Pore velocity estimation uncertainties

Abstract

Geostatistical data analysis techniques were used to stochastically model the spatial variability of groundwater pore velocity in a potential waste repository site. Kriging algorithms were applied to Hanford Reservation data to estimate hydraulic conductivities, hydraulic head gradients, and pore velocities. A first‐order Taylor series expansion for pore velocity was used to statistically combine hydraulic conductivity, hydraulic head gradient, and effective porosity surfaces and uncertainties to characterize the pore velocity uncertainty. Use of these techniques permits the estimation of pore velocity uncertainties when pore velocity measurements do not exist. Large pore velocity estimation uncertainties were found to be located in the region where the hydraulic head gradient relative uncertainty was maximal.