عنوان مقاله [English]
Background and objectives: Background and objectives: Soil surface temperature has a key role in the mass and energy interchange between soil and atmosphere and it is an important input parameter to running the heat, water and carbon balance estimating models in the soil-plant-atmosphere system and weather and climate simulating models as well at the regional and global scales and the whole soil surface energy balance components are affected by soil surface temperature. Instead of the high important and remarkable application of soil surface temperature, its measurements is performed just in the synoptic meteorological stations and in an imperfect manner (just the minimum daily soil surface temperature) and so, it is essential to simulate this important variable by appropriate methods.
Materials and Methods: In this research, two methods including soil surface energy balance model and
satellite images were used to estimating daily mean soil surface temperature in the Sararoud-Kermanshah agro-meteorological station which has the recorded data of both maximum and minimum soil surface temperature at the 2013 to 2014 time period. Estimating daily mean soil surface temperature based on the satellite images was performed by considering the MODIS sensor images at four different times including 22:30, 1:30; 10:30 and 13:30 using the MRT software and to running the soil surface energy balance model, the daily meteorological data including air temperature, wind speed, sunshine and relative humidity along with some soil physical properties were used as the model inputs and the efficiency of these methods was evaluated using some evaluating error indices.
Results: By applying the MODIS sensor images, the results showed that from different combination cases of soil surface temperature at the mentioned imaging times, calculating daily mean soil surface temperature based on the averaging of soil surface temperatures at 22:30, 1:30 and 10:30 times was led to gaining the highest agreement with soil surface temperature observations and the absolute error and determination coefficient of this method to estimating daily mean soil surface temperature were 2.1 °C and 0.93, respectively. by applying the soil surface energy balance model to estimating daily mean soil surface temperature, the absolute error and determination coefficient were 1.8°C and 0.96, respectively. The results of the seasonal time series analysis showed that by using the soil surface energy balance model and satellite images, the highest agreement between calculated and observed values was occurred at summer and winter, respectively.
Conclusion: The overall results of this research showed reasonable and appropriate accuracy of both applied methods but the soil surface energy balance model is suggested because of its higher accuracy. Therefore, it is possible to adopt the applied methodology of this research to simulate the mean soil surface temperature in different regions and the estimated values of the daily mean soil surface temperature could be used to different applications such as soil temperature and moisture simulating models as an input variable.