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Session Proposal: Where Flood Connects Us: Integrating Physical Models, Social Dimensions, and AI Innovations (AGU25)

H162
Where Flood Connects Us: Integrating Physical Models, Social Dimensions, and AI Innovations

Session ID#: 249241

Session Description:
Rapid urbanization and intensifying storms are escalating flood risks globally, demanding innovative, interdisciplinary solutions. This session invites researchers, practitioners, and stakeholders to advance holistic flood science by bridging physical, social, and technological domains—echoing AGU’s theme, “Where Science Connects Us.” We welcome contributions addressing the interconnected nature of flood systems across three themes: (1) integrated modeling of hydrologic, hydraulic, infrastructure, and socioeconomic systems; (2) compound flood impacts on vulnerable populations, infrastructure, and ecosystems; and (3) applications of AI and machine learning for improved flood prediction, assessment, and planning. We seek abstracts that present novel frameworks for: analyzing cascading impacts using coupled natural-human systems, applying AI in real-time forecasting and early warning, evaluating nature-based solutions, and incorporating community sensitivity into risk models. The session aims to foster cross-disciplinary dialogue and share emerging best practices for equitable, science-based adaptation strategies. Submissions from diverse geographic and institutional contexts are strongly encouraged.
Co-Sponsor(s):
  • A - Atmospheric Sciences
  • EP - Earth and Planetary Surface Processes
  • NH - Natural Hazards
  • SY - Science and Society
Index Terms:

1834 Human impacts [HYDROLOGY]
1847 Modeling [HYDROLOGY]
4303 Hydrological [NATURAL HAZARDS]
6309 Decision making under uncertainty [POLICY SCIENCES & PUBLIC ISSUES]
Primary Convener:  Alka Tiwari, The University of Texas at Austin, Bureau of Economic Geology, Department of Earth and Planetary Sciences, Austin, United States
Conveners:  Zhi Li, University of Oklahoma, Norman, United States, L. Ruby Leung, Pacific Northwest National Laboratory, Richland, WA, United States and Scott M Collis, Argonne National Laboratory, Lemont, IL, United States
 
Intersecting Social Vulnerability and Compound Flooding in Coastal U.S. Communities (1868697)
Mahjabeen Fatema Mitu1, Giulia Sofia2, Eleanor Shoreman Ouimet3 and Emmanouil N Anagnostou2, (1)University of Connecticut, Department of Civil and Environmental Engineering, Groton, CT, United States, (2)University of Connecticut, Department of Civil and Environmental Engineering, Storrs, United States, (3)University of Connecticut, Department of Anthropology, Storrs, United States
 
Urban Flood Intelligence in Forecasting,Mapping, and Resilience: A Synergetic Framework (1890152)
Jie Zhao, Yueli Chen, Qingsong Xu, Andrea Reimuth and Xiao Xiang Zhu, Technical University of Munich, Munich, Germany
 
FLAI: An AI-Powered Platform for Flood-Risk Communication (1893382)
Shenglin Li1, Michal Zajac1, Abel Andres Ramirez Molina1, Jiaqi Gong2, Fabricio Juarez1, Connor Barbaccia1, Connor Kulawiak1, Nathan Hubbell1, Caleb Erickson1, Spence Hanegan1 and Julian Garcia1, (1)The University of Alabama, Department of Computer Science, Tuscaloosa, United States, (2)University of Alabama, Department of Computer Science, Tuscaloosa, United States
 
A Machine Learning-Enabled Socio-Economic Vulnerability Assessment Integrated with the SYNXFLOW Hydrodynamic Flood Model in the UK Context (1900584)
Jagriti Jain, Indian Institute of Technology Roorkee, Department of Water Resources Development and Management, Roorkee, India, Xilin Xia, University of Birmingham, School of Engineering, Birmingham, United Kingdom and Deepak Khare, Indian Institute of Technology Roorkee, Water Resource Department and Mangement, Roorkee, India
 
Advancing Flood Susceptibility Prediction with Deep Learning in North Fork Kentucky River Basin, Eastern Kentucky (1902919)
Samir Pahari, Western Kentucky University, Bowling Green, KY, United States and Nahid D. Gani, Western Kentucky University, Earth, Environmental, and Atmospheric Sciences, Bowling Green, United States
 
