As extreme flood events become more intense, frequent, and widespread, accurate and timely flood risk assessments become critical for emergency preparedness, developing mitigation strategies, and resilience planning. Recent advancements in coupled hydrologic, hydraulic, and AI predictive models have significantly enhanced the characterization and prediction of flood risks. This session invites presentations demonstrating innovative large-scale, high-resolution modeling tools, datasets, and capabilities for analyzing extreme hydrologic events and their impacts. We welcome studies focusing on (but not limited to)

1) advances in coupled atmospheric-hydrologic-hydraulic models for enhanced flood risk assessments

2) prediction, projection, and characterization of extreme hydrologic events, including probable maximum precipitation and floods

3) computational advances for achieving real-time streamflow or flood forecasting

4) AI and agent-based modeling approaches for flood prediction and decision support

5) remote sensing data and model fusion

6) uncertainty quantification techniques leveraging multi-forcing, model, and parameter ensembles

7) integrated frameworks for flood risk management

• GC - Global Environmental Change
• NH - Natural Hazards