عنوان مقاله [English]
نویسندگان [English]چکیده [English]
The study of soil temperatures at different depths is significant from various perspectives, including meteorology, climatology, agriculture, industry, and other related bio - activities. Vertical distribution of temperature in soil depends upon three factors, namely:
1) the structure and physical characteristics of soil and its thermal properties;
2) land cover (bare, grass, snow, etc.);
3) the effect of climatologic factors including temperature, precipitation, wind, solar radiation, and humidity.
This paper reports the results of a statistical study on the relationship between ground and soil temperature at different depths (10, 50, and 100 cm) in five synoptic stations in Kermanshah province.
Exact measurement of ground heat flux is a formidable task. Most techniques measure the ground heat flux by measuring the soil temperature at different depths. Given the difficulty of such measurements, it seems that developing the statistical modeling's could be useful. Data were collected for daily minimum air temperatures (meteorological screen) and daily minimum ground temperatures, in addition to soil temperatures at 10, 50, and 100 cm depths at 6:30 am and 6:30 pm local time within a 14-years period (1993 to 2006), adopted from the Kermanshah Regional Meteorological Office. The data were then used to study the relationship between the ground and soil temperature at different depths. The paired-samples t-test was employed to analyze the data. In addition, a multivariate regression model was employed to estimate temperatures at various soil depths (10, 50, 100 cm) based upon variables including ground temperature, Julian day, and depth.
Results and Discussion
As we go down the soil profile in the stations, the mean annual minimum temperature increases and reaches its peak at a depth of 100 cm, mainly due to regular thermal conduction. However, during the warm periods of the year, temperaturesare higher at depths of 10 and 50 cm compared to the other depths, due to extra heating of layers close to the surface. The mean minimum temperatures are very similar at 50 and 100 cm depths. The paired-samples t-test indicated no statistically significant difference between the mean minimum annual temperatures at these two depths. Increase in the depth of the soil leads to a lesser annual temperature range, specifically the diurnal temperature range. The diurnal range almost disappears at the depth of 50 cm. It was also found that the diurnal temperature range at each depth was at its maximum during the summer. The annual temperature difference between ground and various depths increases up to 50 cm, but it levels at lower depths. The paired-samples t-test showed no significant difference between diurnal temperature ranges at 50 and 100 cm.
The similar behavior of temperature curves at different depths indicates that soil type does not have a significant role in distribution of temperature at various soil depths, regardless of climatic differences. In winter, the lowest minimum temperatures at 10, 50, and 100 cm depths, were delayed for 3, 13, and 33 days respectively compared with the lowest temperatures of the ground. This delay for the highest minimum temperatures was a few days longer in the summer
Soil temperature is an important feature that affects various activities. The results of the present study indicate that temperature irregularities are more frequent at ground, with such irregularities decreasing at lower depths. The similarity of results of the present study with previous researches regarding the one month delay of ground and soil depth temperatures indicates that soil type play a secondary role in thermal delay.
Given the difficulty of including various influencing factors in the models due to lack of sufficient data on the one hand, and relative inefficiency of numerical models in simulation of thermal distribution in soil on the other hand, it seems that employing empirical, semi –empirical and statistical models are useful measures to estimate temperatures at various soil depths. The multivariate regression model used in the present study efficiently estimated soil depth temperatures, specifically during spring and autumn. It should be noted that in all studies on the estimation of temperatures at various soil depths, it would be necessary to have a good understanding of soil layers properties, including physical characteristics, structure, thermal conductivity, etc. It should further be understood that no mathematical, statistical or empirical model can be used in different locations unless calibrated according to local conditions. We suggest that empirical, semi-empirical, deterministic and analytic models be employed to estimate soil depth temperatures, and the results be then compared with regression forecasting.
It could then be concluded that lowest temperatures reach more quickly than highest temperatures to a certain depth. The temperatures of various soil depths were estimated by employing a multivariate regression model with good accuracy at the stations for spring, autumn, and winter.