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This study describes the generation of a uniform data base of 2733 non-stationary thermal conductivity laboratory measurements of about 158 soil cores with varying texture, bulk density, soil organic matter, pH, and carbonate content. This data set has been used to validate ten well established pedo-transfer functions for predicting thermal conductivity by using easily available soil information such as soil texture, bulk density, and water content. Models were grouped into (i) physically based and (ii) empirical ones that need measured data for its calibration. The classical physical based transfer-function of deVries et al. has been finally chosen to set up a framework of standard values for the USDA soil classes. For planning purposes, these $$\lambda$$ λ estimates for selected pressure heads only need information on soil texture and bulk density and may be more valuable than single point values of thermal conductivity.

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