Use of groundwater lifetime expectancy for the performance assessment of a deep geologic waste repository: 1. Theory, illustrations, and implications

TL;DR

This paper introduces a framework based on groundwater lifetime expectancy to assess the safety of deep geological waste repositories, helping to identify optimal sites and evaluate risks associated with radionuclide leakage.

Contribution

It develops a novel travel time framework using lifetime expectancy as a safety indicator, incorporating fracture network effects and providing a method for site evaluation.

Findings

Lifetime expectancy can be effectively computed using adjoint equations.

Fracture networks significantly influence the uncertainty in lifetime expectancy.

The method aids in selecting safer repository locations based on probabilistic analysis.

Abstract

Long-term solutions for the disposal of toxic wastes usually involve isolation of the wastes in a deep subsurface geologic environment. In the case of spent nuclear fuel, if radionuclide leakage occurs from the engineered barrier, the geological medium represents the ultimate barrier that is relied upon to ensure safety. Consequently, an evaluation of radionuclide travel times from a repository to the biosphere is critically important in a performance assessment analysis. In this study, we develop a travel time framework based on the concept of groundwater lifetime expectancy as a safety indicator. Lifetime expectancy characterizes the time that radionuclides will spend in the subsurface after their release from the repository and prior to discharging into the biosphere. The probability density function of lifetime expectancy is computed throughout the host rock by solving the backward-in-time solute transport adjoint equation subject to a properly posed set of boundary conditions. It can then be used to define optimal repository locations. The risk associated with selected sites can be evaluated by simulating an appropriate contaminant release history. The utility of the method is illustrated by means of analytical and numerical examples, which focus on the effect of fracture networks on the uncertainty of evaluated lifetime expectancy.