Data and code used in the article "A deep learning method for predicting soil moisture in unsaturated areas based on physical constraints"

Data and code used in the article "A deep learning method for predicting soil moisture in unsaturated areas based on physical constraints", specifically included are water content data from 55 in situ observations for the years 2018-2020 (observation frequency of 5min or 10min), and example code for implementing LSTM and PIDL using python (mainly the tensorflow library).These data can help the reader to better understand and replicate our research. All the data and code has been uploaded. The paper has been published in Water Resources Research, and the citation is: Wang, Y., Wang, W., Ma, Z., Zhao, M., Li, W., Hou, X., et al. (2023). A deep learning approach based on physical constraints for predicting soil moisture in unsaturated zones. Water Resources Research,59, e2023WR035194. https://doi.org/10.1029/2023WR035194