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Estimation of solar radiation based on air temperature and application with the DSSAT v4.5 peanut and rice simulation models in Thailand
Author(s)
Date Issued
October 15, 2013
Type
Article
Abstract
Estimation of solar radiation (SRAD) from daily air temperature by the modified Bristow-Campbell (B-C) model requires three empirical coefficients that are area specific. Previous estimates of these coefficients for Thailand were based on limited data without any evaluation. Accurate estimation of solar radiation has become more important with the wider application of environmental models. The objective of this study was to calibrate and evaluate the coefficients for Thailand with a broader range of data. Meteorological data from 2008 to 2011 were obtained from eight weather stations, three in the North (Chiang Mai, Chiang Rai and Nakhon Sawan), two in the Northeast (Khon Kaen and Ubon Ratchathani), one in the Central (Lop Buri) and two in the South (Chumporn and Surat Thani). Data for 2010 for all locations except Chiang Rai were used for calibration of the coefficients and the remaining data were used as independent data sets for evaluation. The coefficient of determination (R2), root mean square error (RMSE) and normalized root mean square error (RMSEn) were used as indicators of the agreement between the observed and the calculated SRAD. The results showed that the calibration was acceptable (R2=0.56, RMSE=3.07MJm-2d-1 and RMSEn=17.5%). The derived values are a=0.63, b=1.89 and c=1.54. These new coefficients performed well during evaluation with the 13 independent data sets from the eight locations for all four regions, with the R2, RMSE and RMSEn values in the range of 0.39-0.70, 2.42-3.79MJm-2d-1 and 14.0-21.7%, respectively. In addition, simulations using estimated SRAD from the derived values provided high R2 values for peanut and rice yield and total dry matter. These new coefficient values can be used to estimate solar radiation from air temperature data for all locations in Thailand and similar environments in Southeast Asia. © 2013 Elsevier B.V.
Citation
Agricultural and Forest Meteorology, 180, 182-193, 2013