Primary Convener:
Amar Tiwari, Michigan State University

Convener:
Nanditha J S, Princeton University
Anukesh Krishnankutty Ambika, Oak Ridge National Laboratory
Saran Aadhar, Indian Institute of Technology Jodhpur
Alka Tiwari, University of Texas at Austin
Aparimita Priyadarshini Naik, Indian Institute of Technology Guwahati
Amrutha Suresh, University of Padua
Sreeja Pekkat, Indian Institute of Technology Guwahati
Sreedeep Sekharan, Indian Institute of Technology Guwahati

Early Career Convener:
Amrutha Suresh, University of Padua

Chair:
Nanditha J S, Princeton University
Anukesh Krishnankutty Ambika, Oak Ridge National Laboratory
Alka Tiwari, University of Texas at Austin
Aparimita Priyadarshini Naik, Indian Institute of Technology Guwahati

Floods are among the most devastating natural hazards, driven by complex and interrelated physical processes. These processes vary across catchments and seasons, making it critical to understand the unique drivers of flood events, including extreme rainfall, land use change, river dynamics, atmospheric conditions such as hurricanes, and human interventions. As natural variability reshapes flood behavior, advancing catchment-specific knowledge is essential for improving prediction and preparedness, including in under-resourced regions. This session invites contributions that enhance understanding of the physical processes behind flooding and show how improved process-scale insights can strengthen flood forecasting, impact assessment, and risk management. We welcome contributions in areas including, but not limited to: ● Advancements in understanding flood generation processes ● Incorporating physical knowledge into improving flood forecasting ● Physics-informed statistical or machine learning models. ● Studies on riverine, flash, coastal, urban, and hurricane-induced floods ● Innovative approaches for flood modeling in data-limited environments

Index Terms
1817 Extreme events
1821 Floods
1834 Human impacts
1838 Infiltration

Suggested Itineraries:
Disasters‚ Calamities and Extreme Events
National Climate Assessment
Climate Change and Global Policy
Science Communications
Machine Learning and AI
Community and People-Powered Science
Open Science and Open Data
Global Impacts‚ Solutions‚ & Policies

Cross-Listed:
NS - Near Surface Geophysics

Neighborhoods:
3. Earth Covering