H41J:
Large-Scale Watershed Modeling and Data Uncertainty on Hydrologic and Water Quality Processes I

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Session ID#: 17126

Session Description:
In recent years, large-scale watershed modeling has been widely implemented in the field of water resources and environmental subjects. Engineering projects are developed and conducted based on simulated hydrologic, sediment, and nutrient processes. While most modeling efforts were performed by the assumption of deterministic approaches, it has been shown that model predictions could be substantially alternated by the associated uncertainty sources such as forcing inputs, algorithm parameters, model structure, and measured data from calibration/validation. In this session, watershed modeling and the associated uncertainty sources will be discussed to explore broader insights for advanced applications and also to provide potential benefits for decision making processes in the future.
Primary Convener:  Haw Yen, Blackland Research and Extension Center, Texas A&M Agrilife Research, Texas A&M University, Temple, TX 76502, USA, Blackland Research and Extension Center, College Station, United States
Conveners:  Daren Harmel, USDA-ARS, Grassland, Soil and Water Research Laboratory, Temple, TX, United States, Michael J White, USDA-ARS, Grassland, Soil and Water Research Laboratory, Temple, United States and Jeffrey G Arnold, USDA-ARS, Temple, United States
Chairs:  Haw Yen, Blackland Research and Extension Center, Texas A&M Agrilife Research, Texas A&M University, Temple, TX 76502, USA, Blackland Research and Extension Center, College Station, United States and Daren Harmel, USDA-ARS, Grassland, Soil and Water Research Laboratory, Temple, TX, United States
OSPA Liaison:  Haw Yen, Blackland Research and Extension Center, Texas A&M Agrilife Research, Texas A&M University, Temple, TX 76502, USA, Blackland Research and Extension Center, College Station, United States
Index Terms:

1805 Computational hydrology [HYDROLOGY]
1846 Model calibration [HYDROLOGY]
1847 Modeling [HYDROLOGY]
1879 Watershed [HYDROLOGY]

Abstracts Submitted to this Session:

Increasingly, Data Availability Limits Model Predictive Capacity: the Western Lake Erie Basin, a Case Study (Invited) (187836)
Mari-Vaughn V. Johnson1, Kathrine D Behrman2,3, Jay D Atwood4, M. Lee Norfleet1 and Conservation Effects Assessment Project (CEAP), (1)USDA-NRCS, Resources Assessment Division, Temple, TX, United States, (2)University of Texas at Austin, Integrative Biology, Austin, TX, United States, (3)USDA-ARS Grasslands, Soil, and Water Research Laboratory, Temple, TX, United States, (4)USDA-NRCS, Temple, TX, United States
Evaluating uncertainty of climate change projections when bias-corrected with different input datasets (189643)
Aleksey Y Sheshukov, Kansas State University, Biological & Agricultural Engineering, Manhattan, KS, United States and Jungang GAO, Texas A&M University College Station, College Station, TX, United States
The Importance of Land Management Assumptions on Nutrient Hotspots and Scenario Effectiveness (197696)
Margaret McCahon Kalcic1, Rebecca Logsdon Muenich2, Donald Scavia2, Yu-Chen Wang2 and Colleen McCormick Long2, (1)The Ohio State University, Department of Food, Agricultural and Biological Engineering, Columbus, OH, United States, (2)University of Michigan Ann Arbor, Ann Arbor, MI, United States
Modeling pesticide loadings from the San Joaquin watershed into the Sacramento-San Joaquin Delta using SWAT (145469)
Huajin Chen and Minghua Zhang, University of California Davis, Davis, CA, United States
The effect of input data complexity on the uncertainty of streamflow simulation using SWAT-HS (149219)
Linh Hoang1, Elliot M Schneiderman2, Tammo S Steenhuis3, Karen E Moore2 and Emmet M Owens2, (1)City University of New York/ NYC Department of Environmental Protection, Kingston, NY, United States, (2)New York City Department of Environmental Protection, Kingston, NY, United States, (3)Cornell University, Biological and Environmental Engineering, Ithaca, NY, United States
Impacts of Land Use/Cover Uncertainty on Predictions of Ecologically Relevant Flow Metrics (187296)
Latif Kalin, Auburn University, College of Forestry, Wildlife and Environment, Auburn, United States and Furkan Dosdogru, Auburun University, School of Forestry and Wildlife Sciences, Auburn, AL, United States
Improved Calibration Results Using Uncertainty Analysis: An Application of SWAT Model in Southern Brazil (166701)
Tássia Mattos Brighenti, Nadia Bernardi Bonumá and Pedro Luiz Borges Chaffe, UFSC Federal University of Santa Catarina, Florianópolis, Brazil
Systems Reliability Framework for Surface Water Sustainability and Risk Management (191713)
John Robert Myers and Lilit Yeghiazarian, University of Cincinnati Main Campus, Cincinnati, OH, United States

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