Primary Convener:
Sudershan Gangrade, Oak Ridge National Laboratory

Convener:
Ganesh Ghimire, Oak Ridge National Laboratory
Shih-Chieh Kao, Oak Ridge National Laboratory
Mario Morales-Hernandez, I3A-University of Zaragoza

Chair:
Sudershan Gangrade, Oak Ridge National Laboratory
Ganesh Ghimire, University of Iowa
Shih-Chieh Kao, Oak Ridge National Laboratory
Mario Morales-Hernandez, I3A-University of Zaragoza

As extreme flood events get more intense, frequent, and prevalent, accurate and timely flood risk assessments become critical for emergency preparedness, developing mitigation strategies, and resilience planning. Recent advancements in coupled hydrologic, hydraulic, and machine learning models have significantly enhanced the characterization and prediction of flood risks. This session invites presentations demonstrating innovative large-scale, high-resolution modeling tools, 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, and hydraulic models for enhanced flood risk assessments 2) Prediction, projection, and characterization of extreme hydrologic events, including probable maximum precipitation and flood 3) Real-time streamflow or flood forecasting and validation 4) Computational advances in high-resolution hydrologic or inundation modeling 5) Machine learning, surrogate modeling, and hybrid data-model approaches improving predictions 6) Uncertainty quantification techniques leveraging multi-forcing, model, and parameter ensemble 7) Frameworks for integrated flood risk management

Index Terms
1817 Extreme events
1821 Floods
1856 River channels
1860 Streamflow

Cross-Listed:
NH - Natural Hazards

Neighborhoods:
3. Earth Covering