Climatic Factors on Variability of Four Dry Farming Yields in Mashhad and Birjand

Prediction of crop yield is one of the managerial and planning tools in agriculture. Meteorological variables and drought indices play an essential role in yield prediction. In this study, the yield of four crops, namely wheat, barley, chickpea and watermelon was predicted in Mashhad and Birjand regions based on meteorological variables and drought indices using three regression models of Ridge, Enter and Step Wise. For this purpose, ten meteorological parameters and seven drought indices were used in three structures as input multivariate regression models. Results showed that among the meteorological variables, the two variables: number of rainy days and maximum air temperature had higher correlation with crops under study. Similarly, among drought indices, Nguyen index showed such higher correlation. It was found that Ridge multivariate model including weather parameters and meteorological drought indices could be recommended instead of two structures of meteorological variables and drought indices for yield prediction. This recommendation was based on multiple regression analysis and higher determination coefficient (R2) and a lower normal root mean squared error (NRMSE). Also, determination coefficients for all four products in both regions were from 0.91 to 0.99 and NRMSE from 0.09 to 0.48. Results also showed that the most prediction accuracy was for wheat with R2 of 0.996 and NRMSE of 0.09 in Mashhad and for chickpea with R2 of 0.999 and NRMSE of 0.09 in Birjand. Similarly,the least accurate prediction belonged to watermelon having R2 of 0.92 and NRMSE of 0.48 in Birjand and R2 of 0.96 and NRMSE of 0.27 in Mashhad. Overally, due to high R2 and low NRMSE, Ridge regression model is recommended for both regions.