AGU 2002 Fall Meeting Abstract

The following is the abstract for a poster presentation at the Fall 2002 Meeting of the American Geophysical Union (poster NG12B-1033).

Evaluation and Quantification of Uncertainty in the Modeling of Contaminant Transport and Exposure Assessment at a Radioactive Waste Disposal Site

J D Tauxe, (Neptune and Company, Los Alamos, NM 87544;
505-662-2121; e-mail: jtauxe@neptuneinc.org

The disposal of low-level radioactive waste (LLW) in the United States is a highly regulated undertaking. The US Department of Energy (DOE), itself a large generator of such wastes, requires a substantial amount of analysis and assessment before permitting continuing operation of sites for disposal of LLW. One of the requirements that must be met in assessing the performance of a disposal site and technology is that a Performance Assessment (PA) demonstrate "reasonable expectation that certain performance objectives, such as dose to a hypothetical future receptor, not be exceeded. The phrase "reasonable assurance" implies recognition of uncertainty in the assessment process. In order for this uncertainty to be quantified and communicated to decision makers, the PA computer model must accept probabilistic (uncertain) input (parameter values) and produce results which reflect that uncertainty as it is propagated through the model calculations. Model parameters range from water content and other physical properties of alluvium to the activity of radionuclides disposed to the amount of time a future resident might be expected to spend tending a garden. The decision maker has the difficult job of evaluating the uncertainty of modeling results in the context of granting permission for LLW disposal.

In addition to providing decision makers with realistically uncertain modeling results, a probabilistic assessment is also useful in guiding research efforts aimed at reducing the uncertainty in key components of the model. A sensitivity analysis of the modeling results identifies which model parameters are most significant in determining estimated doses, for example, thus providing justification for the allocation of limited research funding.

reference for this presentation:

Tauxe, J., P. Black, J. Carilli, K. Catlett, B. Crowe, M. Hooten, S. Rawlinson, A. Schuh, T. Stockton, V. Yucel, Evaluation and Quantification of Uncertainty in the Modeling of Contaminant Transport and Exposure Assessment at a Radioactive Waste Disposal Site, Eos Trans. AGU, 83(47), Fall Meeting Supplement, Abstract NG12B-1033, 2002