H121
Recent Advances in Large-Scale Hydrologic and Flood Modeling: Assessing and Predicting Extreme Floods
Session ID#: 248646
Session Description:
As extreme flood events get more intense, frequent, and prevalent, accurate and timely flood risk assessments become critical for emergency preparedness, developing mitigation strategies, and resilience planning. Recent advancements in coupled hydrologic, hydraulic, and machine learning models have significantly enhanced the characterization and prediction of flood risks. This session invites presentations demonstrating innovative large-scale, high-resolution modeling tools, and capabilities for analyzing extreme hydrologic events and their impacts. We welcome studies focusing on, but not limited to 1) Advances in coupled atmospheric, hydrologic, and hydraulic models for enhanced flood risk assessments 2) Prediction, projection, and characterization of extreme hydrologic events, including probable maximum precipitation and flood 3) Real-time streamflow or flood forecasting and validation 4) Computational advances in high-resolution hydrologic or inundation modeling 5) Machine learning, surrogate modeling, and hybrid data-model approaches improving predictions 6) Uncertainty quantification techniques leveraging multi-forcing, model, and parameter ensemble 7) Frameworks for integrated flood risk management
Co-Sponsor(s):
Index Terms:
1817 Extreme events [HYDROLOGY]
1821 Floods [HYDROLOGY]
1856 River channels [HYDROLOGY]
1860 Streamflow [HYDROLOGY]
Primary Convener: Sudershan Gangrade, Oak Ridge National Laboratory, Environmental Sciences Division, Oak Ridge, TN, United States
Conveners: Ganesh R Ghimire, Oak Ridge National Laboratory, Environmental Sciences Division, Oak Ridge, TN, United States, Shih-Chieh Kao, Oak Ridge National Laboratory, Environmental Science Division, Oak Ridge, United States and Mario Morales-Hernandez, I3A-University of Zaragoza, Zaragoza, Spain
Future Flood Characteristics in the Western United States (1850803)
Farshid Felfelani1, Andrew James Newman1, Andy Wood1, Amanda Stone2, Kathleen Holman2, Samantha Hartke3 and Kent Walker2, (1)NSF National Center for Atmospheric Research, Boulder, United States, (2)Bureau of Reclamation Denver, Denver, United States, (3)U.S. Army Corps of Engineers, Denver, United States
Flood Impacts Across Scales: A tale of a Multi-Method Approach (Invited) (1852383)
Gabriele Villarini1, Renato Amorim2, Manjaree Binjolkar2, Hanbeen Kim1, Taereem Kim3, Renato Amorim4, Sarah Maebius2, Alexander Michalek2 and Tianjiao Pu1, (1)Princeton University, Civil and Environmental Engineering & High Meadows Environmental Institute, Princeton, United States, (2)Princeton University, Civil and Environmental Engineering, Princeton, NJ, United States, (3)Princeton University, Civil and Environmental Engineering & High Meadows Environmental Institute, Princeton, NJ, United States, (4)University of Iowa, Iowa City, IA, United States
Detecting Spatially Consistent Trends in Sub-Hourly Extreme Rainfall Using a Neighborhood-Based Method (1863122)
Mr. Nischal Kafle1, Nadav Peleg2 and Claudio I Meier1, (1)University of Memphis, Department of Civil Engineering, Memphis, TN, United States, (2)ETH Zurich, Institute of Environmental Engineering, Zurich, Switzerland
Rapid flood mapping using low complexity terrain-based techniques (1875259)
Sunil Bista1, Subash Poudel2 and Rocky Talchabhadel2, (1)Jackson State University, Department of Civil and Environmental Engineering, Jackson, MS, United States, (2)Jackson State University, Department of Civil and Environmental Engineering, Jackson, United States
Real-time Flood Extent Forecasting Using an Encoder-decoder ConvLSTM Integrated with Data Assimilation (1876719)
Yue Li1, Hyongki Lee2, Tien Le Thuy Du2, Amirhossein Rostami1 and Hung-Hsien Wan2, (1)University of Houston, Department of Civil and Environmental Engineering, Houston, TX, United States, (2)University of Houston, Department of Civil and Environmental Engineering, Houston, United States
