ABSTRACT
In the present paper, we propose a combination of Gaussian process-based meta-models with Principal Component Analysis which is originally applied to predict the evolution in time of radionuclide concentration in groundwater following a release from a radioactive waste repository. The resulting empirical model provides a fast response with a measure of prediction uncertainty. An application is presented with reference to a radionuclide contamination problem of a hydrologic system of literature.
