MeetingOfInterest:Meeting-111
From CSDMS
2014 SIAM Conference on Uncertainty Quantification
Savannah Georgia, United States
31 - 03 April 2014
31 - 03 April 2014
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Deadlines
Abstract submission: The abstract submission deadline has passed Registration: Registration is now closed
Official website
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Scientists must provide regulators with defensible quantification of uncertainties associated with sometimes controversial environmental problems (e.g. sustainability, resources management, climate change and impacts, carbon sequestration, fracking). This minisymposium explores how conceptual and data uncertainties are represented, evaluated, and reduced, and how uncertainty quantification is used in risk analysis, decision support, and law. Of interest are probabilistic and non-probabilistic metrics of judging models against data, ranking alternative models and testing hypotheses; sensitivity analyses for unraveling sources of uncertainty; data collection strategies optimized to reduce uncertainty; and how uncertainty measures inform enforcement strategies and legal frameworks.
To address these issues the following speakers have been invited:
Part I (Monday 2:00-4:00pm)
- Emanuele Borgonovo, Bocconi University in Milan – Uncertainty, sensitivity analysis, and risk analysis emanuele.borgonovo@unibocconi.it
- Anthony Jakeman and Joseph Guillaume, Australia National University, Holistic uncertainty management for environmental decision support. Slight uncertainty on commitment tony.jakeman@anu.edu.au joseph.guillaume@anu.edu.au
- Grey Nearing, NASA On the Quantity and Quality of Information Provided by Models and Induction grey.s.nearing@nasa.gov
- Daniel Tartakovsky, UC San Diego – Uncertainty quantification in the presence of subsurface heterogeneity dmt@ucsd.edu
Part II (Tuesday 9:30-11:30am)
- Mary C. Hill, USGS, Computationally frugal evaluation of parameter importance to predictions and their uncertainty
- Burke Minsley. USGS -- Integrating geophysics to reduce groundwater model uncertainty bminsley@usgs.gov
- Ming Ye, FSU , Combined Estimation of Model Scenario, Structure, and Parameter Uncertainty and Sensitivity with Application to Groundwater Reactive Transport Modeling mye@fsu.edu
- Dan Lu, Oak Ridge National Laboratory – Uncertainty evaluation in subsurface flow and transport, with chemical reactions dlu@fsu.edu
