H13Q:
Global Floods: Forecasting, Monitoring, Risk Assessment, and Socioeconomic Response I

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Session ID#: 16951

Session Description:
The increase in the frequency of flood events due to acceleration of the global water cycle induces more risks to human settlements, especially those on floodplains, in an era of rapid population growth. Monitoring and forecasting of the occurrence, intensity, and evolution of flood events have been critical for many humanitarian and government agencies in their efforts to prepare, mitigate, and manage responses to disaster to save lives and limit damage. Risk assessments prior to events are also vital for developing short-term and long-term management plans. Remote sensing and modeling are two powerful technologies for providing timely information of hazardous events. Both research areas advance rapidly to provide better understanding of causation and geophysical process of these hazards, while each has its own strengths and weaknesses. We solicit contributions from modeling and remote sensing, socioeconomic sciences, hazard response, and preparedness fields that study flood hazards and risks across spatial scales.
Primary Convener:  Huan Wu, Sun Yat-Sen University, School of Atmospheric Sciences, Guangzhou, China
Conveners:  Dennis P. Lettenmaier, University of California Los Angeles, Department of Geography, Los Angeles, CA, United States, Donglian Sun, George Mason University, Geography And Geoinformation Science, Fairfax, United States and Philip Ward, Free University of Amsterdam, Amsterdam, Netherlands
Chairs:  Huan Wu, Sun Yat-Sen University, School of Atmospheric Sciences, Guangzhou, China, Dennis P. Lettenmaier, University of California Los Angeles, Department of Geography, Los Angeles, CA, United States, Donglian Sun, George Mason University, Geography And Geoinformation Science, Fairfax, United States and Philip Ward, Free University of Amsterdam, Amsterdam, Netherlands
OSPA Liaison:  Huan Wu, Sun Yat-Sen University, School of Atmospheric Sciences, Guangzhou, China

Cross-Listed:
  • NH - Natural Hazards
Index Terms:

1821 Floods [HYDROLOGY]
1840 Hydrometeorology [HYDROLOGY]
1847 Modeling [HYDROLOGY]
1855 Remote sensing [HYDROLOGY]

Abstracts Submitted to this Session:

Flood Risk and Probabilistic Benefit Assessment to Support Management of Flood-Prone Lands: Evidence From Candaba Floodplains, Philippines (162793)
Andrea Mariel Juarez, GRIPS National Graduate Institute for Policy Studies, Tsukuba, Japan, Kelly Maren Kibler, University of Central Florida, Department of Civil, Environmental and Construction Engineering, Orlando, United States, Takahiro Sayama, Disaster Prevention Research Institute, Kyoto University, Kyoto, Japan and Miho Ohara, ICHARM International Centre for Water Hazard And Risk Management, Tsukuba, Japan
A 30m resolution hydrodynamic model of the entire conterminous United States. (Invited) (119369)
Paul D Bates1, Jeffrey C Neal2, Andy Smith3, Christopher Charles Sampson3, Kris Johnson4 and Oliver Wing5, (1)University of Bristol, School of Geographical Sciences, Bristol, United Kingdom, (2)University of Bristol, School of Geographical Sciences, Bristol, BS8, United Kingdom, (3)SSBN Ltd, Bristol, United Kingdom, (4)The Nature Conservancy, Minneapolis, MN, United States, (5)University of Bristol, Bristol, BS8, United Kingdom
Global Flood Monitoring: First Steps Toward Integrating Remote Sensing Information (Invited) (124382)
Robert F Adler, University of Maryland, College Park, MD, United States and Huan Wu, Sun Yat-Sen University, School of Atmospheric Sciences, Guangzhou, China
Calibration and evaluation of the global flood forecasting system using daily streamflow observations (164914)
Feyera A Hirpa1,2, Peter Salamon3, Hylke Beck4, Valerio Lorini3, Francesco Dottori3 and Jutta Thielen-del Pozo5, (1)Joint Research Center Ispra, Disaster Risk Management Unit, Ispra, Italy, (2)One Concern, Menlo Park, United States, (3)European Commission Joint Research Centre, Ispra, Italy, (4)Princeton University, Civil and Environmental Engineering, Princeton, NJ, United States, (5)European Commission, Joint Research Centre, Ispra, Italy
NASA’s Support to Flood Response (Invited) (181819)
David S Green, NASA Headquarters, Application Science - Wildfires, Washington, United States, John J Murray, NASA Langley Research Center, Hampton, VA, United States and Tim Stough, NASA Jet Propulsion Laboratory, Pasadena, CA, United States
Developing a Global Database of Historic Flood Events to Support Machine Learning Flood Prediction in Google Earth Engine (Invited) (136284)
Beth Tellman, University of Arizona, School of Geography, Development and Environment, Tucson, United States, Jonathan Sullivan, University of Michigan, Sustainability, Ann Arbor, MI, United States, Prof. Albert Kettner, University of Colorado at Boulder, CSDMS/INSTAAR, Boulder, CO, United States, G Robert Brakenridge, University of Colorado at Boulder, Boulder, CO, United States, Daniel A Slayback, Science Systems and Applications, Inc., Lanham, MD, United States, Catherine Kuhn, University of Washington Seattle Campus, Environmental Sciences and Forestry, Seattle, WA, United States and Colin Doyle, The University of Texas at Austin, Department of Geography and the Environment, Austin, United States
Mapping Coastal Floods due to Hurricanes from Optical and Passive Microwave Observations (188319)
Donglian Sun, George Mason University Fairfax, Fairfax, VA, United States
An experimental system for flood risk forecasting at global scale (171454)
Francesco Dottori1, Lorenzo Alfieri2, Milan Kalas1, Valerio Lorini1, Alessandra Bianchi1, Feyera A Hirpa1, Luc Feyen1 and Peter Salamon1, (1)European Commission Joint Research Centre, Ispra, Italy, (2)European Commission Joint Research Centre, Ispra Vey, Italy

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