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Python code for: Excluding quartz content from the estimation of saturated soil thermal conductivity: combined use of differential effective medium theory and geometric mean method


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Created: Jun 17, 2023 at 6:34 a.m.
Last updated: Sep 27, 2023 at 7:09 p.m. (Metadata update)
Published date: Sep 27, 2023 at 7:09 p.m.
DOI: 10.4211/hs.27bad615474940f3b47224fca5334981
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Sharing Status: Published
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Abstract

This dataset accompanies the paper "Excluding Quartz Content from the Estimation of Saturated Soil Thermal Conductivity: Combined use of Differential Effective Medium Theory and Geometric Mean Method," published in Agricultural & Forestry Meteorology. It contains the Python code that implements the DEM-GMM methodology developed by Fu et al. (2023). The code allows for the computation of saturated thermal conductivity in soils based on variables such as sand content, porosity, and temperature. The dataset offers flexibility in data input, permitting manual entry or data importation from an Excel spreadsheet. Prior to executing the Python code, it is highly recommended to read the accompanying document titled "ReadMeFirst" for essential guidelines. For comprehensive theoretical background and definitions used within the code, we refer users to our aforementioned publication.

Fu, Y., Jones, S., Horton, R., Heitman, J., 2023. Excluding quartz content from the estimation of saturated soil thermal conductivity: combined use of differential effective medium theory and geometric mean method. Agricultural and Forest Meterology (accepted).

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How to Cite

Fu, Y. (2023). Python code for: Excluding quartz content from the estimation of saturated soil thermal conductivity: combined use of differential effective medium theory and geometric mean method, HydroShare, https://doi.org/10.4211/hs.27bad615474940f3b47224fca5334981

This resource is shared under the Creative Commons Attribution CC BY.

http://creativecommons.org/licenses/by/4.0/
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