H028
Advancing Hydrologic Modeling and Prediction Using Large-Domain Meteorological and Hydrologic Datasets
Session ID#: 247259
Session Description:
As observing infrastructure and computational capabilities improve, numerous large-domain datasets are continuously developed based on data from stations, remote sensing, and climate models. The development of new data products plays a vital role in supporting hydrologic modeling and in improving operational predictions for hydrologic extremes. However, existing datasets still face problems of inadequacy and/or inaccuracy, especially in remote areas. The uncertainty quantification of large-domain datasets is still in its infancy, and is particularly needed under a changing climate. We invite contributions including but are not limited to following areas: (1) Development of large-domain meteorological and hydrologic datasets; (2) Application of large-domain or large-sample datasets in hydrologic model preparation, calibration, assimilation, forecast, and prediction; (3) Application of artificial intelligence to gain insights from extensive datasets and models; (4) Data uncertainty quantification and the use of probabilistic/ensemble datasets in hydrologic modeling and prediction.
Co-Sponsor(s):
Index Terms:
1805 Computational hydrology [HYDROLOGY]
1816 Estimation and forecasting [HYDROLOGY]
1847 Modeling [HYDROLOGY]
1873 Uncertainty assessment [HYDROLOGY]
Primary Convener: Guoqiang Tang, Wuhan University, School of Water Resources and Hydropower Engineering, Wuhan, China
Conveners: Hongli Liu, University of Alberta, Department of Civil and Environmental Engineering, Edmonton, AB, Canada, Martyn P Clark, University of Calgary, Department of Civil Engineering, Schulich School of Engineering, Calgary, AB, Canada and Andy Wood, NSF National Center for Atmospheric Research, Boulder, United States
Predicting runoff across 4641 small catchments using the improved HBV-PML model constrained with remote sensing evapotranspiration (Invited) (1849157)
Yongqiang Zhang1, Haoshan Wei Sr2, Zhenwu Xu3 and Qi Huang3, (1)Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Key Laboratory of Water Cycle and Related Land Surface Processes, Beijing, China, (2)Institute of Geographic Sciences and Natural Resources Research, Beijing, China, (3)Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing, China
Can More Detailed Geological Maps Improve the Parameterization of Hydrological Models in Large-Sample Studies? (1849820)
Thiago Victor Medeiros do Nascimento1,2, Julia Rudlang3, Sebastian Gnann4, Jan Seibert1, Markus Hrachowitz5 and Fabrizio Fenicia2, (1)University of Zurich, Zurich, Switzerland, (2)EAWAG Swiss Federal Institute of Aquatic Science and Technology, Duebendorf, Switzerland, (3)Delft University of Technology, Department of Water Management, Faculty of Civil Engineering and Geosciences, Delft, Netherlands, (4)University of Freiburg, Chair of Hydrology, Faculty of Environment and Natural Resources, Freiberg, Germany, (5)Delft University of Technology, Faculty of Civil Engineering and Geosciences, Department of Water management, Delft, Netherlands
Time-Varying Streamflow and Nonlinear Dynamics Dataset for the United States (1850678)
Krzysztof Raczynski, Mississippi State University, Geosystems Research Institute, Mississippi State, MS, United States, John Harrison Cartwright, Mississippi State University, Geosystems Research Institute, Mississippi State, United States and Katarzyna Grala, Mississippi State University, Mississippi State, United States
Leveraging Emergent Constraints to Reduce Uncertainty in Future Compound Drought and Heatwave Events Across Mainland China (1854974)
