When establishing a safety case for a high-level nuclear waste repository, coupled thermal, hydraulic, mechanical and chemical (THMC) processes are modelled to assess radionuclide transport and the integrity of barriers. Modelling these processes requires numerous parameters, which are all subject to uncertainty. However, complex and extensive uncertainty quantification (UQ) methods can come at great computational cost, especially when performed on multi-parametric problems. Therefore, UQ methods are sought with manageable computational effort while still capturing the relevant information to allow a meaningful interpretation of the results.

The aim of this study is the comparison of three different UQ methods with different levels of complexity and computational cost in terms of their results. Radionuclide transport and THM-calculations are performed by employing these methods to the French Callovo-Oxfordian claystone as a reference material. The three methods include: (1) a UQ method based on the complete sampling of input parameter distributions by a Monte Carlo approach, (2) a UQ method based on a minimal number of data points, by sampling quantiles of the input parameter distributions, as well as the bounds of the distributions’ intervals, and (3) a UQ method that involves a first-order second-moment reliability approach.

The results depict the different limitations and benefits of the UQ methods analysed while highlighting that a comprehensive understanding of parameter sensitivity and modelling approach are key to choosing the appropriate UQ method.