Abstract

Soil temperature is one of the most important parameters affecting hydro-climatic and agricultural processes. Since it is measured only in the synoptic meteorological stations, lack or deficiency of data is the major challenge in many agricultural studies. In this study, soils temperature were predicted at six different depths of 5, 10, 15, 30, 50 and 100 cm by Multivariate Linear Regression Models (MLRM) using meteorological parameters recorded at Bandar Abbas synoptic station during the period 1991-2013. The meteorological parameters precipitation, evaporation, wind velocity, vapor water pressure, relative humidity, air temperature and ground water level were utilized in this work. Precipitation and ground water were studied in the form of SPI and GRI. Relationship between these factors was identified using the Pearson's correlation coefficient. Temperatures were estimated in difference depths using MLRM. There is a significant correlation among soil temperature with air temperature, pan evaporation for soil depth of 5cm and SPI-3 for soil of 100cm with R² 0.992, 0.885 and -0.71 respectively. It means that air temperature and relative humidity affects soil temperature directly while precipitation impacts soil temperature, inversely. Soil temperature decreased in wet month (P-value=-0/59), significantly. This research could provide a rapid estimation of soil temperature in different months using hydro climatic factors data