Toward Robust Large-scale Evaluations of Flood Inundation Predictions (Invited) (1880033)
Sagy Cohen1, Dipsikha Devi1, Dinuke Munasinghe2, Anupal Baruah1, Dan Tian1, Supath Dhital1 and Hongxing Liu1, (1)The University of Alabama, Department of Geography and the Environment, Tuscaloosa, AL, United States, (2)Department of Geography and Environment, University of Alabama, Tuscaloosa, United States
Event-based flood risk assessment based on a large ensemble climate dataset under climate change: A case study in the Tokachi river basin (1889609)
Takehiko Ito1, Hiroki Okachi2, Sadafumi Hasegawa3, Tsuyoshi Hoshino4 and Tomohito Yamada1, (1)Hokkaido University, Sapporo, Japan, (2)Hokkaido University, Sapporo City, Japan, (3)Hokakido University, Sapporo, Japan, (4)Civil Engineering Research Institute for Cold Region, Sapporo, Japan
Enhancing Riverine Flood Inundation Predictions with Artificial Intelligence (1895931)
Yogesh Bhattarai1, Ganesh R Ghimire2, Rocky Talchabhadel3 and Sanjib Sharma1, (1)Howard University, Department of Civil and Environmental Engineering, Washington, DC, United States, (2)Oak Ridge National Laboratory, Environmental Sciences Division, Oak Ridge, TN, United States, (3)Jackson State University, Department of Civil and Environmental Engineering, Jackson, United States
High-Resolution Climate-Hydrodynamic Modeling Considering Wetland Functions for Extreme Flood Events in the Passaic River Basin (1909533)
Sarawut Jamrussri1, Tomohiro Tanaka1, Kei Ishida2 and Yi-Chen Ethan Yang3, (1)Disaster Prevention Research Institute, Kyoto University, Kyoto, Japan, (2)Center for Water Cycle, Marine Environment, and Disaster Management, Kumamoto University, Kumamoto, Japan, (3)Department of Civil and Environmental Engineering, Lehigh University, Bethlehem, United States
Assessing Culvert Vulnerability to Floods and Flood induced Erosion and Debris Flow (1910179)
Sourav Mukherjee1, Devendra Man Amatya2, Sudhanshu Sekhar Panda3, Mariana Dobre4, Roger Lew4, Anna M Jalowska5 and Johnny Grace6, (1)USDA Forest Service, Center for Forested Wetlands Research, Cordesville, United States, (2)USDA Forest Service Southern Research Station, Cordesville, United States, (3)University of North Georgia, Institute for Environmental Spatial Analysis, Oakwood, United States, (4)University of Idaho, Department of Soil and Water Systems, Moscow, United States, (5)Environmental Protection Agency, Research Triangle Park, United States, (6)USDA Forest Service Southern Research Station, Tallahassee, FL, United States
High-resolution flood inundation maps across the contiguous United States under historical and pseudo-global warming scenarios (1911782)
Alexander Michalek1, Renato Amorim2, Donghui Li3, Manjaree Binjolkar1, Tianjiao Pu3, Gabriele Villarini3, James Done4 and Sudershan Gangrade5, (1)Princeton University, Civil and Environmental Engineering, Princeton, NJ, United States, (2)Princeton University, Civil and Environmental Engineering & High Meadows Environmental Institute, Princeton, NJ, United States, (3)Princeton University, Civil and Environmental Engineering & High Meadows Environmental Institute, Princeton, United States, (4)NSF National Center for Atmospheric Research, Mesoscale & Microscale Meteorology Laboratory, Boulder, United States, (5)Oak Ridge National Laboratory, Environmental Sciences Division, Oak Ridge, TN, United States
Enhancing Flood Sustainability in Florida through Explainable AI-Based Susceptibility Mapping (1912598)
Seyed Mostafa Biazar Seighalani1, Golmar Golmohammadi1, Kourosh Mohammadi Dr.2, Bhavan Voram3, Gurjoban Singh Tiwana1, Saba Shaghaghi Khajehdehi1 and Namrata Ghimire1, (1)University of Florida, Soil, Water and Ecosystem Sciences, Ona, United States, (2)HLV2K Engineering Limited, Mississauga, Canada, (3)university of Florida, Department of Computer Science, Gainesville, United States
Probabilistic Dam Break Flood Risk Mapping Using a Copula-Based Framework and GPU-Accelerated Hydrodynamic Model (1920657)
