Quantification and reduction of the uncertainty in mass balance models by Monte Carlo analysis of prior data
The general objective of this workshop is to investigate and discuss methods by which uncertainties in mass balance models for toxics in the Great Lakes may be reduced. As described by the workshop prospectus, this paper is focused on problems of reducing (and quantifying) uncertainty as they relate to ``in situ field observations/system response measurements for the establishment of initial conditions, boundary conditions, calibration/confirmation data sets, and model post-audit data sets.`` I have taken this description to refer not only to the evaluation of uncertainty in the field observations themselves, but also to the uncertainty associated the analyses of in situ observations as they interact in the overall modeling process. Thus, I will be concerned here with quantification and reduction of uncertainty both (1) as they may be applied to descriptions of the system that is being modeled and (2) as they may be associated with model simulations.
- Research Organization:
- Argonne National Lab., IL (United States)
- Sponsoring Organization:
- USDOE, Washington, DC (United States); Environmental Protection Agency, Washington, DC (United States); National Oceanic and Atmospheric Administration, Washington, DC (United States)
- DOE Contract Number:
- W-31109-ENG-38
- OSTI ID:
- 10136690
- Report Number(s):
- ANL/CP-75636; CONF-920291-1; ON: DE92010278
- Resource Relation:
- Conference: Approaches to reducing uncertainty in mass balance models for toxics: Lake Ontario study,Buffalo, NY (United States),3 Feb - 5 Mar 1992; Other Information: PBD: [1991]
- Country of Publication:
- United States
- Language:
- English
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