Data and code used in the article "Integrating multiphysics processes with deep learning for the Prediction of coupled water-vapor-heat water fluxes in unsaturated zone"

《Integrating multiphysics processes with deep learning for the Prediction of coupled water-vapor-heat water fluxes in unsaturated zone》 (the paper has been submitted to Water Resources Research). The data and code used in the paper, specifically, the water content data and temperature data from in-situ observations from July 1, 2020 to August 29, 2020 (with a frequency of observations of 5 min), and the sample code for implementing cpinn using python (mainly the tensorflow library). These data can help readers better understand and replicate our study. All data and code have been uploaded.

The paper has been submitted to Water Resources Research, if the paper is accepted for publication, all data will be made freely available.

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