Understanding the Interface between Models and Data

Session ID#: 24515

Session Description:
Experience from the first decades of modeling hydrologic systems is that models are rarely accurate predictors of future events. This session considers best practices and new ideas for modeling under large uncertainties, and will highlight new insights about reconciling complex systems models with observation data to improve scientific insight and predictive capabilities. 

Theoretical and applied studies are encouraged. Examples include:

1. Model evaluation and diagnostics (e.g., hypothesis testing, benchmarking, multi-hypothesis models, process diagnostics, sensitivity analysis)

  1. Combining models and data to make better predictions (e.g., system identification, data assimilation, parameter estimation, machine learning)
  2. Using models to suggest better data collection strategies (e.g., experimental design, value of information, observing system simulation experiments)
  3. Information and/or uncertainty quantification & management (e.g., information theory, uncertainty cascades, decision trees, foundations of probability)

The intent is to support a discussion about how uncertainty arises as a product of the scientific method.

Primary Convener:  Kimberly C Brumble, Indiana University Bloomington, History and Philosophy of Science, Bloomington, IN, United States
Conveners:  Kimberly C Brumble, Indiana University Bloomington, History and Philosophy of Science, Bloomington, IN, United States, Grey S Nearing, NASA Goddard Space Flight Center, Greenbelt, MD, United States and Mary C Hill, University of Kansas, Department of Geology, Lawrence, KS, United States

  • A - Atmospheric Sciences
  • IN - Earth and Space Science Informatics
  • NG - Nonlinear Geophysics
Index Terms:

1847 Modeling [HYDROLOGY]
1873 Uncertainty assessment [HYDROLOGY]
1952 Modeling [INFORMATICS]
1990 Uncertainty [INFORMATICS]

Abstracts Submitted to this Session:

Yu-Fen Huang, University of Hawaii at Manoa, Honolulu, HI, United States and Yin-Phan Tsang, MI St-Fisheries & Wildlife, East Lansing, MI, United States
Dilhani Ishanka Jayathilake and Tyler J Smith, Clarkson University, Potsdam, NY, United States
Youlong Xia1, David M Mocko2, Shugong Wang3, Ming Pan4, Sujay Kumar5, Christa D Peters-Lidard5, Helin Wei1 and Michael B Ek6, (1)Environmental Modeling Center, College Park, MD, United States, (2)NASA GSFC/SAIC, Greenbelt, MD, United States, (3)Goddard Space Flight Center, Greenbelt, MD, United States, (4)Princeton University, Civil and Environmental Engineering, Princeton, NJ, United States, (5)NASA GSFC, Greenbelt, MD, United States, (6)Environmental Modeling Center, NOAA/NWS/NCEP, College Park, MD, United States
Walter Lee Ellenburg II1, James Cruise1 and Vijay P Singh2, (1)University of Alabama in Huntsville, Huntsville, AL, United States, (2)Texas A & M University, College Station, TX, United States
Peishi Jiang and Praveen Kumar, University of Illinois at Urbana Champaign, Urbana, IL, United States
Andrew M O'Reilly, University of Mississippi Main Campus, University, MS, United States
Huijuan Cui, IGSNRR Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing, China and Vijay P. Singh, Texas A&M University, College Station, United States
Lucy Amanda Marshall1, Yating Tang2, Hoori Ajami3 and Ashish Sharma1, (1)University of New South Wales, School of Civil and Environmental Engineering, Sydney, NSW, Australia, (2)University of New South Wales, Sydney, NSW, Australia, (3)University of California Riverside, Riverside, CA, United States

See more of: Hydrology