Pattern Changes Analysis Of Soil Temperature In Different Depths Under The Influence Of Humidity And Air Temperature (Case Study: Taleghan Watershed)

In this study, to analyze the pattern of soil temperature changes in the depths of  5, 10, 20, 30, 50 and 100 cm under the influence of temperature (minimum, average and maximum) and humidity (minimum, average and maximum) the Pearson and regression methods were used for Taleghaan synoptic station during the period of 2008 to 2016 . The results showed that soil temperature had the highest correlation coefficient with air temperature while the lowest correlation was found with air humidity time series. So that the maximum coefficient of determination of air temperature and humidity was in a depth of 5 cm whereas the lowest was found in a depth of 100 cm. In order to estimate the deep soil temperature using temperature and humidity variables, the regression models were fitted by 70% to 30% of data for calibration and validation stages, respectively. So to evaluate the accuracy of the calibration and validation stages the NSE and RMSE error criteria were used. In general, the results indicated that the presented regression models had very good and acceptable performance to estimate soil temperature and also with increasing soil depths, correlation coefficient has decreased while error evaluation criteria has increased.