. This study aimed to calibrate and validate four Rs estimation models (Ångström-Prescott, Hargreaves-Samani, Mubiru et al., and Chen and Li) in Ahvaz (with arid climate) and Hamedan (with semi-arid climate) stations during the 1992-2020 climate period and the effect of these models on the ETO estimation. The coefficients of these models were calibrated by the intelligent shuffled frog leaping algorithm (SFLA). To evaluate the efficiency of these models, the estimated Rs values were compared with measured values. Based on the root mean square error (RMSE), the coefficient of determination (R2) statistics and Nash-Sutcliffe, the A-P model with RMSE=1.929, R2=0.918, NS=0.896 and Mobiro et al. model with RMSE=2.925, R2=0.875, NS=0.860 showed better performance than the other models in Ahvaz and Hamedan stations, respectively. A decrease of about 20% was observed in the percentage of ETO difference between, the calculated and the estimated Rs compared to the measured Rs in 2 stations at all of the models.

Keywords

References

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Iranian Journal of Irrigation & Drainage
Volume 16, Issue 2 - Serial Number 92
May and June 2022
Pages 267-279

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