Mengyu Wu1, Dunxian She2, Qin Zhang3 and Jun Xia1, (1)Wuhan University, State Key Laboratory of Water Resources Engineering and Management, Wuhan, China, (2)Wuhan University, School of Water Resources and Hydropower Engineering, Wuhan, China, (3)Changjiang River Scientific Research Institute, Changjiang Water Resources Commission, Wuhan, China
Identifying Dominant Hydrologic Processes Across Continental Landscapes Using Hydrologic Signatures (1865463)
Ryoko Araki, University of California Santa Barbara, Department of Geography, Santa Barbara, CA, United States; San Diego State University, Department of Geography, San Diego, United States, Anne Holt, San Diego State University, San Diego, United States, John Christopher Hammond, U.S. Geological Survey, Maryland-Delaware-DC Water Science Center, Catonsville, United States, Admin Husic, PhD, Virginia Tech, Department of Civil and Environmental Engineering, Manassas, United States and Hilary K McMillan, San Diego State University, Department of Geography, San Diego, CA, United States
Evaluation of High-resolution Meteorological Data Products using Flux Tower Observations Across Brazil (1867313)
Jamie Brown1,2, Rafael Rosolem2, Ross A Woods2, Debora Regina Roberti3 and Humberto R da Rocha4, (1)Hydrology.UK, Environmental Hydrology, Cumbria, United Kingdom, (2)University of Bristol, Civil Engineering, Bristol, United Kingdom, (3)Federal University of Santa Maria, Department of Physics, Santa Maria, Brazil, (4)University of Sao Paulo, Institute of Astronomy, Geophysics and Atmospheric Sciences, Sao Paulo, Brazil
Machine Learning-Based Reconstructions of Historical Daily and Monthly Runoff: A Case Study of the Laurentian Great Lakes Basin (1873116)
Rohini S Gupta, Cornell University, Biological and Environmental Engineering, Ithaca, NY, United States, Sungwook Wi, Cornell University, Ithaca, NY, United States and Scott Steinschneider, Cornell University, Ithaca, United States
What Controls Global Runoff Sensitivity? (1878244)
PEI Xue1, Dominick Spracklen2 and Joseph Holden1, (1)University of Leeds, School of Geography, water@leeds, Leeds, United Kingdom, (2)University of Leeds, School of Earth and Environment, Leeds, United Kingdom
Applying the FAIR eWaterCycle for Multi-Model Any-Catchment Climate Change Impact Assessments with CMIP and CAMELS/CARAVAN data (1880725)
Rolf Hut1, Bart Schilperoort2, Wouter R Berghuijs3, Mark Melotto1, Nick Van De Giesen4 and Dr. Caitlyn A Hall5, (1)Delft University of Technology, Water Management, Delft, Netherlands, (2)Netherlands eScience Center, Amsterdam, Netherlands, (3)Vrije Universiteit Amsterdam, Amsterdam, Netherlands, (4)Delft University of Technology, Faculty of Civil Engineering and Geosciences, Delft, Netherlands, (5)Arizona State University, Tempe, United States
Intensifying Flood Occurrence in the Nile Basin Under 21st-Century Climate Variability (1886531)
Hesham Elhaddad1, Mohamed Sultan2, Eugene Yan3, Thanh Nhan Duc Tran4, Hugo E. Torres-Uribe3 and Hadi Karimi2, (1)Western Michigan University, Department of Geological and Environmental Sciences, Kalamazoo, United States, (2)Western Michigan University, Department of Geological and Environmental Sciences, Kalamazoo, MI, United States, (3)Argonne National Laboratory, Argonne, United States, (4)University of Virginia, Civil and Environmental Engineering, Charlottesville, VA, United States
Comparing Multi-Model Approaches to Simulate Streamflow Across the Contiguous USA (1894047)
Cyril Thebault1, Wouter Knoben2, Nans Addor3 and Martyn P Clark1, (1)University of Calgary, Department of Civil Engineering, Schulich School of Engineering, Calgary, AB, Canada, (2)University of Calgary, Department of Civil Engineering, Schulich School of Engineering, Calgary, Canada, (3)Fathom, Bristol, United Kingdom
From Gauged to Ungauged: A Probabilistic Approach to Regionalize Hydrological Model Parameters (1899969)
