H039
Characterizing, Analyzing, and Dealing with Uncertainty in Human-water Systems for Better Decisions

Session ID#: 159486

Session Description:
Models that simulate interactions between water and society are prone to considerable uncertainties. These complex models, which are a function of human behaviors and the physical properties of the hydrosphere, are designed to support decision making in response to anthropogenic/environmental changes. Inadequate characterization of uncertainty in these models can lead to overconfident, unreliable, and poor decisions. Thus, characterizing uncertainty throughout the various stages of model building and decision making is crucial.
Our session invites contributions that discuss advances, both in theory and application, in methods for uncertainty analysis of human-water models. We welcome presentations on:
- Taxonomy of uncertainty in human-water systems
- New methods for efficient characterization of uncertainty and sensitivity
- Improving conventional tools (e.g., Bayesian updating) for uncertainty quantification
- Combining quantitative uncertainty analysis (e.g., global sensitivity analysis) with qualitative measures of uncertainty (e.g., pedigree analysis, sensitivity auditing)
- Assessing nonlinearities, interactions, and uncertainties using AI/ML techniques
Index Terms:

1803 Anthropogenic effects [HYDROLOGY]
1834 Human impacts [HYDROLOGY]
1849 Numerical approximations and analysis [HYDROLOGY]
1880 Water management [HYDROLOGY]

Primary Convener:  Mohammad Ghoreishi, University of Saskatchewan, School of Environment and Sustainability, Saskatoon, SK, Canada
Conveners:  Newsha Khodatalab Ajami, Stanford University, Woods Institute for the Environment, Stanford, CA, United States, Murugesu Sivapalan, University of Illinois, Urbana-Champaign, Urbana-Champaign, IL, United States, Andrea Saltelli, University of Bergen, Bergen, Norway and Arnald Puy, Princeton University, Department of Ecology and Evolutionary Biology, New Jersey, United States
Student/Early Career Convener:  Razi Sheikholeslami, University of Oxford, School of Geography and the Environment, Oxford, United Kingdom
 
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See more of: Hydrology
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