H11M:
Better Informed than Uncertain: Applications of Information Theory in the Earth Sciences Posters


Submit an Abstract to this Session


Session ID#: 44594

Session Description:
Information Theory (IT) quantifies the information content, or uncertainty and changes in uncertainty, within any form of structured content, including data relevant to earth systems.  IT has a broad and growing applicability within the geosciences in the contexts of complex systems, development and validation of models, and synthesis between models and data.  This session seeks contributions from across the geosciences that highlight IT to address challenges, such as:

  • properly incorporating information about physical laws, constraints, assumptions and other physical properties into models
  • characterizing the information content of data and models to evaluate their usefulness, robustness, and/or appropriateness for a given purpose 
  • evaluating the interplay between data, model structure, and predictive uncertainty, and detecting, diagnosing, and correcting model structural inadequacies 
  • characterizing connectivity in complex networks in the form of spatial or temporal dependencies that represent interactions, dynamics and feedbacks
  • quantifying resilience, sensitivity, robustness and/or vulnerability within earth systems 
Primary Convener:  Allison Eva Goodwell, University of Colorado Denver, Civil Engineering, Denver, CO, United States
Conveners:  Dr. Grey Stephen Nearing, PHD, University of Alabama, Geological Sciences, Tuscaloosa, United States, Uwe Ehret, Karlsruhe Institute of Technology, Institute for Water and Environment, Karlsruhe, Germany and Hoshin Gupta, University of Arizona, Hydrology and Atmospheric Sciences, Tucson, AZ, United States
Primary Liaison:  Allison Eva Goodwell, Prairie Research Institute at University of Illinois at Urbana-Champaign, Illinois State Water Survey, Champaign, United States
Chairs:  Allison Eva Goodwell, Prairie Research Institute at University of Illinois at Urbana-Champaign, Illinois State Water Survey, Champaign, United States and Dr. Grey Stephen Nearing, PHD, Upstream Tech, Tuscaloosa, United States
OSPA Liaison:  Allison Eva Goodwell, Prairie Research Institute at University of Illinois at Urbana-Champaign, Illinois State Water Survey, Champaign, United States
Index Terms:

1847 Modeling [HYDROLOGY]
1873 Uncertainty assessment [HYDROLOGY]
1990 Uncertainty [INFORMATICS]
4430 Complex systems [NONLINEAR GEOPHYSICS]

Abstracts Submitted to this Session:

Information theoretic fingerprinting of hydrologic Models (364880)
Andrew Bennett, University of Arizona, Department of Hydrology & Atmospheric Sciences, Tucson, AZ, United States, Bart Nijssen, University of Washington Seattle Campus, Civil and Environmental Engineering, Seattle, WA, United States, Dr. Grey Stephen Nearing, PHD, Upstream Tech, Tuscaloosa, United States and Martyn P Clark, University of Calgary, Department of Civil Engineering, Schulich School of Engineering, Calgary, AB, Canada
Using signatures to extract hydrologic information from data across scales (Invited) (367916)
Hilary K McMillan, San Diego State University, Department of Geography, San Diego, CA, United States, Ida Westerberg, IVL Swedish Environmental Research Institute, Stockholm, Sweden and Flora Branger, INRAE Lyon, RiverLy, Villeurbanne, France
Hydrological interpretation of a statistical measure of basin complexity (386005)
Saket Pande, Delft University of Technology, Delft, Netherlands and Mohamadmehdi Moayeri, University of Tabriz, Tabriz, Iran
Retrieval of Friction Velocity from Sensible Heat Flux Parameterized Using MEP Model over Land Surfaces (Invited) (394064)
Jingfeng Wang, GA Ins of Tech-Civil & Env Eng, Atlanta, United States, Yao Tang, Georgia Institute of Technology, Atlanta, United States and Yi Deng, Georgia Institute of Technology, School of Earth and Atmospheric Sciences, Atlanta, GA, United States
Unraveling the Causal Dynamics in Stream Solutes by Using an Information-Theoretic Approach (446357)
Peishi Jiang, University of Alabama, Civil, Construction and Environmental Engineering, Tuscaloosa, AL, United States and Praveen Kumar, University of Illinois at Urbana-Champaign, Department of Civil and Environmental Engineering, Urbana, United States
Information theory-based location of sensor nodes: what is optimal? (455737)
Steven V Weijs, University of British Columbia, Civil Engineering, Vancouver, BC, Canada and Hossein Foroozand, University of British Columbia, Civil Engineering, Vancouver, Canada

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