				Search Options
Index \| Site Map \| FAQ \| Facility Info \| Reading Rm \| New \| Help \| Glossary \| Contact Us

Information on Hydrologic Conceptual Models, Parameters, Uncertainty Analysis, and Data Sources for Dose Assessments at Decommissioning Sites (NUREG/CR-6656)

On this page:

Publication Information
Introduction

Download complete document

The following links on this page are to documents in Adobe Portable Document Format (PDF). See our Plugins, Viewers, and Other Tools page for more information. For successful viewing of PDF documents on our site please be sure to use the latest version of Adobe.

NUREG/CR-6656 (PDF - 2.91 MB)

Publication Information

Prepared by
P. D. Meyer
G. W. Gee

T. J. Nicholson, NRC Project Manager

Pacific Northwest National Laboratory
Richland, WA 99352

November, 1999

Prepared for
Division of Risk Analysis and Applications
Office of Nuclear Regulatory Research
U. S. Nuclear Regulatory Commission
Washington, DC 20555-0001
NRC JCN W6503

Availability Notice

Introduction

This report addresses issues related to the analysis of uncertainty in dose assessments conducted as part of decommissioning analyses. The analysis is limited to the hydrologic aspects of the exposure pathway involving infiltration of water at the ground surface, leaching of contaminants, and transport of contaminants through the groundwater to a point of exposure. The basic conceptual models and mathematical implementations of three dose assessment codes are outlined along with the site-specific conditions under which the codes may provide inaccurate, potentially nonconservative results. In addition, the hydrologic parameters of the codes are identified and compared. A methodology for parameter uncertainty assessment is outlined that considers the potential data limitations and modeling needs of decommissioning analyses. This methodology uses generic parameter distributions based on national or regional databases, sensitivity analysis, probabilistic modeling, and Bayesian updating to incorporate site-specific information. Data sources for best-estimate parameter values and parameter uncertainty information are also reviewed. A follow-on report will illustrate the uncertainty assessment methodology using decommissioning test cases.