H066
Global Floods: Forecasting, Monitoring, Risk Assessment, and Socioeconomic Response

Session ID#: 83648

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.

 

We hope this session could also aim to contribute to the aims of the Global Flood Partnership (GFP), i.e. to foster global flood forecasting, monitoring and impact assessment to strengthen preparedness and response and to reduce global flood disaster losses. We solicit contributions from modeling and remote sensing, socioeconomic sciences, hazard response, and preparedness fields that study flood hazards and risks across spatial scales.

Index Terms:

1821 Floods [HYDROLOGY]
1833 Hydroclimatology [HYDROLOGY]
1840 Hydrometeorology [HYDROLOGY]
1855 Remote sensing [HYDROLOGY]

Primary Convener:  Huan Wu, Sun Yat-Sen University, School of Atmospheric Sciences, Guangzhou, China
Conveners:  Philip Ward, IVM - VU University Amsterdam, Amsterdam, Netherlands, Donglian Sun, George Mason University Fairfax, Fairfax, VA, United States and Dennis P Lettenmaier, UCLA, Department of Geography, Los Angeles, CA, United States
Primary Liaison:  Huan Wu, Sun Yat-Sen University, Guangzhou, China
 
Analysis of NFIP claims reveals previously unexplored relationships between flood depth and building damage (501658)
Oliver Wing1,2, Paul D Bates1,2, Nicholas Pinter3, Christopher Sampson2 and Andy Smith2, (1)University of Bristol, School of Geographical Sciences, Bristol, BS8, United Kingdom, (2)Fathom, Bristol, United Kingdom, (3)University of California Davis, Davis, CA, United States
 
The seasonality of extreme floods in the conterminous United States (502862)
Mathias J Collins, NOAA Fisheries Greater Atlantic Region - Gloucester, Gloucester, MA, United States, Stacey Archfield, USGS, Virginia, United States and Glenn A Hodgkins, US Geological Survey, Augusta, ME, United States
 
Real Time Data Acquisition System for Flood Forecasting Using telemetry system (509918)
Sanjaya Gurung, Real Time Solutions Pvt. Ltd., Lalitpur, Nepal
 
Estimation of Crop Loss Due to Flood Inundation Using Remote Sensing Images (510662)
Rehenuma Lazin, Xinyi Shen and Emmanouil N Anagnostou, University of Connecticut, Civil and Environmental Engineering, Storrs, CT, United States
 
Causative attribution of floods using an interpretable data-driven rainfall-runoff model (511943)
Wencong Yang and Hanbo Yang, Tsinghua University, State Key Laboratory of Hydroscience and Engineering, Department of Hydraulic Engineering, Beijing, China
 
River size representation in global flood models: a geospatial investigation. (515367)
Mark Bernhofen1, Mark Trigg2 and Sleigh Andy2, (1)University of Leeds, Leeds, LS2, United Kingdom, (2)University of Leeds, Leeds, United Kingdom
 
Contrasting trends between extreme precipitation and floods in Mediterranean basins (515619)
Tramblay Yves Y1, Louise Mimeau2, Luc Neppel2, Freddy Vinet3 and Eric Sauquet4, (1)HydroSciences Montpellier, Montpellier Cedex 05, France, (2)HydroSciences Montpellier, Montpellier, France, (3)GRED, Montpellier, France, (4)Irstea, UR RiverLy, Lyon-Villeurbanne, France
 
Toward real time forecasting rainfall-related incidents on a railway network in France (520635)
Pierre Javelle1, Reyhaneh S. Hashemi1, Ludovic Oudin2, Didier Organde3, Bahar Salavati4 and François Chirouze4, (1)Irstea, Aix-en-Provence, France, (2)Sorbonne University, UMR CNRS 7619 METIS, Paris, France, (3)HYDRIS Hydrologie, Montferrier-sur-Lez, France, (4)SNCF Group, Paris, France
 
Characterizing the urban waterlogging at multiple scales in the metropolitan area of Guangzhou (528114)
Qifei Zhang1, Zhifeng Wu2 and Paolo Tarolli1, (1)University of Padova, Department of Land, Environment, Agriculture and Forestry, Padova, Italy, (2)Guangzhou University, School of Geographical Sciences, Guangzhou, China
 
