H197
Global Floods: Forecasting, Monitoring, Risk Assessment, and Socioeconomic Response III Posters

Wednesday, 16 December 2020: 04:00-20:59
Poster
Primary Convener:  Huan Wu, Sun Yat-Sen University, School of Atmospheric Sciences, Guangzhou, China
Conveners:  Philip Ward, IVM - VU University Amsterdam, Amsterdam, Netherlands, Dennis P Lettenmaier, UCLA, Department of Geography, Los Angeles, CA, United States and Donglian Sun, George Mason University Fairfax, Fairfax, VA, United States
Primary Liaison:  Huan Wu, Sun Yat-Sen University, Guangzhou, China
Chairs:  Philip Ward, IVM - VU University Amsterdam, Amsterdam, Netherlands and Donglian Sun, George Mason University Fairfax, Fairfax, VA, United States
OSPA Liaison:  Huan Wu, Sun Yat-Sen University, Guangzhou, China
 
A Bayesian Hierarchical Network Model for Daily Streamflow Forecasting (755250)
Álvaro Humberto Ossandón Sr, University of Colorado Boulder, Boulder, CO, United States, Balaji Rajagopalan, University of Colorado at Boulder, Department of Civil, Environmental and Architectural Engineering and CIRES, Boulder, CO, United States, Upmanu Lall, Columbia University, New York, NY, United States, Vimal Mishra, Indian Institute of Technology Gandhinagar, Ahmedabad, 382, India and Nanditha J S, Indian Institute of Technology, Gandhinagar, Discipline of Civil Engineering, Gandhinagar, India
 
A Coupled Physical-Statistical Model for Daily Streamflow Forecasting (735187)
Nanditha J S, Indian Institute of Technology, Gandhinagar, Discipline of Civil Engineering, Gandhinagar, India, Álvaro Humberto Ossandón Sr, University of Colorado Boulder, Boulder, CO, United States, Balaji Rajagopalan, University of Colorado at Boulder, Department of Civil, Environmental and Architectural Engineering and CIRES, Boulder, CO, United States and Vimal Mishra, Indian Institute of Technology Gandhinagar, Ahmedabad, 382, India
 
Assessment of Flood Damage on Early, Medium and Late Rice Crop (677605)
Vuthy Men1, Koji Ikeuchi Prof2, Dai Yamazaki3 and Badri Bhakta Shrestha1, (1)The University of Tokyo, Department of Civil Engineering, Tokyo, Japan, (2)University of Tokyo, Department of Civil Engineering, Tokyo, Japan, (3)The University of Tokyo, Institute of Industrial Sciences, Tokyo, Japan
 
Blending Unconventional Data with Geopotential Height Anomalies to Understand Urban Floods in Hyderabad, India (774225)
Mohammed Azharuddin, Indian Institute of Technology Hyderabad, Hydearbad, India and Satish Kumar Regonda, Indian Institute of Technology Hyderabad, Environmental and Water resources Engineering, Department of Civil Engineering, Hyderabad, India
 
Enhancing community engagement and resilience: Reducing the socio-economic impacts of flooding in Pakistan (734680)
Kiran Khalid, University of the Punjab, Hailey College of Banking and Finance, Lahore, Pakistan and Arslaan Khalid, George Mason University Fairfax, Fairfax, VA, United States
 
Flood-Health Vulnerability and Predictability of Observed Flood Impacts using Flood Forecast and Satellite Inundation in Bangladesh (731635)
Donghoon Lee, University of Wisconsin Madison, Madison, WI, United States, Hassan Ahmadul, Red Cross Climate Centre, Hague, Netherlands and Paul J Block, University of Wisconsin Madison, Department of Civil and Environmental Engineering, Madison, WI, United States
 
How Do Changing Hurricane Rainfall Estimates Affect Pluvial Flood Risk in the Caribbean Under Current and Future Climate Change? (693037)
Leanne Archer1, Jeffrey C Neal2, Paul D Bates2, Emily L Vosper2 and Dann Mitchell2, (1)University of Bristol, School of Geographical Sciences, Bristol, BS8, United Kingdom, (2)University of Bristol, School of Geographical Sciences, Bristol, United Kingdom
 
