H088
Recent Advances in Large-Scale High-Resolution Hydrologic and Flood Modeling and Hydroclimatic Extremes Assessment
Session ID#: 157609
Session Description:
Accurate and timely flood risk quantification is critical for decision-makers for emergency preparedness and flood mitigation planning efforts. The magnitude and frequency of extreme flood events are projected to intensify under dynamic environmental factors such as changes in climate and land use land cover. Recent advances in hydrologic, hydraulic, and hydrodynamic models and their coupling have enabled a better understanding and characterization of these elevated flood risks. This session invites presentations showcasing the use of large-scale, high-resolution modeling tools to characterize past and future changes in hydroclimatic extremes and their associated impacts. We welcome studies focusing on but not limited to, prediction, projection, and characterization of rare hydrologic events; applications relevant to operational flood forecasting; computational challenges associated with high-resolution hydrologic or flood modeling; uncertainty quantification using multi-forcing, model, and parameter ensemble; and frameworks for integrated flood risk management.
Index Terms:
1807 Climate impacts [HYDROLOGY]
1817 Extreme events [HYDROLOGY]
1821 Floods [HYDROLOGY]
1860 Streamflow [HYDROLOGY]
Primary Convener: Sudershan Gangrade, Oak Ridge National Laboratory, Environmental Sciences Division, Oak Ridge, TN, United States
Conveners: Ganesh R Ghimire1, Shih-Chieh Kao1 and Mario Morales-Hernandez2, (1)Oak Ridge National Laboratory, Environmental Sciences Division, Oak Ridge, TN, United States(2)University of Zaragoza, Zaragoza, Spain
Towards the development of a high-resolution historical flood inundation reanalysis dataset for the conterminous United States (1075481)
Sudershan Gangrade1, Ganesh R Ghimire1, Shih-Chieh Kao1, Mario Morales-Hernandez2, Michael Kelleher3 and Alfred J Kalyanapu4, (1)Oak Ridge National Laboratory, Environmental Sciences Division, Oak Ridge, TN, United States, (2)University of Zaragoza, Zaragoza, Spain, (3)University of Exeter, Exeter, EX4, United Kingdom, (4)Tennessee Technological University, Cookeville, TN, United States
Towards high-resolution urban flood forecasting: Sensitivity to spatiotemporal resolution of extreme rainfall events on drainage infrastructure performance in Chicago, Illinois (1088497)
Sun Young Park1, Yifan He2, Andrew Waratuke3 and Marcelo H Garcia2, (1)University of Illinois at Urbana Champaign, Civil and Environmental Engineering, Urbana, IL, United States, (2)University of Illinois at Urbana Champaign, Civil and Environmental Engineering, Urbana, United States, (3)University of Illinois at Urbana Champaign, Ven Te Chow Hydrosystems Lab, Urbana, United States
A New Approach for Saint-Venant Simulation in Large-Scale River Network: Comparing an Open-Source Parallel Computing Numerical Model with Conventional Saint-Venant Models in Texas River Basins (1100283)
Cheng-Wei Yu1, Edward Davis Tiernan2, Sazzad Sharior2, Gerardo Riano2, Eric Jenkins2, Christopher Brashear3 and Ben R Hodges2, (1)National Taiwan University, Taipei, Taiwan, (2)University of Texas at Austin, Austin, TX, United States, (3)University of Texas at Arlington, Arlington, TX, United States
Development of debris flows forecasting system for the mountains of Central Asia by application of ecPoint Rainfall product (1109485)
