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 PCDL using python (mainly the tensorflow library).These data can help the reader to better understand and replicate our research

本数据集对应论文《基于物理约束的非饱和区土壤含水率深度学习预测方法》（A deep learning method for predicting soil moisture in unsaturated areas based on physical constraints）所使用的数据与代码，具体包含2018-2020年55个原位观测点的含水率数据（观测频率为5分钟或10分钟），以及基于Python（主要依托TensorFlow库）实现长短期记忆网络（LSTM）与物理约束深度学习（PCDL）的示例代码。本数据集可帮助读者更好地理解并复现本项研究。