Reference Evapotranspiration Estimation Using Locally Adjusted Coefficient of Angstrom’s Radiation Model in an Arid-Cold Region

Authors
M. Raoof
J. Azizi Mobaser
Water Engineering Department, University of Mohaghegh Ardabili, Islamic Republic of Iran.
Abstract
Acceptable estimation of reference Evapotranspiration (ET0) values by the Penman-Monteith FAO (PM FAO) equation requires accurate solar radiation (Rs) data. Rs values could be estimated using the Angstrom’s radiation model. The aim of this study was to determine the as and bs coefficient (as Angstrom’s parameters) for the Ardabil plain as an arid and cold region. Angstrom’s radiation model and PM FAO equation were calibrated for the study area, by optimizing the as and bs parameter using Generalized Reduced Gradient (GRG) method. Measured Rsdata were collected from the Ardabil Synoptic Station and measured ET0 data were determined using three lysimeters that were installed at the Hangar Research Station. Calibrated results showed that optimized as and bs values were 0.117 and 0.384, respectively. Compared to the original models, errors including RMSE, AE and RE values were decreased and fitted parameters including R2 and regression line slope (m) were improved in the calibrated models. The GMER values for the original models showed that Angstrom’s radiation model overestimated the Rs values and PM FAO equation underestimated the ET0 values. Locally calibrated models estimated Rs and ET0 values better than the original one. Nash-Sutcliffe efficiency coefficient (NSE) values proved that Rs and ET0 estimation by the original models were not satisfactory, but were acceptable in the case of the calibrated models. However, calibration of Angstrom’s radiation model and PM FAO equation is necessary for each region.

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1. Allen, R. G., Pereira, L.S., Raes, D. and Smith, M. 1998. Crop Evapotranspiration Guidelines for Computing Crop Water Requirement. Food and Agriculture Organization of the United Nations, Rome, PP. 20-28.
2. Allen, R. G., Pereira, L. S., Raes, D. and Smith, M. 2006. Crop Evapotranspiration Guidelines for Computing Crop Water Requirements. Paper No. 56, FAO Irrigation and Drainage, PP.:98-107.
3. Antonio, R. P. 2004. The Priestley–Taylor Parameter and the Decoupling Factor for Estimating Reference Evapotranspiration. Agric. For. Meteorol., 125: 305–313.
4. Bakhtiari, B., Ghahreman, N., Liaghat, A. M. and Hoogenboom, G. 2011. Evaluation of Reference Evapotranspiration Models for Semiarid Environment Using Lysimeter Measurements. J. Agr. Sci. Tech., 13: 223-237.
5. da Silva, V. J., Carvalho, H. D., da Silva, C. R., de Camargo, R. and Teodoro, R. E. F. 2011. Performance of Different Methods of Estimating the Daily Reference Evapotranspiration in Uberlandia, MG. Biosci. J. Uberlândia, 27(1): 95-101
6. Doorenbos, J. and Kassam, A. H. 1979. Yield Response to Water. Paper No. 33, FAO Irrigation and Drainage, FAO, Rome, Italy, 193 PP.
7. Feltrin, R. M., de Paiva, J. B. D., de Paiva, E. M. C. D and Beling, F. A. 2011. Lysimeter Soil Water Balance Evaluation for an Experiment Developed in the Southern Brazilian Atlantic Forest Region. Hydr. Process., 25(15): 2321-2328.
8. Gocic´, M., Motamedi, S., Shamshirband, S., Petkovic´, D., Sudheer, C., Hashim, R. and Arif, M. 2015. Soft Computing Approaches for Forecasting Reference Evapotranspiration. Comp. Elec. Agric., 113: 164–173.
9. Gocic´, M., Petkovic´, D. and Shamshirband, S. 2016. Comparative Analysis of Reference Evapotranspiration Equations Modelling by Extreme Learning Machine. Comp. Elec. Agric., 127: 56–63.
10. Hossein, D., Tahei, Y. and Velu, R. 2004. Assessment of Evapotranspiration Estimation Models for Use in Semi-arid Environments. Agri. Water Manage., 64: 91–106.
