H029
Advancing Hydrologic Processes to Improve Flood Prediction
Session ID#: 250130
Session Description:
Floods are among the most devastating natural hazards, driven by complex and interrelated physical processes. These processes vary across catchments and seasons, making it critical to understand the unique drivers of flood events, including extreme rainfall, land use change, river dynamics, atmospheric conditions such as hurricanes, and human interventions. As natural variability reshapes flood behavior, advancing catchment-specific knowledge is essential for improving prediction and preparedness, including in under-resourced regions. This session invites contributions that enhance understanding of the physical processes behind flooding and show how improved process-scale insights can strengthen flood forecasting, impact assessment, and risk management. We welcome contributions in areas including, but not limited to: ● Advancements in understanding flood generation processes ● Incorporating physical knowledge into improving flood forecasting ● Physics-informed statistical or machine learning models. ● Studies on riverine, flash, coastal, urban, and hurricane-induced floods ● Innovative approaches for flood modeling in data-limited environments
Index Terms:
1817 Extreme events [HYDROLOGY]
1821 Floods [HYDROLOGY]
1834 Human impacts [HYDROLOGY]
1847 Modeling [HYDROLOGY]
Primary Convener: Amar Deep Tiwari, Michigan State University, Department of Civil and Environmental Engineering, East Lansing, MI, United States
Conveners: Nanditha J S, Princeton University, Civil and Environmental Engineering, Princeton, United States, Anukesh Krishnankutty Krishnankutty Ambika, Oak Ridge National Laboratory, Earth Science, Oak Ridge, TN, United States and Saran Aadhar, Indian Institute of Technology Jodhpur, Department of Civil & Infrastructure Engineering, Jodhpur, India
Student/Early Career Convener: Alka Tiwari, University of Texas at Austin, Department of Earth and Planetary Sciences, Jackson School of Geosciences, Austin, United States
High-Resolution Flood Assessment and Forecasting in the Great Lakes Basin using Hydrological-Hydrodynamic Models and Socioeconomic Indicators (1861293)
Amar Deep Tiwari1, Dr. Yadu Pokhrel1, Ayumi Fujisaki-Manome2, Yi Hong3, Lauren M Fry4 and Arezoo Rafieeinasab5, (1)Michigan State University, Department of Civil and Environmental Engineering, East Lansing, MI, United States, (2)University of Michigan, Cooperative Institute for Great Lakes Research, Ann Arbor, United States, (3)Cooperative Institute for Great Lakes Research, University of Michigan, Ann Arbor, United States, (4)University of Michigan, Ann Arbor, United States, (5)University Corporation for Atmospheric Research, Boulder, United States
Simulating Flood Dynamics with Agricultural and Grey Infrastructure in Japanese Watersheds (1866893)
Julien Eric Boulange1, Hiroki Minakawa2, Seiya Aihara2 and Takeo Yoshida3, (1)Tokyo University of Agriculture and Technology, Faculty of Agriculture, Tokyo, Japan, (2)National Agriculture and Food Research Organization (NARO), Institute of Rural Engineering, Tsukuba, Japan, (3)National Agriculture and Food Research Organization (NARO), Institute for Rural Engineering, Tsukuba, Japan
Utility of Flood Typing to Enhance Flood Frequency Analysis in the United States (1868078)
Upeakshika Bandara, Arizona State University, School of Sustainable Engineering and Built Environment, Tempe, AZ, United States and Giuseppe Mascaro, Arizona State University, School of Sustainable Engineering and the Built Environment, Tempe, AZ, United States
Foreseeing Rivers Prone to Extreme Floods from Everyday Hydrologic Dynamics (1868370)
Stefano Basso1, Hsing-Jui Wang2, Carina Haugen1, Ralf Merz3 and Larisa Tarasova4, (1)Norwegian University of Science and Technology, Trondheim, Norway, (2)NTU National Taiwan University, Taipei, Taiwan, (3)Helmholtz Centre for Environmental Research UFZ, Catchment Hydrology, Halle, Germany, (4)Helmholtz Centre for Environmental Research - UFZ, Catchment Hydrology, Halle (Saale), Germany
Evaluating the effects of climate change and cascade dams on flood frequency in the Mekong River basin using annual-maximum-series and peak-over-threshold methods (1871338)