Bridging the Global Warning Gap for Flash Floods: A Generalizable AI Framework for Real-Time Forecasting (Invited) (1913323)
Oleg Zlydenko, Rotem Mayo, Ido Zemach, Deborah Cohen and Oren Gilon, Google, Research, Tel Aviv, Israel
 
Chronicle – a Gemini constructed dataset of real world flood events from news (1913552)
Oleg Zlydenko, Rotem Mayo, Ido Zemach, Moral Bootbool, Deborah Cohen and Oren Gilon, Google, Research, Tel Aviv, Israel
 
Where Floods Connect Us: A Decade of Progress in Urban Flood Modeling and Water Infrastructure Advancements in Chicago, Illinois (Invited) (1917453)
Marcelo H Garcia, University of Illinois at Urbana Champaign, Civil and Environmental Engineering, Urbana, United States, Sun Young Park, University of Illinois Urbana Champaign, Civil and Environmental Engineering, Champaign, United States, Dr. Deanna A Hence, University of Illinois at Urbana Champaign, Climate, Meteorology and Atmospheric Sciences, Urbana, United States and Stephen W Nesbitt, University of Illinois at Urbana-Champaign, Climate, Meteorology and Atmospheric Sciences, Urbana, United States
 
Social Learning and Flood Adaptation via a Bayesian Agent-Based Model (1926089)
Erfan Amini, Center for Climate Systems Research, The Climate School, Columbia University, New York, United States, Malgosia Madajewicz, Columbia University, Center for Climate Systems Research, The Climate School, Palisades, United States and Vivek Srikrishnan, Cornell University, Ithaca, NY, United States
 
Weather Jiu Jitsu: Adaptive Chaos Control with Deep Learning of Atmospheric Dynamics to leverage the power of the atmospheric circulation with nudges to move or defuse storms and avert catastrophic flooding (Invited) (1926148)
Upmanu Lall1,2, Qin Huang3, Moyan Liu3, Hyun-Han Kwon4 and Yeongbin Kwon5, (1)Columbia University, Earth and Environmental Engineering, New York, United States, (2)Arizona State University, Water Institute, School of Complex Adaptive Systems, Tempe, United States, (3)Arizona State University, School of Complex Adaptive Systems, Tempe, AZ, United States, (4)Sejong University, Department of Civil and Environmental Engineering, Seoul, South Korea, (5)Seoul National University, Civil & Environmental Engineering, Seoul, South Korea
 
Toward disability-inclusive flood solution: a systematic literature review (1947477)
Jingyan Huang, University of New Hampshire Main Campus, Natural Resources & Earth Systems Science, Durham, NH, United States, Weiwei Mo, University of New Hampshire, Civil and Environmental Engineering, Durham, United States and Fei Han, University of New Hampshire Main Campus, Civil and Environmental Engineering, Durham, United States
 