11. Jacovides, C. P. and Kontonyiannis, H. 1995. Statistical Procedures for the Evaluation of Evapotranspiration Computing Models. Agric. Water Manage., 27: 365-371.
12. López-Urrea, R., Martín de Santa Olalla, F., Fabeiro, C. and Moratalla, A. 2006. Testing Evapotranspiration Equations Using Lysimeter Observations in a Semiarid Climate. Agri. Water Manage., 85: 15-26.
13. Meshram, D. T., Gorantiwar, S. D., Mitral, H. K. and Purohit, R. C. 2010. Comparison of Reference Crop Evapotranspiration Methods in Western Part of Maharashtra State. J. Agro. Meteorol., 12(1): 44-46.
14. Mohawesh, O. E. 2011. Evaluation of Evapotranspiration Models for Estimating Daily Reference Evapotranspiration in Arid and Semiarid Environments. Plant Soil Environ., 57(4): 145-152.
15. Petkovic´, D., Gocic´, M., Shamshirband, Sh., Qasem, S. N. and Trajkovic, S. 2016. Particle Swarm Optimization-Based Radial Basis Function Network for Estimation of Reference Evapotranspiration. Theor. Applied Climat., 125(3): 555–563.
16. Petkovic´, D., Gocic´, M., Trajkovic, S., Shamshirband, Sh., Motamedi, Sh., Hashim, R. and Bonakdari, H. 2015. Determination of the Most Influential Weather Parameters on Reference Evapotranspiration by Adaptive Neuro-Fuzzy Methodology. Comp. Elec. Agric., 114: 277–284.
17. Shamshirband, Sh., Amirmojahedi, M., Gocic´, M. and Akib, Sh. 2016. Estimation of Reference Evapotranspiration Using Neural Networks and Cuckoo Search Algorithm. J. Irrig. Drain. Eng., 142(2).
18. Temesgen, B., Eching, S., Davidoef, B. and Frame, K. 2005. Comparison of Some Reference Evapotranspiration Equations for California. J. Irrig. Drain. Eng., 131(1): 73-84.
19. Trajkovic, S. 2007. Hargreaves Versus Penman-Monteith under Humid Conditions. J. Irrig. Drain. Eng., 133(1): 38-42.
20. Wagner, B., Tarnawski, V. R. Hennings., Müller, V., Wessolek, U. and Plagge, R. 2001. Evaluation of Pedo-Transfer Functions for Unsaturated Soil Hydraulic Conductivity Using an Independent Data Set. Geoderma, 102: 275-297.
21. Xu, C. Y. and Chen, D. 2005. Comparison of Seven Models for Estimation of Evapotranspiration and Groundwater Recharge Using Lysimeter Measurement Data in Germany. Hydrol. Process., 19: 3717–3734.
22. Xu, J. z., Peng, S. H., Luo, Y. F. and Wei, Z. 2009. Influences of Angstrom’s Coefficients on Estimate on Solar Radiation and Reference Evapotranspiration by Penman-Monteith Equation. Proceedings of 16th IAHR-APD Congress and 3rd Symposium of IAHR-ISHS, October 20-23 2008, Hohai University, Nanjing, China.
23. Xu, J. z., Peng, S. H., Yang, S. H., Luo, Y. F. and Wang, Y. J. 2012. Predicting Daily Reference Evapotranspiration in a Humid Region of China by the Locally Calibrated Hargreaves-Samani Equation Using Weather Forecast Data. J. Agr. Sci. Tech., 14: 1331-1342.
24. Xu, J. Z., Peng, S. Z., Zhang, R. M. and Li, D. X. 2006. Neural Network Model for Reference Crop Evapotranspiration Prediction Based on Weather Forecast. J. Hydrau. Eng., 37(3): 376-379. (in Chinese).
25. Young M. H., Wierenga P. J. and Mancino C. F. 1996. Large Weighing Lysimeters for Water Use and Deep Percolation Studies. Soil Sci., 161: 491-501.
Journal of Agricultural Science and Technology
Volume 21, Issue 2
March and April 2019
Pages 487-499