Evaluation of Soil Thermal Conductivity Schemes for Use in Land Surface Modeling

Abstract

Soil thermal conductivity (STC) is an important physical parameter in modeling land surface processes. Previous studies on evaluations of STC schemes are mostly based on direct measurements of local conditions, and their recommendations cannot be used as a reference in selecting STC schemes for land modeling use. In this work, seven typical STC schemes are incorporated into the Common Land Model to evaluate their applications in land surface modeling. Statistical analyses show that the Johansen (1975) scheme and its three derivatives, Côté and Konrad (2005, https://doi.org/10.1139/t04-106), Balland and Arp (2005, https://doi.org/10.1139/s05-007), and Lu et al. (2007, https://doi.org/10.2136/sssaj2006.0041), are significantly superior to the other schemes with respect to both STC estimations and their applications in modeling soil temperature and the partitioning of surface available energy in the Common Land Model. The Balland and Arp (2005, https://doi.org/10.1139/s05-007) scheme ranks at the top among the selected schemes. Uncertainty analyses based on single-point and global simulations both show that the differences in STC estimations can induce significant differences in simulated soil temperature in arid/semiarid and seasonally frozen regions, especially at deep layers. The hydrology-related variables are slightly affected by STC variations, but slight changes in these variables can induce notable changes in soil temperature by altering soil thermal properties. These results emphasize the important role of STC in modeling soil thermodynamics and suggest the necessity of further developing STC schemes based on land modeling applications. According to the evaluation analyses, we recommend the Balland and Arp (2005, https://doi. org/10.1139/s05-007) scheme as a more suitable selection for use in land surface models.Plain Language Summary Soil thermal conductivity (STC) is essential for simulating soil temperature and heat flux in land surface models. Previous studies have proposed quite a few parameterization schemes to estimate STC. Although many works have tried to determine which scheme performed best, most of them were based on direct measurements from specific experimental conditions or local soil samples, and few studies have considered the performances of STC schemes in land surface modeling. Here, we present an evaluation of seven typical STC schemes based on their land modeling applications. The results show that four of the schemes, the Johansen (1975) scheme, Côté and Konrad (2005, https://doi.org/10.1139/t04-106) scheme, Balland and Arp (2005, https://doi.org/10.1139/s05-007) scheme, and Lu et al. (2007, https://doi.org/10.2136/sssaj2006.0041) scheme, perform comparatively better than the other schemes and that the Balland and Arp (2005, https://doi.org/10.1139/s05-007) scheme ranks at the top.Uncertainty analyses demonstrate that soil thermodynamics are strongly sensitive to STC estimates, especially in dry and partly frozen regions. This relationship highlights the important role of STC in modeli...

A Global High‐Resolution Data Set of Soil Hydraulic and Thermal Properties for Land Surface Modeling

“…Next, we use the newly proposed approach for soil water retention parameters and the median values of ensemble PTFs for K s to produce global data sets of soil hydraulic parameters. The soil thermal parameters are also provided following the method identified by Dai, Wei, et al ().…”

“…Table lists the soil hydraulic and thermal parameters associated with the widely used relationship between h ( θ ) ( K ( θ )) and θ (Campbell, ; Mualem, ; van Genuchten, ) and the parameterization schemes of c and k (Balland & Arp, ; Dai, Wei, et al, ; Johansen, ), which are incorporated into Equations () and (). Direct measurements of these parameters are difficult and time‐consuming, and especially impractical in large‐scale land surface modeling.…”

“…For soil hydraulic conductivity, we still use the median values of multiple PTFs following Dai et al (), but the results are further evaluated using a popular soil data set. The soil heat capacity is calculated as the volumetric‐weighted average of the values from soil solids and moisture content, and the soil thermal conductivity is estimated using the scheme identified by Dai, Wei, et al () (the work is under review; see the preprint version in arXiv), which is demonstrated to have the best performance among several highly recommended schemes for global applications. Since Dai, Wei, et al () have evaluated the scheme for establishing soil thermal parameters, we mainly focus on the estimation and validation of soil hydraulic parameters in this work.…”

“…The soil heat capacity is calculated as the volumetric‐weighted average of the values from soil solids and moisture content, and the soil thermal conductivity is estimated using the scheme identified by Dai, Wei, et al () (the work is under review; see the preprint version in arXiv), which is demonstrated to have the best performance among several highly recommended schemes for global applications. Since Dai, Wei, et al () have evaluated the scheme for establishing soil thermal parameters, we mainly focus on the estimation and validation of soil hydraulic parameters in this work. In the last section, global maps of soil hydraulic and thermal properties and their CVs are produced at the spatial resolution of 30″ × 30″ with six soil layers based on the GSDE and SoilGrids data sets.…”

Thermal conductivity of mineral soils relates linearly to air‐filled porosity

“…and n a Figure 2 shows the comparison between estimated λ from Equation (2) Although the linear λ-n a function is much simpler than the previous λ-θ models, the prediction accuracy is comparable to that of previous models. Thus, the new function can be incorporated into simulation frameworks (e.g., weather forecast and land surface models, Dai et al, 2019) for estimating λ.…”