My research group develops and applies systems methods to merge multi-scale field measurements and satellite-based Earth Observation Systems with hydrological and hydrodynamic models. We utilize optimization algorithms, diagnostic model evaluation/parameter estimation techniques and Machine Learning/Artificial Intelligence to advance hydrological process understanding and improve accuracy & reliability of catastrophe flood models. We specifically focus on effective and efficient workflows to help manage risk associated with hydrological extremes (floods & droughts) that are becoming more devastating due to climate change and urbanization. We aim to formulate improved methods to quantify uncertainty in hydrological predictions and communicate actionable hydrological insights to practitioners and decision makers  for better planning and adaptation to future hydrologic extremes.