Twin Monsoon Floods of 2024–2025 in Eastern Bangladesh: Integrating Forecasting Models, Local Impacts, and Regional Data Gaps (1959371)
Mohan Kumar Das1, Md. Awlad Hossain2, Sheikh Fahim Faysal Faysal Sowrav3, Dr. Md. Sazzad Hossain4, Samarendra Karmakar5, Puspendu Biswas Paul1, Jamal U Khan6, Maisha Farzana Methila7, AKM Saiful Islam8, Md. Shameem Hassan Bhuyian9, Fatima Akter7, Faruque Abdullah10, Shipa Rani Singha7, Md Minarul Hoque11, Toru Terao12, Arpita Roy Shawon13, Sifat Tanzil Ovi7, Nigomananda Biswas11, Khan Mohammad Ibtehal11, Sourav Bhowmik14, Syeda Tasneem Binta Haider15 and Md. Rakibul Hasan5, (1)National Oceanographic and Maritime Institute, Dhaka, Bangladesh, (2)University of Dhaka, Depatment of Applied Mathematics, Dhaka, Bangladesh, (3)Bangladesh Maritime University, Department of Oceanography & Hydrography, Dhaka, Bangladesh, (4)Bangladesh Water Development Board, Dhaka, Bangladesh, (5)National Oceanographic And Maritime Institute (NOAMI), Dhaka, Bangladesh, (6)CNRS/LIENSS, La Rochelle, France, (7)University of Dhaka, Department of Meteorology, Dhaka, Bangladesh, (8)Bangladesh University of Engineering and Technology, Institute of Water and Flood Management, Dhaka, Bangladesh, (9)Bangladesh Meteorological Department (BMD), Bangladesh, Dhaka, Bangladesh, (10)Marquette University, Milwaukee, WI, United States, (11)Bangabandhu Sheikh Mujibur Rahman Maritime University, Oceanography and Hydrography, Dhaka, Bangladesh, (12)Kagawa University, Kagawa, Japan, (13)University of Dhaka, Department of Geography and Environment, Dhaka, Bangladesh, (14)Bangladesh University of Engineering and Technology, Department of Physics, Dhaka, Bangladesh, (15)University of Nebraska Lincoln, High Plains Regional Climate Center and School of Natural Resources, Lincoln, United States
 
Depth-Based Urban Flood Modeling for Road Network Accessibility Analysis (1970149)
Shivam Priyadarshi, Central University of South Bihar, Geography, Gaya, India, Shilpi Priyadarshi, A.N. College, Patliputra University, Geography, Patna, India and Anjali Sinha, Ranchi University, Geography, Ranchi, India
 
AI-Powered End-to-End Simulation for Projecting Downscaled Extreme Precipitation, Flooding, and Infrastructure Resilience (1987208)
August Posch, Northeastern University, Boston, MA, United States, Raviraj Dave, Northeastern University, Civil and Environmental Engineering, Boston, MA, United States, Anne Haley, Kitware Inc., Clifton Park, United States, Aashish Chaudhary, Kitware Inc., Clifton Park, NY, United States and Auroop Ganguly, Northeastern University, Civil and Environmental Engineering, Boston, United States
 
Using Natural Language Processing to Reveal Coordination Gaps in Multi-Scale Government Flood Adaptation (1990528)
Isabella Tavarez1,2, Amy C Clement3, Brett F Sanders4,5, Sam Lindemann6, Kevin Larson Mohr1,2, Eva-Marie Martin4, Jochen E Schubert4, Michael C Sukop7,8 and Katharine J Mach1,2, (1)Rosenstiel School of Marine, Atmospheric, and Earth Science, University of Miami, Department of Environmental Science and Policy, Miami, United States, (2)Leonard and Jayne Abess Center for Ecosystem Science and Policy, University of Miami, Miami, United States, (3)Rosenstiel School of Marine, Atmospheric, and Earth Science, University of Miami, Department of Atmospheric Sciences, Miami, United States, (4)University of California Irvine, Department of Civil and Environmental Engineering, Irvine, United States, (5)University of California Irvine, Department of Urban Planning and Public Policy, Irvine, United States, (6)Harvard University, Department of Statistics, Cambridge, United States, (7)Florida International University, Earth and Environment, Miami, United States, (8)Institute of Environment, Florida International University, Miami, United States
 
Hydrologic and geochemical Impacts of Mountaintop Mining on Flood Severity in Eastern Kentucky (1990753)
Md Kibria1, Emelia Harris2 and Adam McKinney2, (1)Morehead State University, Department of Engineering Sciences, Morehead, KY, United States, (2)Morehead State University, Department of Biology and Chemistry, Morehead, United States
 
Flood Severity AI: Bridging Community Intelligence and AI for Flood Resilience (1997114)
Caroline Reed and Julia Kumari Drapkin, ISEECHANGE, New Orleans, United States
 
A Multisensor Framework for Understanding Hybrid Flood Events from Hurricane Helene (2024) (2002172)
Alka Tiwari, The University of Texas at Austin, Bureau of Economic Geology, Department of Earth and Planetary Sciences, Austin, United States and Dev Niyogi, University of Texas at Austin, Jackson School of Geosciences, Austin, United States
See more of: Hydrology
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