Description:

This session highlights advances in the development and applications of AI/ML in hydrological, hydrometeorological, and hydroclimatological modeling and predictions across a wide range of timescales (hours-to-decades) and space scales (local-to-global). This includes theoretical developments in physics-informed machine learning, knowledge guided deep learning, hydroinformatics, and their applications in areas related to hydrology and water resources.  We also encourage papers on the application of AI/ML in improving process-based hydrological and land surface models, uncertainty quantification, and hydrologically relevant climate downscaling. Papers describing current challenges for model developers and users are also welcome, with a special interest in highlighting needs and opportunities for cross-disciplinary collaboration to address national and societal challenges in a changing climate.