NH020
Recent Advances in Flood and Shallow Water Modeling

Session ID#: 158332

Session Description:
Modeling of floods due to hurricanes is an important and difficult challenge. Society requires accurate and trustworthy models such that governments and individuals can make well-informed decisions in their response. The scale on which these events occur leads to significant challenges which can only be solved using numerical models. Hence, applicable numerical modeling frameworks must operate at large scales to accurately account for deep ocean effects  while at the same time providing high resolution of features such as rivers and estuaries. The development of such a modeling framework requires collaboration across engineering, computer science, mathematics, hydrology, etc. to leverage domain specific knowledge with efficient and appropriate numerical methodologies. We invite contributions from all aspects of modeling floods and shallow water flows in the floodplain, coastal waters, and oceanic waters. We particularly emphasize focused modeling efforts for compound flooding events and those incorporating novel techniques such as machine learning.
Index Terms:

4303 Hydrological [NATURAL HAZARDS]
4313 Extreme events [NATURAL HAZARDS]
4316 Physical modeling [NATURAL HAZARDS]
4319 Spatial modeling [NATURAL HAZARDS]

Primary Convener:  Eirik Valseth, The University of Texas at Austin, The Oden Institute for Computational Engineering and Sciences, Austin, TX, United States
Conveners:  Clint Dawson, University of Texas at Austin, Aerospace Engineering & Engineering Mechanics, Austin, TX, United States, Ethan Kubatko, Ohio State University Main Campus, Civil, Environmental & Geodetic Engineering, Columbus, United States and Joannes J Westerink, Univ Notre Dame, Notre Dame, IN, United States
Student/Early Career Convener:  Eirik Valseth, The University of Texas at Austin, The Oden Institute for Computational Engineering and Sciences, Austin, TX, United States
 
Subgrid Correction of Storm Surge Modeling in Orthogonal Curvilinear Coordinates (1046655)
Haoran Sun1, Damrongsak Wirasaet2, Joel Casey Dietrich3, Johnathon Woodruff4, Yuepeng Li5, Andrew Kennedy1 and Diogo Bolster6, (1)University of Notre Dame, Notre Dame, United States, (2)University of Notre Dame, Notre Dame, IN, United States, (3)North Carolina State University Raleigh, Raleigh, NC, United States, (4)North Carolina State University, Raleigh, United States, (5)FIU-IHRC, Miami, FL, United States, (6)University of Notre Dame, Civil and Environmental Engineering and Earth Sciences, Notre Dame, United States
 
A semi-automated setup and calibration process for a cloud-based large-scale compound flood modeling system (1053538)
Yi Liu, Zhuo Liu, Sam Lamont, Yu Zhang, Feyera Hirpa, Hoda El Safty, Liping Liu, Ting Li, Yawen Shen, Shabaz Patel and Brett Baker, One Concern, Inc., Menlo Park, CA, United States
 
Storm Surge Hindcasting Studies Using CYGNSS (1064203)
Mohammad Al-Khaldi, University Corporation for Atmospheric Research, Boulder, CO, United States, Joel Johnson, Ohio State University, Department of Electrical and Computer Engineering, Columbus, United States, Stephen J Katzberg, Retired, Washington, DC, United States, Younghun Kang, The Ohio State University, Civil Environmental and Geodetic Engineering, Columbus, United States and Ethan Kubatko, Ohio State University Main Campus, Civil, Environmental & Geodetic Engineering, Columbus, United States
 
Fast GP Estimation for In-situ Inference of Large Scale Climate Modeling with Statistical Machine Learning (1067432)
Nishant Panda1, Divya Banesh2, Saikat Dey2, Ayan Biswas2, Luke Van Roekel3, Diane Oyen4, Nathan M Urban1, Michael Grosskopf5, Jonathan D Wolfe1 and Earl C Lawrence6, (1)Los Alamos National Laboratory, Los Alamos, NM, United States, (2)Los Alamos National Laboratory, Los Alamos, United States, (3)Los Alamos National Laboratory, Fluid Dynamics and Solid Mechanics Group, Los Alamos, United States, (4)Los Alamos National Laboratory, CCS-3, Los Alamos, United States, (5)Los Alamos National Laboratory, CCS-6, Los Alamos, United States, (6)Los Alamos National Lab, Los Alamos, NM, United States
 
