Abstract
The knowledge of the ground temperature profile with respect to time and depth is very important in many technological fields like geothermal heat pumps, solar energy systems and geotechnical applications. Many researches were performed in the past in order to evaluate this profile. The most common ones, known as energy balance models, use the energy balance equation as a boundary condition. Unfortunately the performance of these models strongly depends on an accurate estimation of several input factors. The objective of this paper is to develop an improved model for the prediction of the ground temperature profile in which the energy balance equation at the ground surface is supplemented by an empirical correlation for the annual average ground surface temperature calculation. This model is less sensitive to uncertainties of input factors. Furthermore, unlike the previous models, a periodic variation of the sky temperature is introduced instead of a previously assumed constant value. The model is validated against measured data in a site located in Varennes (Montreal-Canada) and two further sites, Fort Collins (Colorado) and Temple (Texas) in the U.S.A.
•A new model was developed to improve the prediction of the ground temperature profile.•The mean ground surface temperature is calculated using an empirical correlation.•A periodic variation of the sky temperature was used.•The developed model is less affected by the inaccuracy of input factors estimation.