Shivakumar Balachandran1, Sudershan Gangrade2, Ganesh R Ghimire2, Shih-Chieh Kao3 and Jasim Imran4, (1)University of South Carolina Columbia, Columbia, United States, (2)Oak Ridge National Laboratory, Environmental Sciences Division, Oak Ridge, TN, United States, (3)Oak Ridge National Laboratory, Environmental Science Division, Oak Ridge, United States, (4)Univ South Carolina, Department of Civil and Environmental Engineering, Columbia, United States
High-Resolution Hydrodynamic Reconstruction of Hurricane Helene (2024) Flooding in the Southeastern United States (1922005)
Sudershan Gangrade1, Shih-Chieh Kao2, Ganesh R Ghimire3, Mario Morales-Hernandez4, Michael Kelleher5, Youngsung Kim6, Mariam Khanam1 and Matthew R Norman7, (1)Oak Ridge National Laboratory, Oak Ridge, TN, United States, (2)Oak Ridge National Laboratory, Environmental Science Division, Oak Ridge, United States, (3)Oak Ridge National Laboratory, Environmental Sciences Division, Oak Ridge, TN, United States, (4)I3A-University of Zaragoza, Zaragoza, Spain, (5)Oak Ridge National Laboratory, Computational Sciences and Engineering Division, Oak Ridge, United States, (6)Oak Ridge National Laboratory, Oak Ridge, United States, (7)Oak Ridge National Lab, Oak Ridge, TN, United States
Tiger-HLM: A GPU-Accelerated Distributed Hydrologic Model (1922664)
Manjaree Binjolkar1, Alexander Michalek1, Renato Amorim1, Donghui Li2, Sarah Maebius1, Tianjiao Pu2, Abhishek Biswas3, Stéphane Ethier4 and Gabriele Villarini2, (1)Princeton University, Civil and Environmental Engineering, Princeton, NJ, United States, (2)Princeton University, Civil and Environmental Engineering & High Meadows Environmental Institute, Princeton, United States, (3)Princeton University, Research Computing, Princeton, NJ, United States, (4)Princeton University, Princeton Plasma Physics Laboratory, Princeton, NJ, United States
Enhancing Fluvial Flood Inundation Mapping Through Stochastic Rating Curve Representation (1926538)
Niloufar Soheili, The City College of New York, Department of Civil Engineering, New York, United States, Shivakumar Balachandran, University of South Carolina, CIVIL AND ENVIRONMANTAL ENGINEERING, Columbia, United States, Mahdi Erfani, Scripps Institution of Oceanography, San Diego, United States and Mohammad Erfani, Center for Climate Systems Research, Columbia Climate School, Columbia University, New York, United States
Quantification of the Role of Internal Variability in Flood Inundation during Hurricane Ida (1927683)
Renato Amorim, Princeton University, Civil and Environmental Engineering & High Meadows Environmental Institute, Princeton, NJ, United States, Gabriele Villarini, Princeton University, Civil and Environmental Engineering & High Meadows Environmental Institute, Princeton, United States, Alexander Michalek, Princeton University, Civil and Environmental Engineering, Princeton, NJ, United States, Sofia Menemenlis, Princeton University, The Department of Geosciences, Princeton, NJ, United States and Gabriel Andres Vecchi, Princeton University, Department of Geosciences and The High Meadows Environmental Institute, Princeton, NJ, United States
High-Resolution Flood Inundation Mapping of U.S. Tribal Nations Under Current and Future Conditions: The Case of the Santee Sioux Nation (1935028)
Tianjiao Pu1, Gabriele Villarini1, Renato Amorim2, Donghui Li1, Sudershan Gangrade3, Martha Durr4 and Brandi Janssen5, (1)Princeton University, Civil and Environmental Engineering & High Meadows Environmental Institute, Princeton, United States, (2)Princeton University, Civil and Environmental Engineering & High Meadows Environmental Institute, Princeton, NJ, United States, (3)Oak Ridge National Laboratory, Environmental Sciences Division, Oak Ridge, TN, United States, (4)Nebraska Indian Community College, Macy, United States, (5)University of Iowa, Department of Occupational and Environmental Health, Iowa City, United States
Sub-Kilometer Simulation of Pluvial and Fluvial Flooding Events Using E3SM-RDycore (1936135)
