H019
Advancing flood characterization, modeling and communication
Session ID#: 159699
Session Description:
Flooding is a disastrous phenomenon that has adverse impacts on human life, economy, and environment across the world. Mitigating these impacts requires a comprehensive characterization of flooding through improvements in computer modeling and prediction and effective communication with stakeholders and decision-makers. To cover these topics, this special collection welcomes studies that focus on: (1) innovative techniques (e.g. data assimilation, Machine Learning, and other data-driven methods) that improve the modeling and estimation of flood characteristics (e.g. magnitude, timing, and extent); (2) studies that address the current limitations of design flood estimation, real-time flood inundation and risk modeling (hydrologic, hydrodynamic and loss models); (3) methods that bridge the gaps between science and practice through stakeholder engagement; (4) the impact of nonstationary stressors (e.g., climate and land cover change) and uncertainties related to flood predictions; and (5) studies that focus on socio-economic impacts of floods. Contributions can address various types of flooding, including coastal, fluvial, pluvial, and dam/levee break.
Index Terms:
1817 Extreme events [HYDROLOGY]
1821 Floods [HYDROLOGY]
1856 River channels [HYDROLOGY]
4328 Risk [NATURAL HAZARDS]
Primary Convener: Keighobad Jafarzadegan, University of Alabama, Tuscaloosa, United States
Conveners: Manuela Irene Brunner, University of Freiburg, Institute of Earth and Environmental Sciences, Freiberg, Germany, Brett F Sanders, University of California Irvine, Irvine, CA, United States and Ebrahim Ahmadisharaf, FAMU-FSU College of Engineering, Department of Civil and Environmental Engineering, Tallahassee, United States
Student/Early Career Convener: Ebrahim Ahmadisharaf, FAMU-FSU College of Engineering, Department of Civil and Environmental Engineering, Tallahassee, United States
Advantages of Physically-based Flood Frequency Analysis with Long Term Simulations for Iowa (1046209)
Alexander Michalek, University of Iowa, Civil and Environmental Engineering, Iowa City, IA, United States, Felipe Quintero, University of Iowa, Iowa City, IA, United States, Gabriele Villarini, University of Iowa, IIHR—Hydroscience & Engineering, Iowa City, IA, United States and Witold F Krajewski, University of Iowa, Iowa City, United States
Parametric Approach for Land Building Regulation as A Flood Risk Reduction Measure: New Cairo, Egypt as A Case Study (1047635)
Karim I Abdrabo1, Bahaa Elboshy2, Mohamed Saber1, Tetsuya Sumi3 and Sameh Kantosh1, (1)Disaster Prevention Research Institute, Kyoto University, Kyoto, Japan, (2)Tanta University, Architectural Engineering Department, Tanta, Egypt, (3)Kyoto University, Disaster Prevention Research Institute, Kyoto, Japan
Improving Streamflow and Flood Predictions Through Computational Simulations, Machine Learning and Uncertainty Quantification (Invited) (1051092)
Venkatesh Merwade1, Siddharth Saksena2, Sayan Dey3, Pin-Ching Li3 and Tao Huang4, (1)Lyles School of Civil Engineering, Purdue University, West Lafayette, IN, 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)School of Electronic Information, Wuhan University, Dept. of Space Physics, Wuhan, China
Upskilling Low-Fidelity Hydrodynamic Models of Flood Inundation Through Spatial Analysis and Gaussian Process Learning (1054960)
Q. J. WANG1, Niels Fraehr2, Wenyan Wu2 and Rory Nathan3, (1)University of Melbourne, Parkville, Australia, (2)The University of Melbourne, Parkville, Australia, (3)University of Melbourne, Department of Infrastructure Engineering, Parkville, VIC, Australia
Post-Assessment of ECMWF-mHM ensemble flood forecasting for 2021 summer flood in west Germany (1061214)
Husain Najafi1, Oldrich Rakovec1, Pallav Kumar Shrestha1, Stephan Thober1 and Luis Samaniego2, (1)Helmholtz Centre for Environmental Research - UFZ, Computational Hydrosystems, Leipzig, Germany, (2)Helmholtz Centre for Environmental Research GmbH – UFZ, Computational Hydrosystems, Leipzig, Germany
Seamlessly Coupling a Rainfall-Runoff Model and an Unstructured-grid Inundation Model (1061790)