Optimizing Targeted SAR Acquisitions for Flood Extent Assimilation to Improve Inundation Forecasts (528367)
Antara Dasgupta1, Renaud Hostache2, Raaj Ramsankaran3, Guy Schumann4, Stefania Grimaldi5, Valentijn R N Pauwels6 and Jeffrey P Walker6, (1)IITB-Monash Research Academy, Powai, India, (2)Luxembourg Institute of Science and Technology, Environmental Research and Innovation, Belvaux, Luxembourg, (3)Indian Institute of Technology Bombay, Civil Engineering, Mumbai, India, (4)Remote Sensing Solutions, Inc., Pasadena, CA, United States, (5)Monash University, Clayton, Australia, (6)Monash University, Melbourne, Australia
 
Where do we construct levees?: The automatic extraction of physical levee parameters in contiguous U.S. for global river models (529043)
Yoshiaki Tanaka, The University of Tokyo, Civil Engineering, Bunkyo-KU, Japan and Dai Yamazaki, The University of Tokyo, Institute of Industrial Sciences, Tokyo, Japan
 
A Multi-Sourced Flood Inventory in Contiguous United States During TRMM Era (529094)
Zhijun Huang, Huan Wu, Xiaomeng Li, Nergui Nanding and Zequn Huang, Sun Yat-Sen University, School of Atmospheric Sciences, Guangzhou, China
 
Evaluation of the subseasonal forecast skill of AR-related flooding along the coastal Western U.S. (530449)
Qian Cao, University of California Los Angeles, Los Angeles, CA, United States, Michael J Deflorio, Scripps Institution of Oceanography, Center for Western Weather and Water Extremes (CW3E), La Jolla, CA, United States, F Martin Ralph, Scripps Institution of Oceanography, UC San Diego, Center for Western Weather and Water Extremes, La Jolla, CA, United States and Dennis P Lettenmaier, UCLA, Department of Geography, Los Angeles, CA, United States
 
Global patterns of flood change: an observation-based analysis of the changed magnitude, frequency and drivers of extreme floods (538410)
Shulei Zhang, Beijing Normal University, Beijing, China, Yuting Yang, Tsinghua University, State Key Laboratory of Hydro-Science and Engineering, Department of Hydraulic Engineering, Beijing, China and Xiaoyan Li, Beijing Normal University, Faculty of Geographical Science, Beijing, China
 
The Impact of Dams on Design Floods in the Conterminous US (540887)
Gang Zhao, University of Bristol, Bristol, BS8, United Kingdom, Paul D Bates, University of Bristol, School of Geographical Sciences, Bristol, BS8, United Kingdom and Jeffrey C Neal, University of Bristol, School of Geographical Sciences, Bristol, United Kingdom
 
Potential of the new levee-failure LISFLOOD-FP sub-routine for large scale flood hazard mapping (544686)
Iuliia Shustikova1, Alessio Domeneghetti1, Jeffrey C Neal2, Paul D Bates3, Sergiy Vorogushyn4 and Attilio Castellarin1, (1)University of Bologna, Bologna, Italy, (2)University of Bristol, School of Geographical Sciences, Bristol, United Kingdom, (3)University of Bristol, School of Geographical Sciences, Bristol, BS8, United Kingdom, (4)Helmholtz Centre Potsdam GFZ German Research Centre for Geosciences, Potsdam, Germany
 
Improving Floodplain Topography Using Flood Models and Remote Sensing: A Case Study in The Logone Floodplain (547137)
Apoorva R Shastry, The Ohio State University, School of Earth Sciences and Byrd Polar and Climate Research Center, Columbus, OH, United States and Michael T Durand, The Ohio State University, School of Earth Science and Byrd Polar and Climate Research Center, Columbus, OH, United States
 
Changes to the Exposure of California’s Levee-Protected Critical Infrastructure to Flooding Hazard in a Warming Climate (562041)
Iman Mallakpour1, Amir AghaKouchak2, Mojtaba Sadegh3 and Aneseh Alborzi1, (1)University of California Irvine, Irvine, CA, United States, (2)University of California, Irvine, Civil and Environmental Engineering, Irvine, CA, United States, (3)Boise State University, Boise, ID, United States
 
