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A simplified de V ries‐based model to estimate thermal conductivity of unfrozen and frozen soil
Author(s) -
Tian Z.,
Lu Y.,
Horton R.,
Ren T.
Publication year - 2016
Publication title -
european journal of soil science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.244
H-Index - 111
eISSN - 1365-2389
pISSN - 1351-0754
DOI - 10.1111/ejss.12366
Subject(s) - silt , thermal conductivity , mineralogy , soil science , air temperature , soil test , environmental science , soil water , geology , thermodynamics , atmospheric sciences , geomorphology , physics
Soil thermal conductivity ( λ ) is an important property in soil physics, environmental science, thermal science and engineering disciplines. In situ measurement of λ is complicated and there is a need for a model to predict λ accurately in both unfrozen and frozen soil. In this research, we developed a simplified de V ries‐based model to estimate λ of both unfrozen and frozen soil. The simplified model follows the basic assumptions of the de V ries model, but simplifies or improves the estimates of λ air , λ minerals and g a(minerals) , g a(air) and g a(ice) ( g a are the shape factors for various soil components): λ minerals and g a(minerals) are related to soil mineral composition, and g a(air) and g a(ice) are related linearly to the volumetric fractions of air and ice, respectively. The λ and g a values of sand, silt and clay are required for calculating λ minerals and g a(minerals) . The values of λ silt and g a(silt) , however, are not available in the literature. In this research, we estimated λ silt and g a(silt) by fitting the simplified model to measured λ values of 17 soil samples with various textures, water contents and bulk densities. The simplified model was validated with measured λ data from an additional 10 unfrozen and 18 frozen soil samples, obtained either from the literature or from our own measurements. The performance of the simplified model was evaluated by comparing estimates of λ with those from other available models. The results showed that the simplified de V ries‐based model provided accurate and consistent data for λ , and it performed better than other de V ries‐based models. Highlights We developed a simplified de V ries‐based model to estimate thermal conductivity, λ , of unfrozen and frozen soil. We improved methods to calculate thermal conductivities of soil air and minerals and shape factors of minerals, air and ice. Thermal conductivity and shape factor of silt were estimated with inverse modelling. Our new, simplified model gave more accurate predictions of λ than did other de V ries‐based models.