Hydrological models represent water movement in natural systems, and they are important for water resource planning and management. But the models depend on reliable input data for weather factors, ...

Hydrologic modelers are increasingly using explainable AI (XAI) to provide additional insight into complex hydrological problems, but a new University of Adelaide study suggests XAI's insights may not ...

Machine learning has revolutionised hydrological modelling by offering data-driven alternatives to traditional process-based approaches. Algorithms such as deep neural networks and ensemble learning ...

Recognizing the importance for adaptation to the climate change impact on water resources, the IAEA has developed guidelines and recommendations on the selection and application of isotope-enabled ...

As of the 2016 SWDM, King County Runoff Time Series (KCRTS) is no longer an approved model. KCRTS may only be used for projects vested to earlier versions; it is ...