Global characterization of fluvial floods through long-term high-resolution modeling (563028)
Yuan Yang1, Peirong Lin2, Hylke Beck3, Hui Lu4, Kun Yang5, Dai Yamazaki6, Yang Hong1, Eric F Wood3 and Ming Pan3, (1)Tsinghua University, Department of Hydraulic Engineering, Beijing, China, (2)Princeton University, Civil & Environmental Engineering, Princeton, NJ, United States, (3)Princeton University, Civil and Environmental Engineering, Princeton, NJ, United States, (4)Tsinghua University, Department of Earth System Science, Beijing, China, (5)Center for Earth System Science, Tsinghua University, Beijing, China, (6)The University of Tokyo, Institute of Industrial Sciences, Tokyo, Japan
 
Integrating satellite optical images into operational global flood forecasting systems for better predictions (569272)
Yuta Ishitsuka, University of Massachusetts Amherst, Amherst, MA, United States, Colin J Gleason, University of Massachusetts, Amherst, MA, United States, Dai Yamazaki, The University of Tokyo, Institute of Industrial Sciences, Tokyo, Japan and Peirong Lin, University of Texas, Austin, TX, United States
 
Normalized Difference Scattering Index For Flood Mapping (570177)
Noel Ivan Ulloa, Center for Space and Remote Sensing Research, Jhongli, Taiwan, Shou-hao Chiang, NCU National Central University of Taiwan, Center for Space and Remote Sensing Research, Jhongli, Taiwan and Sang-Ho Yun, Jet Propulsion Laboratory, Pasadena, CA, United States
 
Development and operation of near-realtime inundation analysis system in a data scarce region: A case in Myanmar (577646)
Akiyuki Kawasaki1, Ralph Allen E. Acierto2, Seemanta Sharma Bhagabati3, Masaki Yasukawa4, Win Win Zin5, Khin Than Yu5 and Masaru Kitsuregawa6, (1)University of Tokyo, Department of Civil Engineering, Tokyo, Japan, (2)University of Tokyo, Bunkyo-ku, Japan, (3)The University of Tokyo, Department of Civil Engineering, Tokyo, Japan, (4)The University of Tokyo, Institute of Industrial Science, Tokyo, Japan, (5)Yangon Technological University, Yangon, Myanmar, (6)University of Tokyo, Institute of Industrial Science, Tokyo, Japan
 
Flood Mapping Using Integration of Google Earth Engine and Statistical Thresholding – A Case Study of Bihar Floods in India (582069)
Sachchidanand Singh, Indian Institute of Technology Roorkee, Water Resources Development & Management, Roorkee, India and Mitthan Lal Kansal, Indian Institute of Technology, Roorkee, Department of Water Resource Development & Management, Roorkee, India
 
A Hierarchical Bayesian approach to flood loss modelling using synthetic functions (585980)
Nivedita Sairam, Potsdam, Germany, Kai Schroeter, GFZ German Research Centre for Geosciences, Section Hydrology, Potsdam, Germany and Heidi Kreibich, GFZ German Research Centre for Geosciences, Section 4.4 Hydrology, Potsdam, Germany
 
Characteristics and simulation of flood in Huaihe River Basin, China (586841)
Yashan Cheng1,2, Zhonggen Wang2 and Yin Tang2, (1)University of Chinese Academy of Sciences, Beijing, China, (2)IGSNRR Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
 
Using earth observation data to assess the performance of a global flood forecasting model in an ungauged catchment in Uganda (587197)
Leonore Boelee1, Darren Lumbroso2, Paul Samuels Dr2 and Hannah L Cloke3, (1)Wallingford, England, United Kingdom, (2)HR Wallingford, Wallingford, United Kingdom, (3)University of Reading, Reading, United Kingdom
 
FLOOD RISK ASSESSMENT OF THE PETITE-NATION RIVER IN QUEBEC, CANADA (590401)
Khalid Oubennaceur1, Karem Chokmani2, Yves Gauthier3, Jasmin Gill-Fortin4, Claudie Ratte-Fortin4 and Charles-Andre Bruneau-Tousignant4, (1)Institut National de la Recherche Scientifique-Eau Terre Environnement INRS-ETE, Quebec City, QC, Canada, (2)INRS-ETE, Quebec City, QC, Canada, (3)INRS-ETE, Quebec, QC, Canada, (4)INRS-ETE, Québec, QC, Canada
 
