H044
Data Driven Approaches for Flood Observation, Model Validation, and Uncertainty Quantification

Session ID#: 161579

Session Description:
Quantifying flood risk at high resolution across large scales remains a challenge despite major advances in both physics-based and data-driven approaches to flood prediction. Recently, remotely-sensed data products have seen unprecedented improvements in their quality and spatio-temporal coverage. These datasets provide critical information for flood observation, model validation and uncertainty quantification. This session solicits studies leveraging the application of remote sensing products such as Landsat, SMAP, and the upcoming SWOT mission for improving flood predictions. We welcome topics including but not limited to 1) validation of physically-based models across large-scales; 2) machine learning or hybrid (physics-AI) applications involving remote sensing; 3) statistical techniques for quantifying uncertainty in flood models; 4) application of remotely-sensed hydrological variables (such as soil moisture, vegetation, evapotranspiration) for improved flood mapping; 5) assessing the impact of recent climate change on flood risk estimation.
Co-Organized:
  • NH - Natural Hazards
Index Terms:

1821 Floods [HYDROLOGY]
1855 Remote sensing [HYDROLOGY]
1942 Machine learning [INFORMATICS]
4313 Extreme events [NATURAL HAZARDS]

Primary Convener:  Sayan Dey, Purdue University, West Lafayette, IN, United States
Conveners:  Siddharth Saksena, Virginia Polytechnic Institute and State University, Civil and Environmental Engineering, Blacksburg, VA, United States and Abhinav Gupta, Desert Research Institute, Las Vegas, Division of Hydrologic Sciences, Las Vegas, United States
 
Preparing for Future Floods: Leveraging Remotely Sensed Data, Modeling, and Social Science Information in a Multilayer Network Approach (Invited) (1058691)
Paola Passalacqua1, Matthew Preisser2, Mark Wang3, Patrick Bixler4, Allison Hooks2, Julian Hofmann5, Liv Haselbach6, Hamed Moftakhari7, Harry Evans2, Christine Thies2 and David Maidment8, (1)University of Texas at Austin, Dept. of Civil, Architectural, and Environmental Engineering, Austin, TX, United States, (2)University of Texas at Austin, Austin, United States, (3)University of Texas at Austin, Dept. of Civil, Architectural, and Environmental Engineering, Austin, United States, (4)University of Texas at Austin, Austin, TX, United States, (5)RWTH Aachen University, Aachen, Germany, (6)Lamar University, Beaumont, United States, (7)The University of Alabama, Center for Complex Hydrosystems Research, Tuscaloosa, United States, (8)University of Texas at Austin, Center for Research in Water Resources, Austin, TX, United States
 
Uncertainty Reduction in Fluvial Flood Re-analysis by Assimilating SAR-derived Flood Extent Maps (1062771)
Thanh Huy Nguyen1, Sophie M Ricci1, Andrea Piacentini2, Raquel Rodriguez3, Gwendoline Blanchet3, Cedric H David4, Peter Kettig3 and Simon Baillarin3, (1)CECI, CERFACS/UMR5318-CNRS, Toulouse Cedex 1, France, (2)CERFACS European Centre for Research and Advanced Training in Scientific Computation, Toulouse Cedex 01, France, (3)Centre National d'Études Spatiales, Toulouse Cedex 9, France, (4)NASA Jet Propulsion Laboratory, California Institute of Technology, Pasadena, United States
 
Evaluation of Regional Physically-based Flood Model Outputs using Flood Extent Maps from Remote Sensing for Flood Events in Japan (1063007)
Sam Lamont1, Chandana Gangodagamage2, Zhuo Liu1, Yawen Shen1, Hoda El Safty1, Yi Liu1, Yu Zhang1, Feyera Hirpa1, Ting Li1, Liping Liu1, Brett Baker1 and Shabaz Patel1, (1)One Concern, Inc., Menlo Park, CA, United States, (2)University of Maryland, ESSIC, Greenbelt, United States
 
