Reconstructing GRACE-like TWS anomalies for the Canadian landmass using deep learning and land surface model

Terrestrial water storage (TWS) is an essential part of the global water cycle. Long-term information of observed and modeled TWS is fundamental to analyze water resources, meteorological extreme events (e.g., droughts and floods), and the climate change impacts. Over the past several decades, hydrologists have been applying physically-based hydrological model (GHM) and land surface model (LSM) to simulate TWS and its components (e.g., …