Nicolas Vasquez1, Cyril Thebault1, Ignacio Aguirre1, Darri Eythorsson1, Wouter Knoben2, Mohamed Moghairib1, Kasra Keshavarz1, Andy Wood3,4 and Martyn P Clark1, (1)University of Calgary, Department of Civil Engineering, Schulich School of Engineering, Calgary, AB, Canada, (2)University of Calgary, Department of Civil Engineering, Schulich School of Engineering, Calgary, Canada, (3)Colorado School of Mines, Civil and Environmental Engineering, Golden, CO, United States, (4)National Center for Atmospheric Research, CGD Laboratory, Boulder, CO, United States
High-Resolution Flood Inundation Forecasting Using GPU-Accelerated Hydrologic-Hydrodynamic Modeling: Application to Houston, Texas (1920678)
Manjaree Binjolkar1, Renato Amorim1, Donghui Li2, Tianjiao Pu2, Alexander Michalek1 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
Catchment Specific Controls on Streamflow Simulation in Multi-Model Hydrological Assessments (1923955)
Kunal Bhardwaj, Clemson University, Glenn Department of Civil Engineering, Clemson, SC, United States, Prakash Khedun, Clemson University, Department of Agricultural Sciences, Clemson, United States and Ashok K Mishra, Zachry Department of Civil and Environmental Engineering, Texas A&M University, College Station, United States
Functional Classification of 80,000 Catchments: A Framework for Hydrologic Model Use and Regionalization (1925882)
Ali Ameli, University of British Columbia, Department of Earth, Ocean and Atmospheric Sciences, Vancouver, BC, Canada, Hamed Sharif, University of British Columbia, Department of Earth, Ocean, and Atmospheric Sciences, Vancouver, BC, Canada and Jeffrey McDonnell, University of Saskatchewan, School of Environment and Sustainability, Global Institute for Water Security, Saskatoon, SK, Canada
Enhancing Land Surface Fluxes in Hyper-resolution LSMs with Satellite Land Surface Temperature (1928148)
Onur Güngör Şahin1,2, Adnan Dehghani1, Orhan Gündüz3 and Noemi Vergopolan1, (1)Rice University, Earth, Environmental and Planetary Sciences, Houston, United States, (2)Izmir Institute of Technology, Department of International Water Resources, Izmir, Turkey, (3)Izmir Institute of Technology, Department of Environmental Engineering, İzmir, Turkey
Integrating Diverse Meteorological Inputs for Machine Learning-Based SWE Estimation in Complex Catchments (1936978)
Emily Golitzin1, Ryan Johnson2, Dane Liljestrand3, Ethan Ritchie4 and Kaitlin Meyer2, (1)University of Utah, Civil and Environmental Engineering, Salt Lake City, United States, (2)University of Utah, Civil and Environmenal Engineering, Salt Lake City, United States, (3)University of Utah, Civil and Environmental Engineering, Salt Lake City, UT, United States, (4)Colorado School of Mines, Golden, United States
Variation in water supply prediction among mountain watersheds of the western US and corresponding differences in moisture pathways (1936985)
Jeremy Barroll, University of Colorado at Boulder, Civil, Environmental and Architectural Engineering, Boulder, United States, Ben Livneh, University of Colorado at Boulder, Department of Civil, Environmental, and Architectural Engineering, Boulder, United States and Andrew Charles Winters, University of Colorado Boulder, Atmospheric and Environmental Sciences, Boulder, United States
Hydrological Cycle in a Warming Climate: A Continental-Scale Case Study Across Europe (1942221)
Mr. Vishal Thakur, M.Engg1, Yannis Markonis1, Oldrich Rakovec1 and Yannis Markonis, (1)Faculty of Environmental Sciences, Czech University of Life Sciences Prague, Kamýcká 129, Praha – Suchdol, 16500, Prague, Czech Republic
Albatross: A Scalable Climate Service for Seasonal Precipitation and Inflow Forecasting (1946783)