Sam Lamont, Zhuo Liu, Yu Zhang, Yi Liu, Feyera Hirpa, Ting Li, Liping Liu, Yawen Shen, Hoda El Safty, Brett Baker and Shabaz Patel, One Concern, Inc., Menlo Park, CA, United States
Reconstruction of historical California flood forecasts (1073270)
Xiaoyu Ma, University of California Los Angeles, Department of Geography, Los Angeles, CA, United States and Dennis P Lettenmaier, UCLA, Department of Geography, Los Angeles, CA, United States
Daily Flood Forecasting for a Tropical River basin using state-of-the-art Deep Learning Techniques (1080119)
Siddharth Chatterjee, Indian Institute of Engineering Science and Technology, Shibpur, West Bengal, India, Amina Khatun, Indian Institute of Technology Kharagpur, Agricultural and Food Engineering Department, Kharagpur, India, Sudip Misra, Indian Institute of Technology Kharagpur, Department of Computer Science and Engineering, Kharagpur, India and Timam Ghosh, National Institute of Technology Rourkela, Department of Computer Science and Engineering, Rourkela, India
Horizontal 2D Flood Simulation on Flooding and Vehicle Stability at Car Accidents (1083303)
Nozomi Yusa1, Nanako Utsugisawa2, Koyo Ota2, Takehiko Ito2, Yuki Ogata3, Shiho Onomura2 and Yasuo Nihei2, (1)Tokyo University of Science, Graduate School of Science and Engineering, Department of Civil Engineering, Tokyo, Japan, (2)Tokyo University of Science, Tokyo, Japan, (3)Tokyo university of science, Tokyo, Japan
An assessment of Compound Flooding Impacts across the East Coast, USA (1087630)
Mahjabeen Fatema Mitu1, Giulia Sofia2, Xinyi Shen2 and Emmanouil N Anagnostou3, (1)University of Connecticut, Civil and Environmental Engineering, Groton, CT, United States, (2)University of Connecticut, Civil and Environmental Engineering, Storrs, CT, United States, (3)Professor, Civil and Environmental Engineering, Storrs, United States
Uncertainty quantification is crucial to improve urban flood risk projections (1087987)
Sanjib Sharma1, Xue Li2, Benjamin Seiyon Lee3, Dave Judi2 and Klaus Keller4, (1)Pennsylvania State University Main Campus, Earth and Environmental Systems Institute, University Park, PA, United States, (2)Pacific Northwest National Laboratory, Richland, WA, United States, (3)George Mason University, Department of Statistics, Fairfax, VA, United States, (4)Dartmouth College, Thayer College of Engineering, Hanover, United States
Rapid Flood Extent Mapping for the Houston Metropolis (1090020)
Aylar Samadi, University of Alabama, Civil, Construction, and Environmental Engineering, Tuscaloosa, United States, Keighobad Jafarzadegan, The University of Alabama, Center for Complex Hydrosystems Research, Tuscaloosa, AL, United States and Hamid Moradkhani, The University of Alabama, Civil, Construction, and Environmental Engineering, Tuscaloosa, United States
Flood Potential Portal: A Web Tool For a Better Understanding of Riverine Flood Hazards in the U.S. (1100841)
Mahshid Ghanbari, Department of Civil and Environmental Engineering, Colorado State University, Fort Collins, CO, United States, Steven E Yochum, US Forest Service Fort Collins, Fort Collins, CO, United States, Tyler Wible, Colorado State University, Fort Collins, United States and Mazdak Arabi, Civil and Environmental Engineering Department, Colorado State University, Fort Collins, United States
A catastrophe risk model for current and future flooding in the UK (1103237)
Paul D Bates1, James Savage2, Oliver Wing3, Niall Quinn4, Christopher Sampson4 and Andrew Smith Dr4, (1)University of Bristol, School of Geographical Sciences, Bristol, United Kingdom, (2)Fathom, Bristol, Bristol, UNITED KINGDOM, (3)SSBN Ltd, Bristol, United Kingdom, (4)Fathom, Bristol, United Kingdom
Development of Non-Data Driven Reservoir Routing in the Routing Application for Parallel computatIon of Discharge (RAPID) Model (1110629)
Mark Wahl, US Army Engineer Research and Development Center, Coastal and Hydraulics Laboratory, Vicksburg, MS, United States, Michael L Follum, Follum Hydrologic Solutions, Casper, WY, United States, Cedric H David, NASA Jet Propulsion Laboratory, California Institute of Technology, Pasadena, United States, Joseph Gutenson, US Army Engineer Research and Development Center, Cottondale, AL, UNITED STATES and Ahmad A Tavakoly, US Army Corps of Engineers, Jacksonville, FL, United States
