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Session Proposal: Advancements in Hydrologic Tools and Technologies (AGU25)

IN004
Advancements in Hydrologic Tools and Technologies

Session ID#: 251678

Session Description:
The digital transformation of water-resources management and systems has led to a growing need for interactive forums that present, discuss, and demonstrate computational tools and technologies in hydrology. This is especially important for hydrologists, water managers, and policy makers who need to stay up-to-date with emerging multi-disciplinary methods. This session aims to provide a platform for developers of hydrologic tools, software, and applications to share their technologies with a wider audience. This session will focus on research-to-operation methods, tools, apps, and software that help attendees understand the state-of-the-art in hydrology, analysis, and prediction. By bringing together developers and practitioners in hydrology, this session will provide a valuable opportunity for knowledge sharing and collaboration, helping to advance the field and improve water-resources management.
Co-Sponsor(s):
  • ED - Education
  • H - Hydrology
  • SY - Science and Society
Index Terms:

1902 Community modeling frameworks [INFORMATICS]
1906 Computational models, algorithms [INFORMATICS]
1910 Data assimilation, integration and fusion [INFORMATICS]
1976 Software tools and services [INFORMATICS]
Primary Convener:  Sushant Mehan, South Dakota State University, Department of Agricultural and Biosystems Engineering, Brookings, SD, United States
Convener:  Daniel P Ames, Brigham Young University, Civil and Environmental Engineering, Provo, United States
 
Spatial Attention layer for rainfall spatial interpolation (1846385)
Ju-Young Shin, Kookmin University, School of Civil and Environmental Engineering, Seoul, Korea, Republic of (South), Jiyeon Park, Kookmin University, School of Civil and Environmental Engineering, Seoul, South Korea and Sangbeom Jang, Kookmin University, Departemnt of Civil and Enviornment Engineering, Seoul, South Korea
 
Hydrology Tool Set (HTS): A Suite of Online Tools and Models for Open Science (1847570)
Serban Danielescu, Environment Canada and Agriculture and Agri-Food Canada, Fredericton, NB, Canada
 
Streamlining Satellite-Based Water Quality Assessment: The RS-WaterQuality Mapper Toolbox for QGIS (1860270)
Haibin Su1, Hongxing Liu2, Lei Wang3, Ekaterina Miliutina2, Jilin Men2, Dan Tian2, Yuehan Lu4, Song Shu5, Richard A Beck6 and Amanjit Premsagar4, (1)Texas A & M University - Kingsville, Department of Physics & Geosciences, Kingsville, United States, (2)The University of Alabama, Department of Geography and the Environment, Tuscaloosa, AL, United States, (3)Louisiana State University, Department of Geography and Anthropology, Baton Rouge, LA, United States, (4)The University of Alabama, Geological Sciences, Tuscaloosa, AL, United States, (5)Appalachian State University, Department of Geography and Planning, Boone, NC, United States, (6)University of Cincinnati Main Campus, Cincinnati, OH, United States
 
A National Model for Predicting Submerged Hydraulic Jumps at Low-Head Dams Using Open-Access Remote Sensing Data (1866266)
Kenneth Quintana, Brigham Young University, Provo, UT, United States
 
Coastwise: A Gamified Approach to Coastal Watershed Planning Through the Stormwater Management Model (1873051)
Savannah Lynn1, Victor Leal Sobral1, Luke Schneider2 and Jonathan L Goodall1, (1)University of Virginia, Department of Civil and Environmental Engineering, Charlottesville, VA, United States, (2)University of Virginia, Charlottesville, United States
 
Introducing the Next Generation of USGS Water Data APIs (1873332)
Mike Mahoney, USGS Water Mission Area, Integrated Information Dissemination Division, Northborough, United States
 
FIMserv v.1.0: A Tool for Streamlining Flood Inundation Mapping (FIM) Using the United States Operational Hydrological Forecasting Framework (1883736)
Anupal Baruah1, Supath Dhital1, Sagy Cohen2, Thanh Nhan Duc Tran3, Hesham Elhaddad4, Cheryl Lyn Watts5, Dipsikha Devi1, Yixian Chen1, Carson Pruitt6 and Supath Dhital, Department of Geography and Environment, The University of Alabama, Tuscaloosa, AL 35401, USA, (1)The University of Alabama, Department of Geography and the Environment, Tuscaloosa, AL, United States, (2)The University of Alabama, Tuscaloosa, AL, United States, (3)University of Virginia, Civil and Environmental Engineering, Charlottesville, VA, United States, (4)Western Michigan University, Department of Geological and Environmental Sciences, Kalamazoo, United States, (5)University of Massachusetts Amherst, Geosciences, Amherst, United States, (6)NOAA Office of Water Prediction, National Water Center, Geo-Intelligence Division, Tuscaloosa, United States
 
