Numerical modeling of parametric uncertainties in flow through porous media: development and initial testing of PORSTAT

Previous performance analyses conducted by BWIP generally have been carried out in a deterministic framework, whereby a single model prediction was made and nothing was known about the likelihood of that prediction. As the size of the data base used for repository performance analyses increases, BWIP will progressively move toward a stochastic approach to performance studies. The main advantages of a stochastic approach are that: (1) the likelihood of model predictions can be quantified, and (2) information can be gained about how to reduce the uncertainty in these predictions. PORSTAT solves the stochastic groundwater flow equation coupled with the deterministic heat transfer and mass transport equations. An integrated finite-difference numerical scheme is used in PORSTAT to solve the governing equations. The stochastic groundwater flow equation is approximated by means of a second-order uncertainty analysis technique. Stochastic variables input to PORSTAT may be hydraulic conductivity, specific storage, boundary conditions, and initial conditions. The output from PORSTAT consists of the expected values and covariances of hydraulic heads and Darcian velocities. PORSTAT will be used by BWIP to stochastically model groundwater flow in the thermally influenced zone around the repository. In order to make a preliminary evaluation, the results from two test cases run by PORSTAT and BWIP's Monte Carlo groundwater flow computer code (MAGNUM-MC) are compared. The initial comparison indicates that PORSTAT tends to overestimate the uncertainty in hydraulic head predictions, and thus from a risk analysis viewpoint, produces conservative results. Additional testing is being conducted to determine the limitations and capabilities of PORSTAT. 41 references