Binh Quang Nguyen1, Sameh Kantosh1, Thanh Nhan Duc Tran2, Amar Deep Tiwari3, Menna Farag Ahmed1, Binh Van Doan4 and Venkataraman (Venkat) Lakshmi5, (1)Disaster Prevention Research Institute, Kyoto University, Kyoto, Japan, (2)University of Virginia, Civil and Environmental Engineering, Charlottesville, VA, United States, (3)Indian Institute of Technology Gandhinagar, Ahmedabad, 382, India, (4)Vietnamese-German University, Binh Duong, Vietnam, (5)University of Virginia, Civil and Environmental Engineering, Charlottesville, United States
Towards a global ML-based framework for uncovering flood drivers and enhancing flood prediction in data-limited environments (Invited) (1878078)
Louise J. Slater1, Boen Zhang1, Yinxue Liu2, Michel Wortmann1 and Simon Moulds3, (1)University of Oxford, School of Geography and the Environment, Oxford, United Kingdom, (2)Loughborough University, School of Architecture, Building and Civil Engineering, Oxford, United Kingdom, (3)University of Edinburgh, School of Geosciences, Edinburgh, United Kingdom
Using Rainfall-runoff Simulation Errors to Infer Bedrock Influence on Flood Response in Japanese Mountainous Catchments (1887858)
Sora Fugami, Kyoto University, Department of Civil and Earth Resources Engineering, Graduate School of Engineering, Kyoto, Japan and Yutaka Ichikawa, Kyoto University, Department of Urban Management, Graduate School of Engineering, Kyoto, Japan
How Storm Types Shape Rainfall: A Watershed-Scale Analysis of Dam Overtopping Events in the Eastern U.S. (1917394)
Hodo I. Orok, University of Illinois at Urbana-Champaign, Department of Climate, Meteorology and Atmospheric Sciences, Urbana, United States, Dr. Deanna A Hence, University of Illinois at Urbana Champaign, Climate, Meteorology and Atmospheric Sciences, Urbana, United States and Carolina A Bieri, University of Illinois at Urbana Champaign, Department of Atmospheric Sciences, Urbana, United States
Advancing Continental-Scale Hydrology Model Calibration Using Large-Sample Emulators across a Range of Model Complexity (Invited) (1956993)
Andrew W Wood1, Guoqiang Tang2, Mozhgan Askarzadehfarahani3, Naoki Mizukami3, Sean C Swenson3, Chanel Mueller4, Chris Frans5, Marketa McGuire6 and Brantley Thames4, (1)National Center for Atmospheric Research, CGD Laboratory, Boulder, United States, (2)Wuhan University, School of Water Resources and Hydropower Engineering, Wuhan, China, (3)NSF National Center for Atmospheric Research, Boulder, United States, (4)US Army Corps of Engineers, Headquarters, Washington DC, United States, (5)US Army Corps of Engineers, Seattle, United States, (6)Bureau of Reclamation Denver, Denver, CO, United States
A Copula-Based Statistical Framework for Compound Pluvial–Fluvial Flood Risk Assessment (1970928)
Ms. Achala Singh, PhD, Indian Institute of Technology Indore, Civil Engineering, Indore, India, Suyash Shukla, M.Tech, Indian Institute of Technology Indore, Civil Engineering, Indore, India and Priyank J. Sharma, Assistant Professor, Indian Institute of Technology Indore, Civil Engineering, Indore, India
Quantifying the Effects of Climate Change on Hydrological Extremes Using Coupled High-Resolution WRF-WRF-Hydro Simulations in South Korea (1988927)
Yaewon Lee1, Bomi Kim2, Jiwon Choi1, Yusuke Hiraga3, Jose Angelo Hokson3 and Seong Jin Noh4, (1)Kumoh National Institute of Technology, Department of Civil Engineering, Gumi, South Korea, (2)Kumoh National Institute of Technology, Gumi, South Korea, (3)Tohoku University, Department of Civil and Environmental Engineering, Sendai, Japan, (4)Kumoh National Institute of Technology, Civil Engineering, Gumi, South Korea
Analyzing the June 2024 Flood Event in Northwest Iowa: Challenges and Opportunities for Improved Warning Lead Times (2002791)
Mohamed Abdelkader, University of Iowa, IIHR—Hydroscience & Engineering, Iowa City, United States, Humberto J Vergara, PhD, University of Iowa, IIHR-Hydroscience & Engineering, Iowa City, United States, Vanessa Robledo, Escuela Ambiental, Facultad de Ingeniería, Universidad de Antioquia, Medellín, Colombia, Santiago Henao Gomez, University of Iowa, IIHR—Hydroscience & Engineering, Iowa City, IA, United States and Felipe Quintero, University of Iowa, Iowa Flood Center and IIHR-Hydroscience and Engineering, Iowa City, United States