New modeling points to a million people at risk of flooding in Los Angeles, vastly more than suggested by FEMA maps. How could that happen? (1076045)
Brett F Sanders1, Daniel Kahl1, Jochen E Schubert2 and Katharine J. Mach3, (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, (3)University of Miami, Department of Environmental Science and Policy, Rosenstiel School of Marine, Atmospheric, and Earth Science; Leonard and Jayne Abess Center for Ecosystem Science and Policy, Miami, United States
 
Generation of Wind and Pressure Fields by Deep Learning for Efficient Storm Surge Modeling (1077859)
Iyan E. Mulia, RIKEN, Wako, Japan, Naonori Ueda, RIKEN Center for Advanced Intelligence Project, Tokyo, Japan and Takemasa Miyoshi, RIKEN Center for Computational Science, Kobe, Japan
 
Modeling of Storm-induced Surge and Flooding from Hurricane Harvey in 2017 (1088956)
Wonhyun Lee, University of Texas at Austin, Austin, United States, Alexander Y Sun, University of Texas at Austin, Austin, TX, United States, Bridget R Scanlon, University of Texas at Austin, Bureau of Economic Geology, Jackson School of Geosciences, Austin, TX, United States and Clint Dawson, University of Texas at Austin, Aerospace Engineering & Engineering Mechanics, Austin, TX, United States
 
An Automated Cloud-Based Flood Model Preprocessing Workflow (1115094)
Elizabeth Perry1, Justin Rogers2 and Hannah Hampson1, (1)Jupiter Intelligence, New York, United States, (2)Jupiter Intelligence, San Mateo, United States
 
Multivariate Flood Fragility Models for Homogeneous Earthen USACE Levees (1151851)
Lauren Adams1, Mehrzad Rahimi2, Abdollah Shafieezadeh1 and Ethan Kubatko1, (1)Ohio State University Main Campus, Civil, Environmental & Geodetic Engineering, Columbus, United States, (2)Rice University, Department of Civil and Environmental Engineering, Houston, United States
 
Modeling of Future Flood Risks with Sea Level Rise and Mitigation Measures: A Case Study in West Haven, CT, USA (1152530)
Chang Liu1, Yaprak Onat1, Caterina Massidda2, John Truscinski3 and James O'Donnell4, (1)University of Connecticut, Connecticut Institute for Resilience & Climate Adaptation (CIRCA), Groton, CT, United States, (2)University of Connecticut, Connecticut Institute for Resilience & Climate Adaptation (CIRCA), Groton, United States, (3)University of Connecticut, Connecticut Institute for Resilience and Climate Adaptation (CIRCA), Groton, United States, (4)University of Connecticut, Connecticut Institute for Resilience and Climate Adaptation, Groton, CT, United States
 
Advanced flood inundation modeling skills: Improved boundary conditioning and its interconnection with model parameters (1154745)
Keighobad Jafarzadegan1, Hamid Moradkhani2 and Nazifeh Oruc2, (1)The University of Alabama, Center for Complex Hydrosystems Research, Tuscaloosa, AL, United States, (2)The University of Alabama, Center for Complex Hydrosystems Research, Tuscaloosa, United States
 
