The use of probability elicitation in the high-level nuclear waste regulation program

Abstract Expert judgement elicitation is expected to be used in the performance assessments (PA) of the long-term behavior of high-level waste (HLW) geologic repositories. As a preparation for an effective review of the U.S. Department of Energy (DOE) PA, the Nuclear Regulatory Commission (NRC) is evaluating the mechanics of eliciting expert judgements. One of the objectives of this evaluation is to explore techniques for generating and aggregating probabilistic judgements of future conditions at the proposed HLW repository at Yucca Mountain, Nevada. An actual elicitation was conducted as an aid to these evaluations. This paper documents this probabilistically centered elicitation and subsequent activities to explore aggregation of opinion techniques. Future climate in the Yucca Mountain, Nevada vicinity was selected as the topic for elicitation. Personnel from the NRC and Center for Nuclear Waste Regulatory Analyses (CNWRA) defined the climatic parameters of interest in conjunction with a panel of five expert climatologists. Individual elicitations were performed with each climatologist to produce probabilistic estimates of each parameter at seven points of time in the future. The elicitations employed the fractile technique to generate cumulative probability distributions representing the uncertainty in the predictions. After the individual elicitations, a group session was conducted to explore aggregation and consensus methods.

[1]  Carl-Axel S. Staël von Holstein,et al.  Exceptional Paper---Probability Encoding in Decision Analysis , 1975 .

[2]  W. Edwards,et al.  Decision Analysis and Behavioral Research , 1986 .

[3]  John Rohrbaugh,et al.  Improving the quality of group judgment: Social judgment analysis and the Delphi technique. , 1979 .

[4]  D. Fehringer,et al.  Uncertainty in Regulatory Decision-Making , 1992 .

[5]  Wilfred C. Uecker.  The Quality Of Group-Performance In Simplified Information Evaluation , 1982 .

[6]  Wayne S. Smith,et al.  Adaptive Forecasting Models Based on Predictive Distributions , 1978 .

[7]  R. Clemen.  Combining forecasts: A review and annotated bibliography , 1989 .

[8]  Robin M. Hogarth,et al.  Quality of Group Judgment , 1977 .

[9]  Ali Mosleh,et al.  A critique of current practice for the use of expert opinions in probabilistic risk assessment , 1988 .

[10]  Murray Turoff,et al.  The Delphi Method: Techniques and Applications , 1976 .

[11]  Robert T. Clemen,et al.  Combining Overlapping Information , 1987 .

[12]  T. Modis,et al.  Experts in uncertainty , 1993 .

[13]  L. J. Savage,et al.  The Foundation of Statistics , 1956 .

[14]  R. H. Edmundson,et al.  The accuracy of combining judgemental and statistical forecasts , 1986 .

[15]  George Apostolakis,et al.  Some approximations useful to the use of dependent information sources , 1993 .

[16]  Edna M. White,et al.  Subjective versus objective combining of forecasts: An experiment , 1989 .

[17]  B. Grofman.  Information Pooling and Group Decision Making , 1986 .

[18]  Ralph L. Keeney,et al.  Elicitation and use of expert judgment in performance assessment for high-level radioactive waste repositories , 1990 .

[19]  Elizabeth C. Hirschman,et al.  Judgment under Uncertainty: Heuristics and Biases , 1974, Science.