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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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| Type: | Resource | |
| Storage: | The size of this resource is 309.3 KB | |
| Created: | Jun 17, 2023 at 6:34 a.m. | |
| Last updated: | Sep 27, 2023 at 7:09 p.m. | |
| DOI: | 10.4211/hs.27bad615474940f3b47224fca5334981 | |
| Citation: | See how to cite this resource |
| Sharing Status: | Published |
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| Views: | 186 |
| Downloads: | 2 |
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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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This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
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