Normalized concept for modelling effective soil thermal conductivity from dryness to saturation

Hailong He, Kosuke Noborio, Øistein Johansen, Miles F. Dyck, Jialong Lv

Research output: Contribution to journalReview article

1 Citation (Scopus)

Abstract

Effective soil thermal conductivity (λeff) is a critical parameter for environmental and earth science as well as engineering applications. Models to predict λeff are required in diverse global and community land surface schemes as well as climate models to investigate coupled water and heat transport in soils and heat exchange at the earth surface. Among the many soil thermal conductivity models, models based on the normalized concept are most often developed and utilized for estimating λeff. However, at present no systematic study has been performed to investigate the origin and evolution of the normalized thermal conductivity models, nor to evaluate their performance with large datasets. The objectives of this study were to: (a) review the development and evolution of the normalized thermal conductivity models, and (b) assess their performance with datasets consisting of soils with a full range of water saturation and a wide range of soil textures and bulk densities. A total of 38 normalized thermal conductivity models were critically reviewed and their relationships were clearly outlined. Their performance was evaluated by five categories according to model characteristics with a compiled dataset consisting of 71 soils and 669 tests collected from nine studies. Our analysis demonstrated key roles of the quartz content, solid thermal conductivity and choice of the Kersten functions in the model applicability and accuracy of estimating λeff. The results showed that the Y2018, CK2005, CK2006, J1975, L2007 and T2009 models have the best performance among the models without fitting parameters, but further improvements are required to apply them universally. Although the models of H2017, LD2015, M2006 and K2007 are the best performing models with fitting parameters, approaches to calculate these parameters are required so they can be easily applied. Future studies on parametrization of currently well-performing models for wider and more accurate application, development of a soil thermal conductivity database for model evaluation and calibration purposes, and connecting soil thermal conductivity models to hydraulic properties are recommended. Highlights: The history and evolution of normalized thermal conductivity models and the potential Kersten (Ke) functions are collated and synthesized. A total of 38 models were reviewed and their performance was evaluated with a total of 71 soils and 669 tests from nine studies. The Y2018, CK2005, CK2006, J1975, L2007 and T2009 are the best ranked models without fitting parameters. The models of H2017, LD2015, M2006 and K2007 are the best ranked models with fitting parameter.

Original languageEnglish
Pages (from-to)27-43
Number of pages17
JournalEuropean Journal of Soil Science
Volume71
Issue number1
DOIs
Publication statusPublished - 1 Jan 2020

Fingerprint

thermal conductivity
saturation
modeling
soil

Keywords

  • degree of saturation
  • effective soil thermal conductivity
  • thermal conductivity empirical model
  • thermal conductivity model evaluation
  • water content

Cite this

He, Hailong ; Noborio, Kosuke ; Johansen, Øistein ; Dyck, Miles F. ; Lv, Jialong. / Normalized concept for modelling effective soil thermal conductivity from dryness to saturation. In: European Journal of Soil Science. 2020 ; Vol. 71, No. 1. pp. 27-43.
@article{65581522ab0d4168b0455348b82e331a,
title = "Normalized concept for modelling effective soil thermal conductivity from dryness to saturation",
abstract = "Effective soil thermal conductivity (λeff) is a critical parameter for environmental and earth science as well as engineering applications. Models to predict λeff are required in diverse global and community land surface schemes as well as climate models to investigate coupled water and heat transport in soils and heat exchange at the earth surface. Among the many soil thermal conductivity models, models based on the normalized concept are most often developed and utilized for estimating λeff. However, at present no systematic study has been performed to investigate the origin and evolution of the normalized thermal conductivity models, nor to evaluate their performance with large datasets. The objectives of this study were to: (a) review the development and evolution of the normalized thermal conductivity models, and (b) assess their performance with datasets consisting of soils with a full range of water saturation and a wide range of soil textures and bulk densities. A total of 38 normalized thermal conductivity models were critically reviewed and their relationships were clearly outlined. Their performance was evaluated by five categories according to model characteristics with a compiled dataset consisting of 71 soils and 669 tests collected from nine studies. Our analysis demonstrated key roles of the quartz content, solid thermal conductivity and choice of the Kersten functions in the model applicability and accuracy of estimating λeff. The results showed that the Y2018, CK2005, CK2006, J1975, L2007 and T2009 models have the best performance among the models without fitting parameters, but further improvements are required to apply them universally. Although the models of H2017, LD2015, M2006 and K2007 are the best performing models with fitting parameters, approaches to calculate these parameters are required so they can be easily applied. Future studies on parametrization of currently well-performing models for wider and more accurate application, development of a soil thermal conductivity database for model evaluation and calibration purposes, and connecting soil thermal conductivity models to hydraulic properties are recommended. Highlights: The history and evolution of normalized thermal conductivity models and the potential Kersten (Ke) functions are collated and synthesized. A total of 38 models were reviewed and their performance was evaluated with a total of 71 soils and 669 tests from nine studies. The Y2018, CK2005, CK2006, J1975, L2007 and T2009 are the best ranked models without fitting parameters. The models of H2017, LD2015, M2006 and K2007 are the best ranked models with fitting parameter.",
keywords = "degree of saturation, effective soil thermal conductivity, thermal conductivity empirical model, thermal conductivity model evaluation, water content",
author = "Hailong He and Kosuke Noborio and {\O}istein Johansen and Dyck, {Miles F.} and Jialong Lv",
year = "2020",
month = "1",
day = "1",
doi = "10.1111/ejss.12820",
language = "English",
volume = "71",
pages = "27--43",
journal = "Journal of Soil Sciences",
issn = "0022-4588",
publisher = "Wiley-Blackwell Publishing Ltd",
number = "1",

}

Normalized concept for modelling effective soil thermal conductivity from dryness to saturation. / He, Hailong; Noborio, Kosuke; Johansen, Øistein; Dyck, Miles F.; Lv, Jialong.

