Normalized concept for modelling effective soil thermal conductivity from dryness to saturation
Notice bibliographique
Résumé
Abstract Effective soil thermal conductivity ( λ eff ) is a critical parameter for environmental and earth science as well as engineering applications. Models to predict λ eff 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 λ eff . 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 λ eff . 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 ( K e ) 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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».