Saturation-Dependent Thermal Conductivity of Southern Ontario Soils

Abstract

Soil thermal conductivity is an important parameter in geotechnical and environmental engineering applications, influencing the performance of underground energy storage, ground heat exchangers, and other subsurface thermal systems. Through geotechnical characterization and laboratory measurements, this study investigates the thermal conductivity of 20 soil samples collected from seven locations in Southern Ontario. The key soil properties, including texture, moisture content, and bulk density, were analyzed to understand their impact on thermal conductivity. Measured thermal conductivity values were compared with published regression-based and normalized models to assess their predictive accuracy across diverse soil types. A statistical evaluation incorporating root mean square error (RMSE), mean absolute error (MAE), and coefficient of determination (R²) was performed to identify the best-performing models. The results indicate that Lu et al. (2014) and Yoon et al. (2018) describe the most reliable regression-based models, demonstrating strong correlations with measured data, minimum bias, and low error margins. Among normalized models, the Côté and Konrad (2005) model exhibited superior adaptability and lower prediction errors, while Johansen’s (1975) model performed well but required calibration for extreme soil compositions. The results emphasize the significant influence of soil texture and moisture content on thermal conductivity, with silty and sandy soils exhibiting higher values due to their mineral composition and structural properties. The best-performing models effectively captured these variations, highlighting their applicability in geotechnical and environmental engineering.