An Empirical Model for Estimating Soil Thermal Conductivity from Texture, Water Content, and Bulk Density

2014 ◽  
Vol 78 (6) ◽  
pp. 1859-1868 ◽  
Author(s):  
Yili Lu ◽  
Sen Lu ◽  
Robert Horton ◽  
Tusheng Ren
Keyword(s):  
Thermal Conductivity ◽  
Water Content ◽  
Bulk Density ◽  
Empirical Model ◽  
Soil Thermal Conductivity

scholarly journals An Empirical Model for Estimating Soil Thermal Conductivity from Soil Water Content and Porosity

2016 ◽  
Vol 17 (2) ◽  
pp. 601-613 ◽  
Author(s):  
Bing Tong ◽  
Zhiqiu Gao ◽  
Robert Horton ◽  
Yubin Li ◽  
Linlin Wang
Keyword(s):  
Thermal Conductivity ◽  
Water Content ◽  
Empirical Model ◽  
Large Scale ◽  
Soil Heat Flux ◽  
Soil Thermal Conductivity ◽  
New Model ◽  
Scale Models ◽  
Complex Models ◽  
Mean Square Errors

Abstract Soil thermal conductivity λ is a vital parameter for soil temperature and soil heat flux forecasting in hydrological models. In this study, an empirical model is developed to relate λ only to soil volumetric water content θ and soil porosity θs. Measured λ values for eight soils are used to establish the empirical model, and data from four other soils are used to evaluate the model. The new model is also evaluated by its performance in the Simple Biosphere Model 2 (SiB2). Results show that the root-mean-square errors (RMSEs; ranging from 0.097 to 0.266 W m−1 K−1) of the new model estimates of λ are lower than those (ranging from 0.416 to 1.006 W m−1 K−1) for an empirical model of similar complexity reported in the literature earlier. Further, with simple inputs and equations, the new model almost has the accuracy of other more complex models (RMSE of λ ranging from 0.040 to 0.354 W m−1 K−1) that require additional detailed soil information. The new model can be readily incorporated in large-scale models because of its simplicity as compared to the more complex models. The new model is tested for its effectiveness by incorporating it into SiB2. Compared to the original SiB2 λ model, the new λ model provides better estimates of surface effective radiative temperature and soil wetness. Owing to the newly presented empirical model’s requirement for simple, available inputs and its accuracy, its usage is recommended within large-scale models for applications where detailed information about soil composition is lacking.

The effect of soil temperature and soil water content on thermal properties in an artificial forestland and a natural regrowth grassland

2020 ◽  
Author(s):  
Tangtang Zhang ◽  
Xin Ma
Keyword(s):  
Thermal Conductivity ◽  
Thermal Properties ◽  
Soil Temperature ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Soil Condition ◽  
Soil Thermal Conductivity ◽  
Soil Thermal Properties ◽  
Increasing Temperature

<p>Soil temperature, soil water content and soil thermal properties were measured in an artificial forestland and a natural regrowth grassland from November in 2017 to July in 2019. The results show that the effects of soil temperature and soil water content on thermal properties are different in different soil condition. Soil thermal conductivity (K) and soil volumetric heat capacity (C) increase with increasing temperature in unfrozen period, but soil diffusivity (D) has no significant dynamic cycle and it almost keeps a constant level in a certain time. Soil thermal conductivity (K) decreases with increasing temperature during soil frozen period. The C and K increase with increasing soil water content in unfrozen period, while the D decrease with increasing soil water content.</p>

scholarly journals Experimental And Numerical Invetigation Of Dependence Of Soil Thermal Conductivity On Temperature Water Content, And Soil Texture

2021 ◽  
Author(s):  
Behnam Jowkar-Baniani
Keyword(s):  
Thermal Conductivity ◽  
Water Content ◽  
Soil Texture ◽  
Conductivity Data ◽  
Soil Thermal Conductivity ◽  
Pump System ◽  
Heat Pump System ◽  
Thermal Conductivity Data ◽  
Apparent Thermal Conductivity ◽  
The Impact

Comprehensive set of thermal conductivity data for a loam soil was generated, for temperature variations from 5ºC to 92ºC and water content variations from dry to saturation, and compared to two other soil textures. The results exhibited similar characteristics as those of the other textures, where a significant change in soil thermal conductivity was. Using the thermal conductivity data sets, a model representing heat and mass transfer in soil was used to study the apparent thermal conductivity due to vapour migration. In addition, a computer simulation of a ground source heat pump system was developed, where the experimental data was used to investigate the impact of water content and soil texture variation on the GSHP performance. It was observed that the GSHP energy consumption varied more prominently when the soil wetness varied from dryness to full saturation and less significantly when the soil type varied from coarse to finer texture.