Giulio Palcic1, Matteo Giuliani2, Guido Ascenso1, Carsten Ehbrecht3, Nils Hempelmann4 and Andrea Castelletti1, (1)Politecnico di Milano, Department of Electronics, Information, and Bioengineering, Milano, Italy, (2)Politecnico di Milano, Department of Electronics, Information, and Bioengineering, Milano, 20133, Italy, (3)DKRZ German Climate Computing Centre, Hamburg, Germany, (4)European Center for Medium-Range Weather Forecasts, Bonn, Germany
Advancing 9-Month Hydrologic Forecasts for Large Transboundary Basins: A Case Study in the Great Lakes Region (1952025)
Yi Hong, Cooperative Institute for Great Lakes Research, University of Michigan, Ann Arbor, United States, Matthew Parent, University of Michigan Ann Arbor, Ann Arbor, United States, Dani Jones, University of Michigan, Cooperative Institute for Great Lakes Research, Ann Arbor, United States, Lindsay Fitzpatrick, Cooperative Institute for Great Lakes Research, Ann Arbor, United States and Lauren M Fry, University of Michigan, Ann Arbor, United States
Evaluating Future Hydrologic Drought Projections Through Ensemble Modeling of Structurally Distinct RCMs (1962585)
Youngjun Son1, Cameron Bracken1, Goutam Konapala1, Nathalie Voisin1,2, Vincent Tidwell1, Connor Aghili3 and Neal Mann3, (1)Pacific Northwest National Laboratory, Richland, United States, (2)University of Washington, Seattle, United States, (3)Argonne National Laboratory, Lemont, United States
The First Step in Nationwide Flood Risk Modeling with Stochastic Storm Transposition: A National Transposition Domain Dataset (1966687)
Benjamin FitzGerald, University of Wisconsin Madison, Civil and Environmental Engineering, Madison, WI, United States, Daniel B Wright, University of Wisconsin-Madison, Department of Civil and Environmental Engineering, Madison, United States, Lei Yan, University of Wisconsin Madison, Madison, United States, Antonia Sebastian, University of North Carolina at Chapel Hill, Department of Earth, Marine, and Environmental Sciences, Chapel Hill, NC, United States, Marissa Webber, University of North Carolina at Chapel Hill, Earth, Marine, and Environmental Sciences, Chapel Hill, NC, United States, David Rosa, FEMA Engineering Resources Branch, Washington, United States and Gregory S. Karlovits, U.S. Army Corps of Engineers Hydrologic Engineering Center, Davis, United States
Evaluation of Temperature Trends Simulated by Reanalysis Data at Observations Sites in the Continental United States (1971836)
Pushpendra Raghav, University of Alabama, Tuscaloosa, AL, United States, Kaustubh Anil Salvi, Indian Institute of Technology Bombay, Department of Civil Engineering, Mumbai, India and Mukesh Kumar, University of Alabama, Tuscaloosa, United States
Modeling Streamflow in Fire-Impacted Watersheds across the CONUS using LSTMs (1972879)
Dr. Claudia Corona, PhD1, Cooper Moon1 and Terri S Hogue2, (1)Colorado School of Mines, Civil and Environmental Engineering, Golden, CO, United States, (2)Colorado School of Mines, Civil and Environmental Engineering, Hydrologic Science and Engineering, Golden, CO, United States
Evaluating the Influence of Precipitation Forcing and Vegetation Dynamics on Hydrologic Simulations in Semi-Arid Snow-Dominated Catchments Using Noah-MP and RAPID (1984524)
Sadaf Moghisi1, Ali Behrangi2, Aniket Gupta2, Mohammad Farmani3, Bohumil Svoma4 and Guo-Yue Niu2, (1)University of Arizona, Tucson, AZ, United States, (2)University of Arizona, Department of Hydrology and Atmospheric Sciences, Tucson, United States, (3)University of Arizona, Department of Hydrology and Atmospheric Sciences, Tucson, AZ, United States, (4)Salt River Project, Tempe, United States
From Buoy to Forecast: Enhancing GFS and ERO Accuracy for Improved Precipitation Prediction (2002495)
Isabel Sanchez Viruet, Maryland Sea Grant College, College Park, MD, United States, AJ Reiss, NOAA, NWS, College Park, United States and Avichal Mehra, NOAA NWS NCEP Environmental Modeling Center, College Park, United States
