Zihe Xu

Graph Learning for River Water Quality Forecasting: Advances in Hydrological Connectivity Representation, Dynamic Topology, and Physics-Informed Modeling

Graph neural networks are increasingly used for river water-quality forecasting because they can represent interactions among monitoring locations that conventional site-wise time-series models cannot capture. However, the usefulness of graph learning depends strongly on whether...