Unpiloted Aerial Vehicle (UAV) Image Velocimetry for Validation of Two-dimensional Hydraulic Model Simulations (1071309)
Christopher Masafu, University of Glasgow, Glasgow, G12, United Kingdom, Richard Williams, University of Glasgow, School of Geographical and Earth Sciences, Glasgow, G12, United Kingdom, Xiaogang Shi, University of Glasgow, School of Interdisciplinary Studies, Glasgow, United Kingdom, Qiangqiang Yuan, Wuhan University, School of Geodesy and Geomatics, Wuhan, China and Mark Trigg, University of Leeds, Leeds, United Kingdom
 
Assessment of different satellite precipitation products on streamflow simulation in arid to semi-arid data sparse-region : A case study of Souss River (South Morocco) (1104352)
Ismail Bouizrou, UNITED STATES, Mourad Aqnouy, Moulay Ismaïl University, Faculty of Sciences and Techniques, Errachidia, Morocco, Applied Geology and Remote Sensing Research Team, Applied Geology Research Laboratory, Errachidia, Morocco and Abdelmounaim Bouadila, Moulay Ismaïl University, Faculty of Sciences and Techniques, Errachidia, Applied Geology and Remote Sensing Research Team, Applied Geology Research Laboratory, Fez, Morocco
 
Urban Flood Dataset: A globally representative satellite-based labeled dataset of flooding in urban settings (1108915)
Hannah Friedrich1, Beth Tellman2, Rohit Mukherjee2, Zhijie Zhang1, Jonathan Giezendanner1, Venkataraman (Venkat) Lakshmi3 and Upmanu Lall4, (1)University of Arizona, School of Geography, Development and Environment, Tucson, United States, (2)University of Arizona, School of Geography, Development and Environment, Tucson, AZ, United States, (3)University of Virginia, Engineering Systems and Environment, Charlottesville, United States, (4)Columbia University, Earth and Environmental Engineering, New York, United States
 
Daily Flood Mapping Using U-Nets for MODIS and VIIRS (1127670)
Nicholas Leach1, Veda Sunkara2, Philip Popien3 and Colin Doyle1, (1)Cloud to Street, Brooklyn, United States, (2)Cloud to Street, New York, NY, United States, (3)Cloud to Street, New York, United States
 
A Data-driven Spatial Approach to Characterize Flood Hazard (1133202)
Rubayet Bin Mostafiz1, Md Adilur Rahim2, Carol J Friedland3 and Robert V Rohli1, (1)Louisiana State University, Oceanography and Coastal Sciences, Baton Rouge, LA, United States, (2)Louisiana State University, Baton Rouge, LA, United States, (3)Louisiana State University Agricultural Center, Department of Biological and Agricultural Engineering, LaHouse Resource Center, Baton Rouge, United States
 
c-HAND: Near Real-Time Coastal Flood Mapping (1135033)
Mark Wang, University of Texas at Austin, Dept. of Civil, Architectural, and Environmental Engineering, Austin, United States, Paola Passalacqua, University of Texas at Austin, Dept. of Civil, Architectural, and Environmental Engineering, Austin, TX, United States, Shukai Cai, University of Texas at Austin, Oden Institute for Computational Engineering and Sciences, Austin, United States and Clint Dawson, University of Texas at Austin, Aerospace Engineering & Engineering Mechanics, Austin, TX, United States
 
Expected amount of data accumulation to develop reasonable flash flood predictive models using machine learning approaches (1137394)
Hyunje Yang, Haewon Moon, Honggeun Lim, Jaehoon Kim and Hyung Tae Choi, National Institute of Forest Science, Forest Environment and Conservation Department, Seoul, South Korea
 
New insights into damage initiation point of depth-damage function revealed from flood risk patterns in the United States (1166326)
Md Adilur Rahim1, Rubayet Bin Mostafiz2, Carol J Friedland3 and Robert V Rohli2, (1)Louisiana State University, Baton Rouge, LA, United States, (2)Louisiana State University, Oceanography and Coastal Sciences, Baton Rouge, LA, United States, (3)Louisiana State University Agricultural Center, Department of Biological and Agricultural Engineering, LaHouse Resource Center, Baton Rouge, United States
 