Atmospheric drivers of major flood producing storms in India (595792)
Nanditha J S, IIT Gandhinagar, Discipline of Civil Engineering, Gandhinagar, India, Vimal Mishra, Indian Institute of Technology Gandhinagar, Ahmedabad, 382, India, Balaji Rajagopalan, University of Colorado at Boulder, Department of Civil, Environmental and Architectural Engineering and CIRES, Boulder, CO, United States and Andy Wood, National Center for Atmospheric Research, Boulder, CO, United States
 
From publishable to operational: new metrics to more honestly measure the ability of remote sensing algorithms to consistently monitor flooded assets and populations in near real time (603865)
Beth Tellman1,2, Sam Weber3,4, Lisa Landuyt5,6, Jiayong Liang6, Emmalina Glinskis1, Jeff C Ho7, Jonathan Sullivan8,9 and Colin Doyle1,10, (1)Cloud to Street, New York, NY, United States, (2)Earth Institute, Columbia Water Center and the International Research Center on Climate and Society, New York, NY, United States, (3)Cloud to Street, Brooklyn, NY, United States, (4)University of California Irvine, Department of Ecology and Evolutionary Biology, Irvine, CA, United States, (5)Ghent University, Gent, Belgium, (6)Cloud to Street, New York, United States, (7)Cloud to Street, New York, CA, United States, (8)Cloud to Street, Ann Arbor, MI, United States, (9)University of Michigan, Sustainability, Ann Arbor, MI, United States, (10)University of Texas at Austin, Austin, TX, United States
 
A scale of atmospheric river intensity captures the economic impacts of flooding in the western United States (608194)
Thomas Corringham, Scripps Institution of Oceanography, La Jolla, CA, United States, F Martin Ralph, Scripps Institution of Oceanography, UC San Diego, Center for Western Weather and Water Extremes, La Jolla, CA, United States, Alexander Gershunov, Scripps Institution of Oceanography, Center for Western Weather and Water Extremes (CW3E), La Jolla, CA, United States, Daniel R Cayan, University of California San Diego, La Jolla, CA, United States and Cary Alan Talbot, Engineer Research and Development Center, US Army Corps of Engineers, Coastal and Hydraulics Laboratory, Vicksburg, MS, United States
 
Unprecedented crop loss due to 2019 Midwest US flood quantified from Space (613684)
Manoochehr Shirzaei, Mostafa Khoshmanesh, Chandrakanta Ojha, Grace Carlson, Susanna Werth, Sonam Futi Sherpa, Em Blackwell and Guang Zhai, Arizona State University, Tempe, AZ, United States
 
Impacts of Sea Level Rise on Compound Fluvial and Coastal Flooding (617894)
Mahshid Ghanbari and Mazdak Arabi, Department of Civil and Environmental Engineering, Colorado State University, Fort Collins, CO, United States
 
Reliability of a Low-Complexity Tool for Large-Scale Flood Inundation Mapping (618944)
Michael Follum, U.S. Bureau of Reclamation, Mills, WY, United States, Adnan Rajib, ORISE Fellow at US Environmental Protection Agency, Cincinnati, OH, United States, Zhu Liu, University of California Davis, Davis, CA, United States, Ahmad A Tavakoly, University of Texas, Austin, TX, United States and Venkatesh Merwade, Purdue University, West Lafayette, IN, United States
 
A new observational-modeling framework for flash-flood forecasting in complex-terrain watersheds. (620770)
Vanessa Alexandra Lopera1, Nicolas Velasquez1, Soraya Castillo1, Carlos Hoyos2, Juan Camilo Trujillo Sr3 and Olver Hernandez Sr1, (1)Universidad Nacional de Colombia, Medellin, Medellin, Colombia, (2)National University of Colombia, Bogotá, Colombia, (3)Sistema de Alerta Temprana de Medellín y Valle de Aburrá, Medellin, Colombia
 
Analysis and verification of FloodScan rear-real-time flood mapping during and following Cyclone Idai (627687)
John F. Galantowicz1, Jeffrey Picton1 and Ben Root2, (1)Atmospheric and Environmental Research Lexington, Lexington, MA, United States, (2)Atmospheric and Environmental Research, Lexington, MA, United States
 