Gautam Bisht1, Donghui Xu2, Jeffrey Johnson3, Jed Brown4, Matthew Knepley5, Mark F Adams6, Dongyu Feng1, Dalei Hao1, Jon Wolfe7, Zeli Tan2, Mukesh Kumar8, Peter Bogenschutz9 and Jishi Zhang10, (1)Pacific Northwest National Laboratory, Richland, United States, (2)Pacific Northwest National Laboratory, Richland, WA, United States, (3)Cohere Consulting, Seattle, United States, (4)Argonne National Laboratory, Argonne, United States, (5)University at Buffalo, Buffalo, NY, United States, (6)Lawrence Berkeley National Laboratory, Berkeley, United States, (7)Los Alamos National Laboratory, Los Alamos, United States, (8)University of Alabama, Civil, Construction and Environmental Engineering, Tuscaloosa, AL, United States, (9)Lawrence Livermore National Laboratory, Livermore, CA, United States, (10)Lawrence Livermore National Laboratory, Livermore, United States
Application of a Real-Time Data Assimilation System to Enhance Flood Forecasts in Japan (1954265)
Yingying LIU1, Kei Yoshimura1, Menaka Revel2 and Yuting Zhu3, (1)The University of Tokyo, Kashiwa, Japan, (2)University of Waterloo, Waterloo, Canada, (3)Tsinghua University, Shenzhen, China
A hierarchical Bayesian approach to understanding recent flash flood trends in the USA (1957732)
Fatemeh Yavari, The City University of New York (CCNY), Civil Engineering, New York, United States, Mohamed Abdelkader, University of Iowa, IIHR—Hydroscience & Engineering, Iowa City, United States, Hamid Moradkhani, The University of Alabama, Center for Complex Hydrosystems Research, Tuscaloosa, United States and Naresh Devineni, Department of Civil Engineering, The City College of the City University of New York, and CUNY-CREST, Department of Civil Engineering, New York, United States
A Scalable Approach for Maximizing Global Flood Model Resolution (1968937)
Hannah Hampson1, Elizabeth Perry2, Joseph Pucciarelli3, Callie McNicholas4, Matthew Woelfle5 and Justin Rogers1, (1)Jupiter Intelligence, San Mateo, United States, (2)Jupiter Intelligence, New York, United States, (3)Jupiter Intelligence, Boulder, United States, (4)Jupiter Intelligence, Inc., Seattle, United States, (5)Jupiter Intelligence, Inc., Boulder, United States
An Attention-Guided Deep Learning Model for High-Resolution Flood Inundation Prediction – A Proof of Concept (1971403)
Faria Nur1, Sudershan Gangrade2, Ganesh R Ghimire2, Shih-Chieh Kao3 and Alfred J Kalyanapu4, (1)Tennessee Technological University, Cookeville, United States, (2)Oak Ridge National Laboratory, Environmental Sciences Division, Oak Ridge, TN, United States, (3)Oak Ridge National Laboratory, Environmental Science Division, Oak Ridge, United States, (4)Tennessee Technological University, Cookeville, TN, United States
Global Sensitivity Analysis of Hydrodynamic Urban Flood Inundation Mapping and Modeling in a Coastal River Basin in the South United States (1975049)
Reza Saleh Alipour, University of Alabama, Civil, Construction, and Environmental Engineering, Tuscaloosa, United States, Junho Song, University of Alabama, Alabama Water Institute, Tuscaloosa, United States, Sudershan Gangrade, Oak Ridge National Laboratory, Environmental Sciences Division, Oak Ridge, TN, United States, James Halgren, The University of Alabama, Alabama Water Institute, Tuscaloosa, United States and Steven J Burian, Cooperative Institute for Research to Operations in Hydrology (CIROH), Alabama Water Institute, The University of Alabama, Tuscaloosa, AL, Alabama Water Institute, Tuscaloosa, United States
Solutions of Diffusion Wave Equation Using Meshless Radial Basis Function Collocation Method for Flood Routing (1976129)
Ismet Karakan, University of South Carolina Columbia, Columbia, SC, United States, Jani FATHIMA Jamal, University of South Carolina, CIVIL AND ENVIRONMANTAL ENGINEERING, Columbia, United States, Hanif Chaudhry, University of South Carolina Columbia, Columbia, United States and Jasim Imran, Univ South Carolina, Department of Civil and Environmental Engineering, Columbia, United States
Impact of Compound Flooding under Climate Extremes: A Case Study of East Boston (1976409)