A Framework for the Evaluation of Flood Inundation Predictions Over Extensive Benchmark Databases (1885833)
Dipsikha Devi1, Supath Dhital1, Dinuke Munasinghe2, Sagy Cohen1, Anupal Baruah1, Yixian Chen3, Dan Tian1 and Carson Pruitt4, (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, (3)University of Alabama, Department of Geography and the Environment, Tuscaloosa, AL, United States, (4)NOAA Office of Water Prediction, National Water Center, Geo-Intelligence Division, Tuscaloosa, United States
 
Artificial intelligence-guided iterations between observations and models significantly improve continental-scale predictions of sediment respiration (Invited) (1902306)
Avni Malhotra1, Brieanne K. Forbes1, Dr. Stefan F Gary, MS, PhD2, Amy E Goldman3, Bre Rivera Waterman4, Vanessa Alessandra Garayburu-Caruso5, Michael P Bruen6, Etienne Fluet-Chouinard1, Sushant Mehan7, Micah Taylor8, Marcelo Ardon9, M. Bayani Cardenas10, Walter K Dodds11, Christian Lønborg12, William H McDowell13, Moussa Moustapha14, Allison Myers-Pigg8, Peter Regier1, Tod Rubin15, Hyun-Seob Song16, Ryan D. Stewart17, Jorge Villa18, Nicholas D Ward19, Timothy D Scheibe1 and James Stegen1, (1)Pacific Northwest National Laboratory, Richland, WA, United States, (2)Parallel Works Inc., Chicago, United States, (3)Pacific Northwest National Laboratory, Biological Sciences, Richland, WA, United States, (4)University of Kansas, Civil, Environmental, and Architectural Engineering, Lawrence, KS, United States, (5)Pacific Northwest National Laboratory, Environmental Molecular Sciences Laboratory, Richland, United States, (6)Dooge Centre for Water Resources Research, School of Civil Engineering, University College Dublin, Dublin, Ireland, (7)South Dakota State University, Agricultural and Biosystems Engineering, Brookings, United States, (8)Pacific Northwest National Laboratory, Richland, United States, (9)North Carolina State University, Forestry and Environmental Resources, Raleigh, United States, (10)University of Texas at Austin, Earth and Planetary Sciences, Austin, United States, (11)Kansas State University, Manhattan, KS, United States, (12)Aarhus University, Aarhus C, Denmark, (13)University of New Hampshire, Department of Natural Resources and the Environment, Durham, United States, (14)University of Ebolowa, Kribi, Cameroon, (15)The Watershed Project, Richmond, United States, (16)University of Nebraska Lincoln, Department of Biological Systems Engineering, Department of Food Science and Technology, Nebraska Food for Health Center, Lincoln, United States, (17)Virginia Polytechnic Institute and State University, Crop and Soil Environmental Sciences, Blacksburg, United States, (18)University of Louisiana at Lafayette, School of Geosciences, Lafayette, United States, (19)Pacific Northwest National Laboratory, Sequim, United States
 
Bankfull and Mean-Flow Channel Geometry Estimation Through Machine Learning Algorithms Across the CONtiguous United States (CONUS) (1923976)
Reihaneh Zarrabi, University of Alabama, Department of Geography and the Environment, Tuscaloosa, United States, Riley McDermott, NOAA, Office of Water Prediction, Silver Spring, United States, Mohammad Erfani, Center for Climate Systems Research, Columbia Climate School, Columbia University, New York, United States and Sagy Cohen, The University of Alabama, Department of Geography and the Environment, Tuscaloosa, AL, United States
 
Demonstrating new tools and frameworks to facilitate continental-scale hydrologic data access and evaluation (1947802)
Sam Lamont1, Matt Denno1, Katie van Werkhoven2 and Sam Landsteiner3, (1)Research Triangle Institute, Center for Water Resources, Remote, United States, (2)Research Triangle Institute, Remote, United States, (3)Research Triangle Institute, Research Triangle Park, United States
 
Modernizing HydroShare: Using a Cloud-Native Architecture to Accelerate Water Science Innovation (1959358)
Anthony M Castronova1, Irene Garousi Nejad2, Scott Black3 and Abner Bogan2, (1)Consortium of Universities for the Advancement of Hydrological Science, Washington, DC, United States, (2)Consortium of Universities for the Advancement of Hydrologic Science, Inc., Arlington, United States, (3)Consortium of Universities for the Advancement of Hydrologic Science, Inc., Cambridge, United States
 
