Testing and application of simple semi-analytical models for soil temperature estimation and prediction in environmental assessments.

The ability of various semi-analytical models to predict soil temperature profiles in an experimental plot during a 16-year monitoring study for soil depths up to 120 cm is evaluated. The models are developed from an analytical model by replacing the steady-state soil temperature with easily obtained hourly and daily average temperature values. Such values include the hourly air temperature, the daily average air temperature, the hourly soil temperature of selected soil depths from three daily observations, the daily average of the soil temperature profile and the hourly soil temperature for the bottom depth. The performance evaluation results show that, in principle, all models exhibit high correlation (R values in the range 0.85-0.97), indicating a very good agreement between measured and predicted values. In addition, error statistics reveal that the best performance in terms of Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) is the model based on the daily average of the soil temperature profile with MAE values in the range of 0-0.4°C and RMSE values in the range of 0.1-1.5°C.