In: European Journal of Soil Science, Vol. 71, No. 1, 01.01.2020, p. 27-43.

Research output: Contribution to journalReview article

TY - JOUR

T1 - Normalized concept for modelling effective soil thermal conductivity from dryness to saturation

AU - He, Hailong

AU - Noborio, Kosuke

AU - Johansen, Øistein

AU - Dyck, Miles F.

AU - Lv, Jialong

PY - 2020/1/1

Y1 - 2020/1/1

N2 - Effective soil thermal conductivity (λeff) is a critical parameter for environmental and earth science as well as engineering applications. Models to predict λeff are required in diverse global and community land surface schemes as well as climate models to investigate coupled water and heat transport in soils and heat exchange at the earth surface. Among the many soil thermal conductivity models, models based on the normalized concept are most often developed and utilized for estimating λeff. However, at present no systematic study has been performed to investigate the origin and evolution of the normalized thermal conductivity models, nor to evaluate their performance with large datasets. The objectives of this study were to: (a) review the development and evolution of the normalized thermal conductivity models, and (b) assess their performance with datasets consisting of soils with a full range of water saturation and a wide range of soil textures and bulk densities. A total of 38 normalized thermal conductivity models were critically reviewed and their relationships were clearly outlined. Their performance was evaluated by five categories according to model characteristics with a compiled dataset consisting of 71 soils and 669 tests collected from nine studies. Our analysis demonstrated key roles of the quartz content, solid thermal conductivity and choice of the Kersten functions in the model applicability and accuracy of estimating λeff. The results showed that the Y2018, CK2005, CK2006, J1975, L2007 and T2009 models have the best performance among the models without fitting parameters, but further improvements are required to apply them universally. Although the models of H2017, LD2015, M2006 and K2007 are the best performing models with fitting parameters, approaches to calculate these parameters are required so they can be easily applied. Future studies on parametrization of currently well-performing models for wider and more accurate application, development of a soil thermal conductivity database for model evaluation and calibration purposes, and connecting soil thermal conductivity models to hydraulic properties are recommended. Highlights: The history and evolution of normalized thermal conductivity models and the potential Kersten (Ke) functions are collated and synthesized. A total of 38 models were reviewed and their performance was evaluated with a total of 71 soils and 669 tests from nine studies. The Y2018, CK2005, CK2006, J1975, L2007 and T2009 are the best ranked models without fitting parameters. The models of H2017, LD2015, M2006 and K2007 are the best ranked models with fitting parameter.

AB - Effective soil thermal conductivity (λeff) is a critical parameter for environmental and earth science as well as engineering applications. Models to predict λeff are required in diverse global and community land surface schemes as well as climate models to investigate coupled water and heat transport in soils and heat exchange at the earth surface. Among the many soil thermal conductivity models, models based on the normalized concept are most often developed and utilized for estimating λeff. However, at present no systematic study has been performed to investigate the origin and evolution of the normalized thermal conductivity models, nor to evaluate their performance with large datasets. The objectives of this study were to: (a) review the development and evolution of the normalized thermal conductivity models, and (b) assess their performance with datasets consisting of soils with a full range of water saturation and a wide range of soil textures and bulk densities. A total of 38 normalized thermal conductivity models were critically reviewed and their relationships were clearly outlined. Their performance was evaluated by five categories according to model characteristics with a compiled dataset consisting of 71 soils and 669 tests collected from nine studies. Our analysis demonstrated key roles of the quartz content, solid thermal conductivity and choice of the Kersten functions in the model applicability and accuracy of estimating λeff. The results showed that the Y2018, CK2005, CK2006, J1975, L2007 and T2009 models have the best performance among the models without fitting parameters, but further improvements are required to apply them universally. Although the models of H2017, LD2015, M2006 and K2007 are the best performing models with fitting parameters, approaches to calculate these parameters are required so they can be easily applied. Future studies on parametrization of currently well-performing models for wider and more accurate application, development of a soil thermal conductivity database for model evaluation and calibration purposes, and connecting soil thermal conductivity models to hydraulic properties are recommended. Highlights: The history and evolution of normalized thermal conductivity models and the potential Kersten (Ke) functions are collated and synthesized. A total of 38 models were reviewed and their performance was evaluated with a total of 71 soils and 669 tests from nine studies. The Y2018, CK2005, CK2006, J1975, L2007 and T2009 are the best ranked models without fitting parameters. The models of H2017, LD2015, M2006 and K2007 are the best ranked models with fitting parameter.

KW - degree of saturation

KW - effective soil thermal conductivity

KW - thermal conductivity empirical model

KW - thermal conductivity model evaluation

KW - water content

UR - http://www.scopus.com/inward/record.url?scp=85066900806&partnerID=8YFLogxK

U2 - 10.1111/ejss.12820

DO - 10.1111/ejss.12820

M3 - Review article

AN - SCOPUS:85066900806

VL - 71

SP - 27

EP - 43

JO - Journal of Soil Sciences

JF - Journal of Soil Sciences

SN - 0022-4588

IS - 1

ER -