BayesOpt-SWMM: A Gaussian process-based Bayesian Optimization Tool for Parameter Calibration and Uncertainty Analysis of SWMM Model (1119262)
Ahad Hasan Tanim, University of South Carolina Columbia, Columbia, SC, United States, Erfan Goharian, University of South Carolina, Civil and Environmental Engineering, Columbia, SC, United States and Jasim Imran, University of South Carolina, Columbia, Columbia, United States
A Regional Flow-Duration-Frequency Analysis for the State of Vermont (1122807)
Scott Lawson1, Kristen Underwood1, Rebecca Manners Diehl2 and Donna M Rizzo1, (1)University of Vermont, Department of Civil and Environmental Engineering, Burlington, VT, United States, (2)University of Vermont, Geography, Burlington, VT, United States
Optimizing Historical Storms with HEC-HMS (1132244)
Thomas Brauer1, Joshua Willis1, Gregory S. Karlovits1 and Lauren Coe2, (1)U.S. Army Corps of Engineers Hydrologic Engineering Center, Davis, United States, (2)U.S. Army Corps of Engineers Los Angeles District, Los Angeles, United States
Grid Edge Classification Method to Enhance Levee Resolution in Dual-Grid Inundation Models (1136671)
Daniel Kahl1, Jochen E Schubert2, Ariane Jong1 and Brett F Sanders1, (1)University of California Irvine, Department of Civil and Environmental Engineering, Irvine, United States, (2)University of California Irvine, Department of Civil and Environmental Engineering, Irvine, CA, United States
Characterization of flash flood hydrographs and their relationship with hydro-geomorphologic parameters (1151691)
Mariana Alvarez Moncada1, Esneider Zapata1, Janet Barco2, Julian Uran1 and Jose Lozano1, (1)Area Metropolitana del Valle de Aburrá, Proyecto Sistema de Alerta Temprana de Medellín y el Valle de Aburrá (SIATA), Medellin, Colombia, (2)Universidad de Medellín, Medellin, Colombia
Assessing differential impacts of storm-surge flooding on coastal communities of the Great Lakes (1152942)
Yi Hong, University of Michigan - Cooperative Institute for Great Lakes Research, Ann Arbor, United States, Sara Hughes, University of Michigan, Cooperative Institute for Great Lakes Research, Ann Arbor, United States and Eric J Anderson, Great Lakes Environmental Research Laboratory (GLERL), National Oceanic and Atmospheric Administration (NOAA), Ann Arbor, United States
Application of Empirical River Flow Forecasting Models for Poorly Gauged and Ungauged Basins Located in Cold Weather Regions (1156854)
Chiara Belvederesi1, John Albino Dominic2, Anil Gupta3, Gopal Achari2 and Quazi K. Hassan2, (1)University of Calgary, Calgary, AB, Canada, (2)University of Calgary, Calgary, Canada, (3)Alberta Environment and Parks, Calgary, AB, Canada
Application of Hybrid Optimization for Calibration of Streamflow in Narmada River Basin (1165398)
Surya Kiran Guniganti, Indian Institute of Technology Hyderabad, Civil Engineering, Hydearbad, India, Satish Kumar Regonda, Indian Institute of Technology Hyderabad, Department of Civil Engineering and Department of Climate Change, Hydearbad, India, Seann M Reed, NOAA/NWS Middle Atlantic River Forecast Center, State College, United States and Balaji Rajagopalan, Univ Colorado, Civil, Environmental, and Architectural Engineering and Cooperative Institute for Research in Environmental Sciences, Boulder, United States
Evaluation of Real-time Short-range Urban Flood Forecasting Using a 2-D Hydrodynamic Model and Precipitation Forecast Ensemble (1166967)
Gustavo de Almeida Coelho1, Celso Ferreira2, James L Kinter3,4 and Felício Cassalho3, (1)Furman University, Earth, Environmental, and Sustainability Sciences, Greenville, SC, United States, (2)George Mason University, Sid and Reva Dewberry Dept of Civil, Environmental & Infrastructure Engineering, Fairfax, VA, United States, (3)George Mason University, Fairfax, VA, United States, (4)Center for Ocean-Land-Atmosphere Studies, Climate Dynamics, Fairfax, United States
Optimal mesh discretization for a hydrodynamic model based on significant vertical features with element size function on Louisiana coastal wetlands (1167247)