scholarly journals Experimental And Numerical Invetigation Of Dependence Of Soil Thermal Conductivity On Temperature Water Content, And Soil Texture

2021 ◽  
Author(s):  
Behnam Jowkar-Baniani
Keyword(s):  
Thermal Conductivity ◽  
Water Content ◽  
Soil Texture ◽  
Conductivity Data ◽  
Soil Thermal Conductivity ◽  
Pump System ◽  
Heat Pump System ◽  
Thermal Conductivity Data ◽  
Apparent Thermal Conductivity ◽  
The Impact

Comprehensive set of thermal conductivity data for a loam soil was generated, for temperature variations from 5ºC to 92ºC and water content variations from dry to saturation, and compared to two other soil textures. The results exhibited similar characteristics as those of the other textures, where a significant change in soil thermal conductivity was. Using the thermal conductivity data sets, a model representing heat and mass transfer in soil was used to study the apparent thermal conductivity due to vapour migration. In addition, a computer simulation of a ground source heat pump system was developed, where the experimental data was used to investigate the impact of water content and soil texture variation on the GSHP performance. It was observed that the GSHP energy consumption varied more prominently when the soil wetness varied from dryness to full saturation and less significantly when the soil type varied from coarse to finer texture.

scholarly journals Mediate relation between electrical and thermal conductivity of soil

2020 ◽  
Vol 6 (3) ◽  
Author(s):  
Hans Schwarz ◽  
David Bertermann
Keyword(s):  
Thermal Conductivity ◽  
Electrical Conductivity ◽  
Water Content ◽  
Bulk Density ◽  
Geophysical Methods ◽  
Heat Extraction ◽  
Geothermal Systems ◽  
Corrective Factor ◽  
Thermal Conductivity Model

Abstract Thermal conductivity is a key parameter for many soil applications, especially for dimensioning shallow and very shallow geothermal systems based on the possible heat extraction rate and for modelling heat transfer processes around high voltage underground cables. Due to the limited purview of direct thermal conductivity measurements, for an investigation of extensive areas, usually other geophysical methods like electrical resistivity tomography measurements are applied. To derive thermal conductivity of soil from geoelectrical measurements a relation between electrical and thermal conductivity is needed. Until now only few approaches worked on a direct correlation between both conductivities. Due to the difficulties of a direct relation, within this study a modular approach of a mediate correlation between electrical and thermal conductivity was investigated. Therefore, a direct relationship between a corrected electrical conductivity and water content as well as the standard and simple thermal conductivity model of Kersten (Bull of the Univ Minnesota 28:1–227, 1949) was used. To develop this concept soil types of sand, silt loam and clay were investigated where different saturation steps and pressure loads were applied. For each configuration electrical and thermal conductivity as well as water content and bulk density was determined. To refine the results of the calculated water content a corrective factor was applied. Furthermore, bulk density as an inlet parameter of the Kersten equation was also derived based on electrical conductivity. The suggested proceeding enables the determination of thermal conductivity solely based on electrical conductivity without prior soil property information.

Analytical Determination of Soil Thermal Conductivity and Diffusivity

1988 ◽  
Vol 110 (4) ◽  
pp. 306-312 ◽  
Author(s):  
J. G. Ingersoll
Keyword(s):  
Thermal Conductivity ◽  
Moisture Content ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Soil Porosity ◽  
Analytical Determination ◽  
Seasonal Temperature ◽  
Soil Thermal Conductivity ◽  
Dry Soil

A simple model has been developed that can be used to calculate the soil thermal conductivity and diffusivity on the basis of the following factors: soil porosity; soil water content; conductivity, specific heat, and density of the constituents of soil, i.e., solid matter, water, and air. The model assumes that the void space in soil can be presented by a combination of plane fissures, whose direction is either parallel to the heat flow or perpendicular to it. A coefficient introduced to account for this combination in the two directions can be estimated from measured data as a function of the soil water content. Moreover, it is assumed that air and moisture conduct heat across the fissures in parallel. It is found that soil conductivity and diffusivity increase relatively rapidly with a few percent addition of moisture to entirely dry soil. For instance, assuming a typical soil porosity of 40 percent we conclude that the ratio of soil diffusivities of saturated to dry soil is about four, while that of soild with 2.5 percent moisture content to dry soil is a little over two. That is to say, a small moisture addition to dry soil brings the diffusivity half way to its saturation value. Since soil always contains small amounts of moisture, this finding explains the fact that measured seasonal temperature damping factors in extreme humid and extreme arid climates differ by less than a factor of two even though the moisture content of the respective soils may differ by more than an order of magnitude.

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