The increasing frequency and magnitude of hydrometeorological extremes are exacerbating the risks of global flood events on an unprecedented scale. Changing human-climate dynamics, in particular, present unique challenges for scientific communities to accurately monitor,  analyze, forecast, predict, and manage large-scale flood events. Accurate and timely prediction of flood hazards is pivotal for decision-makers in developing flood mitigation, climate resilience, and disaster management strategies. Recent advances in science and technology have led to the development of improved monitoring systems and predictive models that can assimilate observational data into modeling frameworks providing significantly improved understanding and characterization of flood risks. The evolution of remote sensing technologies and monitoring networks, in conjunction with human feedback, are advancing the predictive capabilities, but challenges remain for large-scale floods. The session invites contributions including but not limited to, (1) the development of flood-monitoring and prediction tools (integrated atmospheric-hydrologic-hydrodynamic modeling, data assimilation, uncertainty quantification, machine learning), (2) the analysis of floods, and (3) lessons learned from managing floods from scientific and societal perspectives. Papers focusing on large-scale flood modeling efforts as well as continental and global scale hydrologic forecasting systems are of particular interest.

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