Quantitative Survey of Drought Effects on Barley Yield in East Azerbaijan by Classical Statistical Methods

The growing season climatic parameters, especially rainfall, play the main role to predict the yield production. Therefore, the main objective of this research was to find out some possible relations among meteorology parameters and drought indexes with the yield using classical statistical methods. To achieve the objective, ten meteorological parameters and twelve drought indexes were evaluated in terms of normality and their mutual influences. Then the correlation analysis between the barley yield and the climatic parameters and drought indexes was performed. The results of this study showed that among the drought indexes, Nguyen Index, Transeau Index, Rainfall Anomaly Index and Standardized Precipitation Index (SPI24) are more effective for prediction of barely yield. It was also found that the multivariate regression is better than the univariate regression models. Finally, all the obtained regression models were ranked based on statistical indexes(R,RMSE and MBE). This study showed that the multivariate regression model including wind speed, sunshine, temperature summation more than 10, precipitation and Nguyen index is the best model for prediction yield production in Miane. Average wind speed and Nguyen index were recognized to be the most effective parameters for yield production in the model.