Volume 21, Issue 2 (2019)                   JAST 2019, 21(2): 487-499 | Back to browse issues page

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Raoof M, Azizi Mobaser J. Reference Evapotranspiration Estimation Using Locally Adjusted Coefficient of Angstrom’s Radiation Model in an Arid-Cold Region. JAST 2019; 21 (2) :487-499
URL: http://jast.modares.ac.ir/article-23-14331-en.html
1- Water Engineering Department, University of Mohaghegh Ardabili, Islamic Republic of Iran.
Abstract:   (2730 Views)
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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Article Type: Research Paper | Subject: Agricultural Economics/Agriculture Marketing and Supply Chains
Received: 2017/03/11 | Accepted: 2018/07/10 | Published: 2019/03/2

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