Influence of Different Methods to Estimate the Soil Thermal Properties from Experimental Dataset

Leugim Corteze Romio (), Tamires Zimmer, Tiago Bremm, Lidiane Buligon, Dirceu Luis Herdies and Débora Regina Roberti
Additional contact information
Leugim Corteze Romio: Caçapava do Sul Campus, Federal University of Pampa, Caçapava do Sul 96570-000, RS, Brazil
Tamires Zimmer: Physics Department/Micrometeorology Laboratory, Federal University of Santa Maria, Santa Maria 97105-900, RS, Brazil
Tiago Bremm: Physics Department/Micrometeorology Laboratory, Federal University of Santa Maria, Santa Maria 97105-900, RS, Brazil
Lidiane Buligon: Physics Department/Micrometeorology Laboratory, Federal University of Santa Maria, Santa Maria 97105-900, RS, Brazil
Dirceu Luis Herdies: Center for Weather Forecasting and Climate Studies (CPTEC), National Institute for Space Research (INPE), São José dos Campos 12630-000, SP, Brazil
Débora Regina Roberti: Physics Department/Micrometeorology Laboratory, Federal University of Santa Maria, Santa Maria 97105-900, RS, Brazil

Land, 2022, vol. 11, issue 11, 1-17

Abstract: Knowledge of soil thermal properties (diffusivity ( k ) and conductivity ( λ )) is important to understand the soil–plant–atmosphere interaction related to the physical and biological processes associated with energy transfer and greenhouse gas exchanges. The incorporation of all the physical processes that occur in the energy transfer in the soil is a challenge in order to correctly estimate soil thermal properties. In this work, experimental measurements of soil temperature and soil heat flux obtained in a silty clay loam soil covered by native grassland located in the Brazilian Pampa biome were used to estimate soil thermal properties using different methods including the influence of the soil water content at different soil depths in heat transfer processes. The λ was estimated using the numerical solution of the Fourier equation by the Gradient and Modified Gradient methods. For the surface layer, the results for both models show large variability in daily values, but with similar values for the annual mean. For λ at different soil depths, both models showed an increase of approximately 50% in the λ value in the deeper layers compared to the surface layer, increasing with depth in this soil type. The k was estimated using analytical and numerical methods. The analytical methods showed a higher variability and overestimated the values of the numerical models from 15% to 35%. The numerical models included a term related to the soil water content. However, the results showed a decrease in the mean value of k by only 2%. The relationship between thermal properties and soil water content was verified using different empirical models. The best results for thermal conductivity were obtained using water content in the surface layer ( R 2 > 0.5). The cubic model presented the best results for estimating the thermal diffusivity ( R 2 = 0.70). The analyses carried out provide knowledge for when estimating soil thermal properties using different methods and an experimental dataset of soil temperature, heat flux and water content, at different soil depths, for a representative soil type of the Brazilian Pampa biome.

Keywords: soil thermal conductivity; soil thermal diffusivity; soil water content; numerical modeling; Pampa biome (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/2073-445X/11/11/1960/pdf (application/pdf)
https://www.mdpi.com/2073-445X/11/11/1960/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jlands:v:11:y:2022:i:11:p:1960-:d:961311

Access Statistics for this article

Land is currently edited by Ms. Carol Ma

More articles in Land from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().