Session 10C Advances in Large-scale Flood Modeling, Monitoring, Forecasting, Analysis, and Management I

Wednesday, 31 January 2024: 10:45 AM-12:00 PM
339 (The Baltimore Convention Center)
Host: 38th Conference on Hydrology
Cochairs:
Sudershan Gangrade, ORNL, Environmental Sciences Division/Water Resources Science and Engineering, Oak Ridge, TN; Shih-Chieh Kao, Texas A&M University, Civil Engineering, College Station, TX; Mario Morales-Hernández, ORNL, Knoxville, TN; Thomas E. Adams III and Chandana Gangodagamage, NASA Goddard Space Flight Center, Earth System Science Interdisciplinary Center (ESSIC), Greenbelt, MD

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.

Papers:
10:45 AM
10C.1
Advancing Flash Flood Forecasting Capabilities in West Africa with Machine Learning and Satellite Observations
Efthymios Nikolopoulos, Rutgers University, Piscataway, NJ; and A. Ali, W. Amponsah, G. Anagnostopoulos, A. Aravamudan, J. J. Gourley, V. Maggioni, M. Nasibi, V. Robledo, H. Vergara, and X. Zhang

11:00 AM
10C.2
Operational Hydrology with NOAA’s National Water Model: Current Capabilities and Future Enhancements
Brian Cosgrove, NWS Office of Water Prediction, Silver Spring, MD; NWS, Silver Spring, MD; and E. P. Clark, A. Dugger, T. C. Flowers, D. J. Gochis, T. M. Graziano, and F. L. Ogden

11:15 AM
10C.3
11:30 AM
10C.4
A High Resolution Global Pluvial Flood Model for Predicting Physical Risk in a Changing Climate
Elizabeth Perry, Jupiter Intelligence, New York, NY; and C. J. McNicholas, Ph.D.

11:45 AM
10C.5
A Global Flood Inundation Database (GloFID)
Chandana Gangodagamage, OeilSat LLC GSFC/UMD, Hanover, MD; and R. M. Tshimanga, S. Lamont, K. Matta, S. Venukanthan, and S. Mahanama

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