Showing 4 results for Reference Evapotranspiration
B Bakhtiari, A.m Liaghat, A Khalili, M.j Kjanjani,
Volume 13, Issue 50 (1-2010)
Abstract
In this study, the Penman-Monteith methods proposed by the Food and Agriculture Organization (FAO-56) and American Society of Civil Engineers (ASCE) were used for hourly ETo estimation under the semiarid climate of Kerman, Iran. Hourly ETo estimations obtained from the proposed methods were compared with measured ETo values by using a large weighing electronic lysimeter during April to September 2005 (totally 3352 hourly ETo data cases). Simple linear regression and statistical factors such as root mean square error and index of agreement were used for estimated and observed value comparison. The average of measured and estimated hourly ETo values using these methods for integrated data were 0.28 and 0.23 mm hr-1, respectively, which means that average estimated ETo values were approximately 21 percent less than the measured ETo values. This analysis was also performed for hourly data of each month during the study period. The results showed that FAO-56 Penman-Monteith underestimated ETo values by 18.4, 19.3, 26.3, 20.4, 21.4 and 22.1 percent for April to September, respectively, when compared with the measured values. Similarly, the ASCE Penman-Monteith underestimated ETo values by 17, 19.6, 18.4, 18.2, 19.7 and 20.9 percent for the same period, respectively, when compared with the lysimetric data. Finally, a set of regression equation for transformation of the estimated hourly data into the measured hourly ETo values has been presented for each month.
M. A. Moradi, A. Rahimikhoob,
Volume 16, Issue 62 (3-2013)
Abstract
Reference evapotranspiration (ET0) is a necessary parameter for calculating crop water requirements and irrigation scheduling. In this study, a method was presented as ET0 is estimated with NOAA satellite imagery in the irrigation network. In this method, a pixel from a set of pixels within the irrigation network was chosen with the highest vegetation index, and its surface temperature (Ts) with extraterrestrial radiation parameter (Ra) was used as inputs of the model. The M5 model tree for converting Ta and Ra to ET0 was used as input variables. In this research, Gazvin irrigated area was selected as a case study. A total of 231 images of NOAA satellite related to irrigation season of the study area were used. The results obtained by the M5 model were compared with the Penman–Monteith results, and error values were found within acceptable limits. The coefficient of determination (R2), percentage root mean square error (PRMSE) and the percentage mean bias error (PMBE) were found to be 0.81, 8.5% and 2.5%, respectively, for the testing data set.
H. Karimi Avargani, A. Rahimikhoob, M. H. Nazarifar,
Volume 23, Issue 3 (12-2019)
Abstract
In recent years, a lot of research has been done on the Aquacrop model, the results show that this model simulates the product performance for deficit irrigation conditions. But this model, like other models, is sensitive to values of independent variables (model inputs). In this research, the sensitivity of the Aquacrop model was analyzed for 4 input parameters of reference evapotranspiration, normalized water productivity, initial canopy cover percentage and maximum canopy cover for barley. Irrigation treatments included full irrigation and two deficit irrigation treatments of 80% and 60%, the experiment was done in 2014-15 growing season in the field of Abourihan College. The values of measured biomass were used as the base values for treatments. The Beven’s method (Beven et al., 1979) was used for sensitivity analysis of Aquacrop model. The results showed that the model is most sensitive to the reference crop evapotranspiration, So the sensitivity coefficient for this parameter for full irrigation treatments, 80% full irrigation and 60% full irrigation were -1.1, -1.2 and -2.3 respectively. The negative sign indicates that if the value of reference evapotranspiration input is exceeded the actual value into the model, Yield performance is simulated less than actual value. In the meantime, the higher the degree of deficit irrigation, the greater the sensitivity of the model.
Y. Sabzevari, M. Saeidinia,
Volume 25, Issue 2 (9-2021)
Abstract
The FAO Penman-Monteith is a baseline method to estimate reference evapotranspiration. In many cases, it is difficult to access all data, so replacing simpler models with lower input data and appropriate accuracy is necessary. The purpose of this study is to investigate the capability of the experimental models, gene expression programming, stepwise regression, and Bayesian network in estimating reference evapotranspiration. In this research, daily information of the Boroujerd synoptic station in the period of 1996 -2017 was used as model inputs. Based on the correlation between input and output parameters, six input patterns were determined for modeling. The results showed that the Kimberly-Penman model has the best performance among the experimental models. Gene expression programming with fourth pattern and Default Model Operators (R2 = 0.98 and RMSE = 0.9), Bayesian Network with sixth pattern (R2=0.91 and RMSE = 1.01), and stepwise regression with sixth pattern have the most accurate patterns at R2 = 0.91 and RMSE = 0.9 in the training stage. Comparison of the performance of the three models showed that the gene expression programming model was superior to the other two models with the Average Absolute Relative Error (AARE) of 0.12 and the Mean Ratio (MR) of 0.94. The results showed that gene expression programming had an acceptable ability to estimate reference evapotranspiration under the weather conditions of Boroujerd and could be introduced as a suitable model.
