Evaluation of Multiple Ridge Regression Model to Estimation of Pan Evaporation

Abstract
     Evapotranspiration is one of the most important parameters in the Planning and operation of reservoirs, designing of irrigation systems. The practical importance of accurate estimates of evaporation and the complexity of effect phenomenon, shows the use of new methods of data mining. In this study, the simulation of pan evaporation in Tabriz station using multiple regression models were investigated. Meteorological data, including maximum and minimum air temperature, dew point, maximum and minimum air relative humidity, number of sunshine hours and Daily wind speed during (1992-2012) were used in synoptic Tabriz stations. Various models of multiple linear regression and nonlinear one  were derived for Tabriz station. The selected multiple linear regression model were tested by Ridge Regression method to be considered multi-collinearity among inputs in the model.Variance inflation factor, values for each variable were calculated. The results showed that all Variance inflation factor ,s had the value less than 10. In addition, the ratio  for two- variable selected model was 3.34. Therefore, there was no multi-collinearity in the selected multiple linear regression model f (Tmin, n). Durbin-Watson statistic for the selected model was 1.45 that shows the reliability of the selected multiple linear regression model. RMSE and R
²
values of the selected models (multiple linear regression and Non- Linear Regression) was calculated as 2.45 and 0.67 and 2.58 and 0.65, respectively. This results demonstrate the ability of regression techniques to estimate Pan evaporation in Tabriz station.