Identification of flood events using Sentinel 2 and Landsat 8 data on the Google Earth Engine in Hyderabad City (776739)
Samba Siva Sai Prasad Thota1, Mohammed Azharuddin1 and Satish Kumar Regonda2, (1)Indian Institute of Technology Hyderabad, Hydearbad, India, (2)Indian Institute of Technology Hyderabad, Environmental and Water resources Engineering, Department of Civil Engineering, Hyderabad, India
 
Increased urban exposure to flooding from 1985 to 2015 (771518)
Ziyu Lin1,2, Zhenzhong Zeng3, Xiaoping Liu1, Alan D. Ziegler4, Xiaocong Xu5 and Rongrong Xu3, (1)Sun Yat-Sen University, School of Geography and Planning, Guangzhou, China, (2)University of Hong Kong, School of Biological Sciences, Hong Kong, Hong Kong, (3)Southern University of Science and Technology, School of Environmental Science and Engineering, Shenzhen, China, (4)Mae Jo University, Faculty of Fisheries & Aquatic Resources, Chiang Mai, Thailand, (5)Sun Yat-sen University, School of Geography and Planning, Guangzhou, China
 
Influence of the monsoonal activity and hydrological conditions on big floods over Bengal delta (723242)
Dewan Abdul Quadir1, Towhida Rashid1, Nazmul Ahasan1 and Toma Rani Saha2, (1)University of Dhaka, Department of Meteorology, Dhaka, Bangladesh, (2)Helmholtz Centre for Environmental Research - UFZ, Computational Hydrosystems, Leipzig, Germany
 
Leveraging earth observation and inundation models to map frequent to rare flood hazards (691965)
Laurence Paul Hawker, University of Bristol, Bristol, BS8, United Kingdom, Jeffrey C Neal, University of Bristol, School of Geographical Sciences, Bristol, United Kingdom, Beth Tellman, Arizona State University, Tempe, AZ, United States, Jiayong Liang, Cloud to Street, New York, United States, Guy Schumann, Remote Sensing Solutions, Inc., Pasadena, CA, United States, Colin Doyle, The University of Texas at Austin, Department of Geography and the Environment, Austin, TX, United States, Jonathan Sullivan, Cloud to Street, Ann Arbor, MI, United States, James Savage, Fathom, Bristol, United Kingdom and Raphael Muamba Tshimanga, University of Kinshasa, Congo Basin Water Resources Research Center (CRREBaC) & Dept. Natural Resources Management, Kinshasa, Congo
 
Leveraging Soil Moisture for Early Flood Detection (758361)
Veda Sunkara1, Colin Doyle2, Hyunglok Kim3, Beth Tellman4 and Venkataraman (Venkat) Lakshmi3, (1)Cloud to Street, New York, NY, United States, (2)The University of Texas at Austin, Department of Geography and the Environment, Austin, TX, United States, (3)University of Virginia, Engineering Systems and Environment, Charlottesville, VA, United States, (4)Arizona State University, Tempe, AZ, United States
 
Nonstationary regional flood inundation projection under climate change: a case study of Athabasca River Basin, Canada (676171)
Guanhui Cheng1, Gordon Huang1, Feng Wang2, Nan Wang1, Jiannan Zhang1, Kailong Li3 and Cong Dong1, (1)University of Regina, Regina, Canada, (2)Beijing Normal University, Beijing, China, (3)University of Regina, Regina, SK, Canada
 
Prediction of flood claims over the contiguous United States (CONUS) by building a classification/regression-hybrid machine learning scheme (669063)
Qing Yang1,2, Xinyi Shen2, Feifei Yang3, Kang He3, Emmanouil N Anagnostou2, Hojjat Seyyedi4, Jack Eggleston5 and Albert Kettner6, (1)Guangxi University, College of Civil Engineering and Architecture, Nanning, China, (2)University of Connecticut, Civil and Environmental Engineering, Storrs, CT, United States, (3)University of Connecticut, Civil and Environmental Engineering, Groton, CT, United States, (4)Swiss Re America Holding Corporation, Schaumburg, IL, United States, (5)U.S. Geological Survey, Hydrologic Remote Sensing Branch, Leetown, WV, United States, (6)University of Colorado Boulder, INSTAAR, Boulder, CO, United States
 