Gavkhar Mamadjanova1,2, Maria Shahgedanova1 and Fatima Maria Pillosu1,3, (1)University of Reading, Department of Geography and Environmental Science, Reading, United Kingdom, (2)Hydrometeorological Research Institute, Center of Hydrometeorological Service of the Republic of Uzbekistan (Uzhydromet), Tashkent, Uzbekistan, (3)European Center for Medium-Range Weather Forecasts, Forecast Department, Reading, United Kingdom
Rapid, Lagrangian Modeling of 2D Flooding: A Rivulet-Based Approach (1116720)
Corinne Roth1, Brent Daniel2, Cynthia L Rakowski3, Timothy N McPherson3 and Dave Judi3, (1)Pacific Northwest National Laboratory, Richland, United States, (2)Pacific Northwest National Laboratory, Earth Systems Predictability and Resiliency, Richland, WA, United States, (3)Pacific Northwest National Laboratory, Richland, WA, United States
Combining LSTM and physically-based models for global-scale streamflow prediction (1120020)
Ian P Davies, Jupiter Intelligence, Seattle, United States, Galen Yacalis, Jupiter Intelligence, San Mateo, CA, United States, Hannah Hampson, Jupiter Intelligence, New York, United States, Marco Maneta, Jupiter Intelligence, San Mateo, United States and Stephan R Sain, Jupiter Intelligence, Boulder, United States
Assessing the Impact of Climate Change on Flooding in Highly Urbanized Bagmati River Basin, Nepal (1127894)
Bardan Dangi1, Sunil Bista2, K.N. Dulal3 and Bikesh Kasula1, (1)Pulchowk Campus, IOE, TU, Civil Engineering, Lalitpur, Nepal, (2)Pulchowk Campus, Institute of Engineering, Tribhuvan University, Lalitpur, Nepal, (3)HillSide College of Engineering, PU, Kathmandu, Nepal
Performance of Height Above Nearest Drainage (HAND) Model Compared to 2D Hydraulic Models for Flood Assessment (1164701)
Navin Tony Thalakkottukara1, Melanie K. Watkins2, Jobin Thomas1, Benjamin C Holland2 and Thomas Oommen3, (1)Michigan Technological University, Geological and Mining Engineering and Sciences, Houghton, MI, United States, (2)Michigan Technological University, Civil, Environmental and Geospatial Engineering, Houghton, United States, (3)Michigan Technological University, Geological and Mining Engineering and Sciences, Houghton, United States
A scalable, cloud-based modeling framework for global-scale flood risk assessment (1168468)
Marco Maneta1, Fariborz Daneshvar1, Rahul Dhakal1, Hannah Hampson2, Jared Oyler3, Elizabeth Perry2, Tarandeep Singh Kalra2, Luke Madaus4, Hillary A Scannell1, Stephan R Sain4 and Justin Rogers1, (1)Jupiter Intelligence, San Mateo, United States, (2)Jupiter Intelligence, New York, United States, (3)Jupiter Intelligence, State College, United States, (4)Jupiter, Boulder, United States
CloudRIFT - an Automatic Hydrodynamic Flood Modeling System on Azure (1172328)
Xue Li1, Tao Fu2, John J Garza3 and Dave Judi1, (1)Pacific Northwest National Laboratory, Richland, WA, United States, (2)Pacific Northwest National Laboratory, EED/Hydrology, Richland, WA, United States, (3)Pacific Northwest National Laboratory, Richland, United States
Future floods and changing flood-producing mechanisms across the Delaware River Basin (1178691)
Ning Sun1, Mark S Wigmosta2, Zhaoqing Yang2, Hisham Eldardiry1, Mithun Deb3, Taiping Wang3 and Dave Judi2, (1)Pacific Northwest National Laboratory, Energy and Environment Directorate, Richland, WA, United States, (2)Pacific Northwest National Laboratory, Richland, WA, United States, (3)Pacific Northwest National Laboratory, Seattle, United States
Land Use Land Cover Hydrologic Performance of the National Water Model Retrospective (Invited) (1181065)
Steven J Burian1, Ryan Johnson2, James Halgren2 and Bibek Acharya3, (1)University of Alabama, Alabama Water Institute, Tuscaloosa, AL, United States, (2)University of Alabama, Alabama Water Institute, Tuscaloosa, United States, (3)University of Utah, Salt Lake City, UT, United States