Operationalizing Hydrologic Research: Building Web-Based Forecast and Visualization Tools with Tethys Platform (1965986)
Jianting Shi, Brigham Young University, Civil and Construction Engineering, Provo, United States, Daniel P Ames, Brigham Young University, Civil and Environmental Engineering, Provo, United States, Nathan R Swain, Brigham Young University, Provo, United States and Tasfia Mahjarin, Brigham Young University, Civil and Construction Engineering, Provo, UT, United States
 
MoltenFAC: A Tiled Flow Accumulation Algorithm for Large-Scale, Massively Parallel, and Memory-Efficient CPU/GPU Processing (1966682)
Brodie Alexander, The University of Alabama, Department of Electrical and Computer Engineering, Tuscaloosa, AL, United States, Huidae Cho, Department of Civil Engineering, New Mexico State University, Las Cruces, United States, Junho Song, University of Alabama, Alabama Water Institute, Tuscaloosa, United States and James Halgren, The University of Alabama, Alabama Water Institute, Tuscaloosa, United States
 
Tethys Dash: A Modular Framework for Low-Code Hydrologic Dashboards, Integrated Data Visualization, and Decision Support (1967182)
Tasfia Mahjarin, Brigham Young University, Civil and Construction Engineering, Provo, UT, United States, Corey Krewson, Aquaveo, Provo, United States, Daniel P Ames, Brigham Young University, Civil and Environmental Engineering, Provo, United States, Jianting Shi, Brigham Young University, Civil and Construction Engineering, Provo, United States and Nathan R Swain, Aquaveo LLC, Provo, United States
 
A Neural Network-Based Integration of HEC-RAS, LISFLOOD-FP, and OWP-HAND FIM for Enhanced Flood Inundation Mapping (1968335)
Sadra Seyvani1, Parvaneh Nikrou2, Sagy Cohen3 and Dan Tian3, (1)University of Alabama, Tuscaloosa, United States, (2)University of Alabama, Tuscaloosa, AL, United States, (3)The University of Alabama, Department of Geography and the Environment, Tuscaloosa, AL, United States
 
Democratizing National Water Model Data: A Mobile App for National Water Model River Discharge Monitoring and Flood Warning (1968518)
Jerson Jaramillo Garcia, Brigham Young University, Provo, UT, United States, Daniel P Ames, Brigham Young University, Civil and Environmental Engineering, Provo, United States and Matthew Womble, University of Alabama, Alabama Water Institute, Tuscaloosa, United States
 
MIDAS: A Memory-Efficient, Multi-Interface Toolkit for Scalable High-Performance Hydrologic Flow and Drainage Analysis Using OpenMP Parallelism (1968891)
Huidae Cho, New Mexico State University Main Campus, Las Cruces, NM, United States
 
Streamlining Community Modeling through Automated Data Processing for the Next Generation Water Resources Modeling Framework (1995596)
James Halgren1, Joshua Cunningham1, Chad Perry2, Quinn Lee1, Sonam Lama1, Arpita Patel3, Savalan Naser Neisary4, Sifan Abera Koriche5, Manjila Singh1 and Nia Minor2, (1)The University of Alabama, Alabama Water Institute, Tuscaloosa, United States, (2)University of Alabama, Alabama Water Institute, Tuscaloosa, United States, (3)The University of Alabama, Cooperative Institute for Research to Operations in Hydrology (CIROH), Alabama Water Institute, Tuscaloosa, United States, (4)The University of Alabama, Department of Civil, Construction, and Environmental Engineering, Tuscaloosa, United States, (5)University of Alabama, Tuscaloosa, AL, United States
 
Advancing Hazard Resilience with SPHERE (Spatial Platform for Hazard Evaluation and Risk Estimation): A Modular Open-Source Framework for Flood Risk Analysis (2003385)
Ashley Hoke, FEMA/Niyam IT, Hazus, Denver, United States, Troy Schmidt, FEMA/Niyam IT, Hazus, Fairfax, United States and Douglas Bausch, Federal Emergency Management Agency, Washington, D.C., United States
 
WaterSoftHack: Machine Learning, Data Analytics and Cyberinfrastructure Training for Water Science and Engineering (2003393)
Vidya Samadi1, Bijaya Adhikari2, D. Matthew Boyer3, Anthony Castronova4, Ibrahim Demir5, Krishna Panthi6, Adarsha Neupane1, Mostafa Saberian7, Nima Zafarmomen1 and Matthew Boyer, (1)Clemson University, Department of Agricultural Sciences, Clemson, SC, United States, (2)University of Iowa, Computer Science, Iowa, United States, (3)Clemson University, Eugene T. Moore School of Education, Clemson, SC, United States, (4)Consortium of Universities for the Advancement of Hydrologic Science, Inc., Arlington, United States, (5)Tulane University, New Orleans, United States, (6)Clemson University, School of Computing, Clemson, SC, United States, (7)Clemson University, Department of Civil Engineering, Clemson, United States
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