Quantifying the Impact of Observation Operators on Flood Inundation Forecast Quality (664997)
Antara Dasgupta1,2, Renaud Hostache3, Raaj Ramsankaran1, Guy Schumann4,5, Concetta Di Mauro6,7, Stefania Grimaldi8, Valentijn R N Pauwels9 and Jeffrey P Walker10, (1)Indian Institute of Technology Bombay, Civil Engineering, Mumbai, India, (2)IITB-Monash Research Academy, Powai, India, (3)Luxembourg Institute of Science and Technology, Environmental Research and Innovation, Belvaux, Luxembourg, (4)Remote Sensing Solutions, Inc., Pasadena, CA, United States, (5)University of Bristol, School of Geographical Sciences, Bristol, United Kingdom, (6)Vienna University of Technology, Centre for Water Resource Systems, Vienna, Austria, (7)Luxembourg Institute of Science and Technology, Environmental Research and Innovation, Esch-sur-alzette, Luxembourg, (8)Monash University, Clayton, Australia, (9)Monash University, Melbourne, Australia, (10)Monash University, Department of Civil Engineering, Clayton, VIC, Australia
 
 
Real Time Data Acquisition System for Flood Forecasting Using telemetry system (699632)
Sanjaya Gurung, Real Time Solutions Pvt. Ltd., Lalitpur, Nepal
 
rSHUD: An R Package Facilitating Quick and Reproducible Hydrologic Deployment Worldwide. (775005)
Lele Shu, University of California Davis, Davis, CA, United States, Paul Aaron Ullrich, University of California Davis, Land, Air & Water Resources, Davis, CA, United States and Christopher Duffy, Pennsylvania State University Main Campus, Department of Environmental and Civil Engineering, University Park, PA, United States
 
Title: Capacity Building to Enhance Resilience to Hydrodynamic Disasters in Emerging Regions (751846)
Teshome Lemma Yami1, Jonathan J Gourley2, Shang Gao3, Mengye Chen4, Zhi Li1, Humberto J Vergara5, Race A Clark1, Laura G Labriola6, Daniel Mandl7, Yang Hong8 and Shang Gao, (1)University of Oklahoma Norman Campus, Norman, OK, United States, (2)National Severe Storms Lab, Oklahoma City, OK, United States, (3)University of Oklahoma, Oklahoma, United States, (4)The University of Oklahoma, Norman, OK, United States, (5)Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, Norman, OK, United States, (6)University of Oklahoma Norman Campus, Civil Engineering and Environmental Science, Norman, OK, United States, (7)NASA Goddard Space Flight Center, Greenbelt, MD, United States, (8)School of Civil Engineering and Environmental Sciences, University of Oklahoma, Norman, OK, United States
 
Urban Flood Monitoring Using an Integrated River Basin-Urban Flood Modeling Approach (719324)
Weitian Chen1, Huan Wu1, Naijun Zhou2 and Xiaomeng Li3, (1)Sun Yat-Sen University, Guangzhou, China, (2)University of Maryland, College Park, MD, United States, (3)Sun Yat-Sen University, School of Atmospheric Sciences, Guangzhou, China
 
Using CYGNSS to Monitor Flood in Southern China (693111)
Can Wang, Zhejiang University, Zhejiang University/University of Illinois at Urbana-Champaign Institute, Hangzhou, China and Shurun Tan, Zhejiang University, Zhejiang University/University of Illinois at Urbana-Champaign Institute, Haining, China
 
Using remote sensing to collect data on the impact of flooding on the built environment in Kerala, India (731038)
Eleanor A Ainscoe1, Barbara Hofmann1, Steven Reece2 and Quillon K Harpham1, (1)HR Wallingford, Wallingford, United Kingdom, (2)University of Oxford, Oxford, United Kingdom
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