Sami Shokrana, Massachusetts Institute of Technology, Center for Sustainability Science and Strategy, Cambridge, United States, Katerina Boukin, Massachusetts Institute of Technology, Civil and Environmental Engineering, Cambridge, MA, United States and Kenneth M Strzepek, Massachusetts Institute of Technology, Center for Sustainability Science and Strategy, Cambridge, MA, United States
Advances in Continental-Scale Flood Inundation Mapping and Prediction (1976844)
Carson Pruitt, NOAA Office of Water Prediction, National Water Center, Geo-Intelligence Division, Tuscaloosa, United States and Derek Giardino, Fernando Salas, Ryan Spies, Robert Hanna, Matt Luck, Greg Petrochenkov, Emily Deardorf, Ali Forghani, Hamideh H. Safa, Zahra Ghahremani
Beyond the Rain: A Scalable Framework for Urban Flood Risk Modeling and the Role of Drainage Infrastructure under Intensifying Storm Events (1981094)
Katerina Boukin, Massachusetts Institute of Technology, Civil and Environmental Engineering, Cambridge, MA, United States, Kenneth M Strzepek, Massachusetts Institute of Technology, Center for Sustainability Science and Strategy, Cambridge, MA, United States and Randolph Kirchain, Massachusetts Institute of Technology, Cambridge, United States
HEC-RAS 2D Emulation Using Sparse Gaussian Process Regression – Benchmarking New Approaches to Reduce the Computational Demand of Probabilistic Flood Modeling. (1982762)
Richard Passarelli1, Scott Lawson2, Rosemary Cyriac1, Mohammad Ghaneeizad1, Shubham Jain3, Maryam Pakdehi3, Jack Elsey4, Daniel Wilusz2, Mathew Mampara2, Sarada Kalikivaya1, David Rosa5 and Haden Smith6, (1)AtkinsRéalis, Alexandria, United States, (2)Dewberry, Fairfax, United States, (3)Michael Baker International, Katy, United States, (4)CDM Smith, Boston, United States, (5)FEMA Engineering Resources Branch, Washington, United States, (6)USACE Risk Management Center, Denver, United States
A Novel Global Flood Modeling Framework Powered by Cloud-Scalable HEC-RAS 2D Engine and Advanced Climate Forcings (1983244)
Jungho Kim, Marco Maneta, Michael Gomez, Abdullah Al, Minjae Kim, Bishwodeep Adhikari, Matt Lammers, Miguel Novo Villar, Ho Hsieh, Kyra Bryant, Arman Pouyaei, Chen Liang, Tsung-Lin Hsieh, Zac Flamig, Michael Amodeo and Edward Joseph Kearns, First Street, New York, United States
High-Resolution Flash Flood Forecasting in New Jersey: Bridging Prediction and Preparedness (1983824)
Efthymios Ioannis Nikolopoulos1, Sinan Rasiya Koya2, Yifan Wang3, Yaocheng Wu3 and Jie Gong3, (1)Rutgers University New Brunswick, Civil and Environmental Engineering, New Brunswick, NJ, United States, (2)University of Nebraska Lincoln, Civil and Environmental Engineering, Lincoln, NE, United States, (3)Rutgers University New Brunswick, Civil and Environmental Engineering, New Brunswick, United States
Advancing NOAA’s Near Real Time Flood Inundation Mapping Capabilities with Ripple1D and Flows2FIM (1993766)
Abdul Raheem Siddiqui1, Matthew Deshotel2, Scott Lawson3, Seth Lawler3, Bradford Bates1 and Roberto Gonzalez-Pita1, (1)Earth Resources Technology Inc, Laurel, United States, (2)Dewberry, Ashland, United States, (3)Dewberry, Fairfax, United States
Enhancing NOAA’s National Flood Inundation Mapping Evaluation System with Scalable Container Orchestration (1994191)
Dylan Bentley Lee1, Abdul Raheem Siddiqui1, Fernando Aristizabal1, Kevin Spurrier2, Roberto Gonzalez-Pita1 and Bradford Bates1, (1)Earth Resources Technology Inc, Laurel, United States, (2)Raytheon Company Silver Springs, Silver Spring, United States
Spatiotemporal Assessment of Flood Susceptibility Using Remote Sensing Indices and Random Forest Classification in Sunamganj District, Bangladesh (1998791)
Md. Rakibul Hasan1, Sabyasachi Paul2, Fahmida Sultana2, Sadia Nasrin Shara3, Sohanur Rahman Shuvo2 and Hridoy Saha3, (1)National Oceanographic And Maritime Institute (NOAMI), Dhaka, Bangladesh, (2)Urban and Rural Planning Discipline, Khulna University, Khulna, Bangladesh, (3)University of Dhaka, Dhaka, Bangladesh