Shu Gao1, Peter Bacopoulos1, Jin Ikeda2 and Celalettin Emre Ozdemir3, (1)Louisiana State University, Coastal Ecosystem Design Studio, Baton Rouge, United States, (2)Louisiana State University, Center for Computation and Technology, Baton Rouge, LA, United States, (3)Louisiana State University, Civil and Environmental Engineering, Baton Rouge, United States
Flood Evolution under Anthropogenic Change: Non-Uniform Flood Hazard Increases across Three Tributaries within an Eastern North Carolina City by End of Century (1172688)
Hunter Carey Quintal, University of North Carolina at Chapel Hill, Department of Earth, Marine and Environmental Sciences, Chapel Hill, NC, United States, Antonia Sebastian, University of North Carolina at Chapel Hill, Environment, Ecology and Energy Program, Chapel Hill, NC, United States and Kathie Dello, State Climate Office of North Carolina, Raleigh, NC, United States
Comprehensive Urban Flood Assessment Framework to Incorporate the Influence of Changing Climate (1174751)
Lalit Pal1, Sayan Dey2, Siddharth Saksena3, Venkatesh Merwade2 and Chandra Shekhar Prasad Ojha4, (1)Indian Institute of Technology Roorkee, Civil Engineering Department, Roorkee, India, (2)Purdue University, West Lafayette, IN, United States, (3)Virginia Polytechnic Institute and State University, Civil and Environmental Engineering, Blacksburg, VA, United States, (4)Indian Institute of Technology (IIT) Roorkee, Civil Engineering, Roorkee, India
Ice-Jam Flood Risk Assessment for Canada using a Machine Learning Approach (1179174)
Keith A Sawicz1, Matthew Hergott2, Samyadeep Ghosh3, Geetha Sakamuri4 and Kiran Chinnayakanahalli1, (1)Verisk Analytics, Research, Boston, United States, (2)Verisk Analytics, Boston, United States, (3)Verisk Analytics, Research, Hyderabad, India, (4)Verisk Analytics, Hyderabad, India
Investigation into the Impacts of Land Subsidence on Flood Inundation during Hurricane Harvey in Brays Bayou, Texas (1184964)
Han Jiang1, Jiaqi Zhang1, Yi Liu2 and Nick Z. Fang1, (1)University of Texas at Arlington, Civil Engineering, Arlington, TX, United States, (2)Morgan State University, Civil Engineering, Baltimore, United States
Flood Hazard Assessment for Urbanized Areas with an Indicator of Potential Impact on Humans (1188846)
Weichen Huang1, Kevin Murphy2, Fariborz Daneshvar1, Timothy Marchman3, Daniel Dominique3, Glenn O’Neil4 and Valeriy Yu Ivanov2, (1)University of Michigan, Civil and Environmental Engineering, Ann Arbor, United States, (2)University of Michigan, Civil and Environmental Engineering, Ann Arbor, MI, United States, (3)University of Michigan, Environment and Sustainability, Ann Arbor, United States, (4)Institute of Water Research, Michigan State University, East Lansing, United States
Lowering Barriers to Process-Based Prediction and Understanding of Flood Frequency using the Nextgen Water Modeling Framework (1194697)
Daniel Wright, University of Wisconsin-Madison, Department of Civil and Environmental Engineering, Madison, United States, Luciana Cunha, WEST Consultants Inc., Folsom, United States, Fred L. Ogden, NOAA/NWS Office of Water Prediction, National Water Center, Tuscaloosa, United States and Benjamin FitzGerald, University of Wisconsin-Madison, Civil and Environmental Engineering, Madison, United States
Compound flood hazard assessment using a Bayesian framework (1195029)
Somayeh Mohammadi1, Michelle Bensi2, Shih-Chieh Kao3, Scott DeNeale3, Joseph Kanney4, Elena Yegorova4 and Meredith Carr5, (1)University of Maryland College Park, College Park, MD, United States, (2)University of Maryland College Park, Department of Civil and Environmental Engineering, College Park, United States, (3)Oak Ridge National Laboratory, Environmental Sciences Division, Oak Ridge, TN, United States, (4)Nuclear Regulatory Commission, Washington, MD, United States, (5)U.S. Army Engineer R&D Center, Coastal & Hydraulics Laboratory (ERDC-CHL), Vicksburg, United States
Determining the Drivers of Flood Seasonality through Model Experiments (1199840)
Tara Troy, University of Victoria, Victoria, BC, Canada, Naresh Devineni, The City University of New York (City College), Department of Civil Engineering, New York, United States and Upmanu Lall, Columbia University, Earth and Environmental Engineering, New York, United States