Flooding Assessment Using Computer Vision on Smallsat Imagery (1175992)
Madhu Sridhar1, Vishal Perekadan2, Bradley W Baker2 and Aaron S Kaulfus3, (1)University of Alabama in Huntsville, Huntsville, United States, (2)University of Alabama in Huntsville, Huntsville, AL, United States, (3)NASA Marshall Space Flight Center, Huntsville, United States
 
A Vision-based Framework for Monitoring and Measurement of Water Depth (1177369)
Mohammad Erfani, University of South Carolina, Civil and Environmental Engineering, Columbia, United States and Erfan Goharian, University of South Carolina, Civil and Environmental Engineering, Columbia, SC, United States
 
Flood frequency analysis using gap-filled daily streamflow time series (1178032)
Rishitha Bikkumalla, Indian Institute of Technology Gandhinagar, Ahmedabad, 382, India, Nanditha J S, Indian Institute of Technology, Gandhinagar, Discipline of Civil Engineering, Gandhinagar, India and Vimal Mishra, Indian Institute of Technology Gandhinagar, Department of Civil Engineering, Ahmedabad, India
 
Investigation of Long-lasting Damage Due to Hagibis Flood Using SAR Polarimetry and ALOS-2 Data in Japan (1180937)
Ruma Adhikari, Indian Institute of Technology Roorkee, Roorkee, India, Alok Bhardwaj, Indian Institute of Technology Roorkee, Civil Engineering, Roorkee, India and Unmesh Khati, Indian Institute of Technology Indore, Indore, India
 
Multiresolution Calibration of a Flood Hazard Model (1182198)
Samantha Roth, Pennsylvania State University Main Campus, Statistics, University Park, United States, Benjamin Seiyon Lee, George Mason University, Department of Statistics, Fairfax, VA, United States, Sanjib Sharma, Pennsylvania State University, Earth and Environmental Systems Institute, University Park, PA, United States, Iman Hosseini-Shakib, Pennsylvania State University Main Campus, Earth and Environmental Systems Institute, University Park, PA, United States, Klaus Keller, Dartmouth College, Thayer College of Engineering, Hanover, United States and Murali Haran, Pennsylvania State University, University Park, PA, United States
 
Satellite-Based Flood Inundation Mapping: A Multi-Regional Evaluation of VIIRS and SAR Products (1182356)
Efthymios Ioannis Nikolopoulos, Rutgers University New Brunswick, Civil and Environmental Engineering, New Brunswick, United States, Pramod Pandey, Florida Institute of Technology, Melbourne, United States, Emanuel Storey, San Diego State University, Geography, San Diego, CA, United States, Qingyuan Zhang, University of Maryland, Earth System Science Interdisciplinary Center, College Park, United States, Josef Kellndorfer, NOAA Center for Satellite Applications and Research, College Park, United States, Wei Hao, NOAA Center for Satellite Applications and Reserch, College Park, United States, Fernando Aristizabal, Lynker, Leesburg, United States, William C. Straka, University of Wisconsin Madison, Cooperative Institute for Meteorological Satellite Studies, Madison, WI, United States, Sanmei Li, George Mason University Fairfax, Fairfax, VA, United States, Sean Helfrich, NESDIS, NOAA, Center for Satellite Applications and Research, College Park, United States and Witold F Krajewski, University of Iowa, Iowa City, United States
 
Urban Flooding Open Knowledge Network (UFOKN): Current products and future functionalities (1188049)
Siddharth Saksena, Virginia Polytechnic Institute and State University, Civil and Environmental Engineering, Blacksburg, VA, United States
 
Evaluation of Hydrologic Parameter Variability on Flood Inundation extents and Decentralized Flood Mitigation Measure Effectiveness and Optimal Ranking (1200315)
Jessica Seersma1, Siddharth Saksena2, Sayan Dey3, Peter Singhofen4 and Venkatesh Merwade3, (1)Colorado State University, Fort Collins, United States, (2)Virginia Polytechnic Institute and State University, Civil and Environmental Engineering, Blacksburg, VA, United States, (3)Purdue University, West Lafayette, IN, United States, (4)Streamline Technologies, Winter Springs, FL, United States
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