Open access
Aug 2026
Groundwater level prediction in a karst aquifer using spatio-temporal graph convolutional networks: a case study of Jinan, China
Workflow of a spatio-temporal graph convolutional network predicting karst groundwater levels, with a Random Forest ranking driving factors. Accurate groundwater level prediction in karst aquifer systems remains challenging due to their complex hydrogeological characteristics, including rapid recharge responses, pre...
Sen Hou, Xue-Rui Xing, Li-Ting Xing et al.
· Journal of Hydroinformatics · 0 citations