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A sigmoidal model for predicting soil thermal conductivity-water content function in room temperature.
Sepaskhah, Ali Reza; Mazaheri-Tehrani, Maasumeh.
Affiliation
  • Sepaskhah AR; Irrigation Department, Shiraz University, Shiraz, Islamic Republic of Iran. sepas@shirazu.ac.ir.
  • Mazaheri-Tehrani M; Irrigation Department, Shiraz University, Shiraz, Islamic Republic of Iran.
Sci Rep ; 14(1): 17272, 2024 Jul 27.
Article in En | MEDLINE | ID: mdl-39068193
ABSTRACT
Apparent thermal conductivity of soil (λ) as a function of soil water content (θ), i.e., λ(θ) is needed to determine the heat flow in soil. The function of λ(θ) can be used in heat and water flow models for simplicity. The objective of this study was to develop a sigmoidal model based on logistic equation for entire range of soil water contents and a wide range of soil textures that can be used in simulation of heat and water flow in respected modes. Further, performance of the developed sigmoidal model along with two other models in literature was evaluated. In the proposed sigmoidal model, the constants of this model are estimated based on empirical multivariate equations by using soil sand content and bulk density. The sigmoidal model was validated with good accuracy for a wide range of soil textures, as the relationship between the measured and predicted λ showed slope and intercept values of nearly 1.0 and 0.0, respectively. Comparison of the results obtained by sigmoidal model with those obtained from Johansen and Lu et al. models indicated that, the sigmoidal model was superior to the other two models in prediction of λ for a wide range of soil textures and soil water contents. Furthermore, comparison with a recently proposed model by Xiong et al. indicated that our sigmoidal model is superior. Therefore, our developed sigmoidal model can be used in heat and water flow models to predict the soil temperature and heat flow.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Sci Rep Year: 2024 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Sci Rep Year: 2024 Document type: Article