Dissipation Mechanisms in an Unstructured Global Tidal Model (1166440)
Joannes J Westerink, University of Notre Dame, Department of Civil and Environmental Engineering and Earth Sciences, Notre Dame, United States, Coleman Blakely, University of Notre Dame, CEEES, Notre Dame, IN, United States, María Teresa Contreras Vargas, University of Notre Dame, Department of Civil & Environmental Engineering & Earth Sciences, Notre Dame, IN, United States, Guoming Ling, University of Notre Dame, Department of Civil and Environmental Engineering and Earth Sciences, Notre Dame, IN, United States, Damrongsak Wirasaet, University of Notre Dame, Notre Dame, IN, United States, William Pringle, University of Notre Dame, South Bend, United States, Edward Payson Myers III, NOAA, NOS/OCS, Silver Spring, MD, United States, Saeed Moghimi, NOAA, Silver Spring, United States, Gregory N Seroka, NOAA National Ocean Service, Silver Spring, United States, Yuji Funakoshi, University Corporation for Atmospheric Research, Boulder, MD, United States and Lei Shi, NOAA NOS/OCS/CSDL/MMAP, Silver Spring, United States
 
Calibration and Validation of the Coastal Storm Modeling System (CSTORM-MS) for the Louisiana Coast (1171236)
Fatima Bukhari1, Christopher Massey2, Mary A Bryant3, Norberto Carlos Nadal Caraballo4 and Margaret B Owensby4, (1)U.S. Army Engineers Research and Development Center, Coastal and Hydraulics Laboratory, Vicksburg, United States, (2)U.S. Army Engineers Research and Development Center, Coastal and Hydraulics Laboratory, Vicksburg, MS, United States, (3)Coastal and Hydraulics Laboratory, Vicksburg, MS, United States, (4)US Army Engineer Research and Development Center, Coastal & Hydraulics Laboratory, Vicksburg, United States
 
An Overview of a Multi-Agency Modeling Effort to Quantify Future Conditions in the Great Lakes (1174220)
Margaret B Owensby1, Thomas C Massey1, Robert E Jensen1, Norberto Carlos Nadal Caraballo1, Madison Yawn1, David Bucaro2, Johnna Potthoff2 and Kaitlyn McClain2, (1)US Army Engineer Research and Development Center, Coastal & Hydraulics Laboratory, Vicksburg, United States, (2)US Army Corps of Engineers, Chicago District, Chicago, United States
 
Propagating Uncertainty through GEFS-Enabled Global ESTOFS: Assessing Machine-Learning and Finite-Element-based Frameworks (1178172)
Albert Cerrone, University of Notre Dame, Civil & Environmental Engineering & Earth Sciences, Notre Dame, United States, Benjamin Pachev, University of Texas at Austin, Austin, United States, Guoming Ling, University of Notre Dame, Department of Civil and Environmental Engineering and Earth Sciences, Notre Dame, IN, United States, Clint Dawson, University of Texas at Austin, Institute for Computational Engineering and Sciences, Department of Aerospace Engineering and Engineering Mechanics, Austin, TX, United States and Joannes J Westerink, Univ Notre Dame, Notre Dame, IN, United States
 
Improving and optimizing wetting and drying algorithms for finite element modeling of coastal flooding with ADCIRC (1191179)
Dylan Wood, University of Notre Dame, Notre Dame, United States, Joannes J Westerink, Univ Notre Dame, Notre Dame, IN, United States, Damrongsak Wirasaet, University of Notre Dame, Notre Dame, IN, United States, Rick Luettich, University of North Carolina at Chapel Hill, Institute of Marine Sciences, Morehead City, United States and Shintaro Bunya, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
 
Application and Analysis of a Parametric Rainfall Model in a Hurricane Storm Surge Model (1193403)
Mackenzie Hudson, Ohio State University Main Campus, Columbus, OH, United States, Ethan Kubatko, Ohio State University Main Campus, Civil, Environmental & Geodetic Engineering, Columbus, United States and Younghun Kang, The Ohio State University, Civil Environmental and Geodetic Engineering, Columbus, United States
 
Development and application of a multidimensional hydrodynamic model and supporting mesh generation tool (1195333)
Younghun Kang and Ethan Kubatko, Ohio State University Main Campus, Civil, Environmental & Geodetic Engineering, Columbus, United States
 
Sediment Entrainment by Shallow Mass Flows Over Sloped Topography (1198280)
Colton Conroy, Southern Methodist University, Dallas, TX, United States and David L George, USGS Cascades Volcano Observatory, Vancouver, WA, United States
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