Investigation of effect metrological variables on different depth of temperature and its estimation base on regression method in Guilan province

Soil is the base of plant growth and has a significant effect on agricultural production. On the other hand, this section of the ecosystem is strongly affected by climate factors. The aim of this study was to investigate the relationship between meteorological variables with soil temperature at different depthes and to use the most effective factor for estimation of it  using the regression method without the need for more complex models in stations of Guilan province. Therefore, the relationship between meteorological data including air temperature at 2m-elevation, cloudiness, sunshine hours, rainfall, relative humidity, evaporation, and wind speed with soil temperature at depths of 5, 10, 20, 30, 50, and 100 cm at stations of Guilan province in a 10-year period from 2009 to 2018 was studied by correlation analysis. Finally, a regression equation was developed based on 70 percent of the data and it was validated by another 30 percent of the data to estimate soil temperature at different depths. The results illustrated that among the various independent variables, the average daily temperature at 2m-elevation had the highest correlation with the soil temperature at different depths. The correlation coefficient for different station was 0.70 - 0.97. Finally, it can be concluded that the regression method is an acceptable method for estimation of soil temperature at different depths, especially at shallower depths. So that the RMSE values range from 1.7 to 4.9 ° C and the determination coefficient values range from 0.62 to 0.96.