Evaluation of the Impacts of Precipitation Uncertainties on Flood Magnitude and Timing (628291)
Nergui Nanding1, Zhijun Huang1, Huan Wu2, Robert F Adler3, Lorenzo Alfieri4, Jingjing Li5 and Xiwu Zhan6, (1)Sun Yat-Sen University, School of Atmospheric Sciences, Guangzhou, China, (2)Sun Yat-Sen University, Guangzhou, China, (3)University of Maryland, College Park, MD, United States, (4)EU Joint Research Centre, Ispra, Italy, (5)California State University-Los Angeles, Los Angeles, CA, United States, (6)NOAA/NESDIS/STAR, College Park, MD, United States
 
Evaluation of S2S Multi-model Extreme Precipitation Forecasts For Flood Forecasting (628389)
Qingyun Duan, Hohai University, Nanjing, China and Wentao Li, Beijing Normal University, Beijing, China
 
Representing the Topographic Effects on Solar Radiation in the National Water Model to Improve Snowmelt Runoff Prediction (629401)
Guo-Yue Niu, University of Arizona, Hydrology and Atmospheric Sciences, Tucson, AZ, United States, Yuanhao Fang, Hohai University, College of Hydrology and Water Resources, Nanjing, China and Michael Barlage, National Center for Atmospheric Research, Boulder, CO, United States
 
Deep Learning-based Flood Extent Mapping with Optical Imagery (631347)
Asmamaw Gebrehiwot, North Carolina Agricultural and Technical State University, High point, NC, United States, Sang-Ho Yun, Jet Propulsion Laboratory, Pasadena, CA, United States and Jungkyo Jung, Seoul National University, Seoul, Korea, Republic of (South)
 
Application of Today’s Earth result for flood assessment (631759)
Wenchao yixisi1505@gmaiL.com, University of Tokyo, Bunkyo-ku, Japan, Kenshi Hibino, The University of Tokyo, Tokyo, Japan, Yuta Ishitsuka, University of Tokyo, Department of Civil Engineering, Bunkyo-ku, Japan, Shinta Seto, Nagasaki University, Nagasaki, Japan, Dai Yamazaki, The University of Tokyo, Institute of Industrial Sciences, Tokyo, Japan, Kosuke Yamamoto, Japan Aerospace Exploration Agency, Tsukuba, Japan, Misako Kachi, JAXA Japan Aerospace Exploration Agency, EORC, Tsukuba, Japan, Riko Oki, JAXA Japan Aerospace Exploration Agency, Sagamihara, Japan, Xiaoxing Wang, The University of Tokyo, Kashiwa, Japan and Kei Yoshimura, The University of Tokyo, Institute of Industrial Science, Kashiwa, Japan
 
Uncertainty Propagation in Flood Hazards and Damage Assessment (631987)
Ping Lu1, Jie Wang2, Long Yang3, Qiuhong Tang2 and Zhu Liu1, (1)Tsinghua University, Department of Earth System Science, Beijing, China, (2)Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing, China, (3)Nanjing University, Nanjing, China
 
SEASONAL PREDICTION OF PRECIPITATION IN THAILMAD BY GENETIC PROGRAMMING (634050)
Kiyoharu Hasegawa, Musashino, Tokyo, Japan and Shinjiro Kanae, Tokyo Institute of Technology, Department of Civil and Environmental Engineering, Tokyo, Japan
 
Risk and Exposure Assessment of Brazilian Municipalities to Flash-Flood: Pilot Study in Places of Itajaí Basin (634759)
Viviana Aguilar-Muñoz, CEMADEN Researcher Fellow, Hydrology and Disasters, São José dos Campos, Brazil, Luz Adriana Cuartas, CEMADEN Researcher, Hydrology, Sao Jose Dos Campos, Brazil, Olga Lucía Pacheco-Calderón, CEMADEN Researcher Fellow, Disasters, São Paulo, Brazil, Aureliene Aparecida Souza Jorge, INPE Computer Technologist, CPTEC, Cachoeira Paulista, Brazil and Leonardo Bacelar Lima Santos, CEMADEN Researcher, Computer Technology, São José dos Campos, Brazil
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