Impact of nonideal transport upon the effectiveness of pump-and-treat groundwater remediation: A computational investigation

Abstract

The impact of various nonidealities affecting pump and treat remediation was analyzed using numerical simulations. In particular, the effect of the following important non-idealities was investigated: spatial variability of hydraulic conductivity (K-field heterogeneity), spatial variability of sorption parameters, rate-limited desorption, and the combined effects of the latter two with K-field heterogeneity. Heterogeneous K-fields are modelled as spatially correlated lognormal random fields in this thesis. A hypothetical problem scenario was used to illustrate the effects of most of these nonidealities. The effect of K-field heterogeneity was also examined for a plume formed by naturally leaching conditions.Monte Carlo simulations were used to analyze the impact of uncertainty of K-field heterogeneity on the uncertainty of cleanup times. For the highest K-field variability of \sigma\sb{\rm Y} = 2.0, the uncertainty in the 95% cleanup time estimated by coefficient of variation was approximately 0.2. Some analytical results derived for travel time moments, radial velocity variances, and effective hydraulic conductivity were compared with the numerical results.Efficient codes were developed to for the solution of three-dimensional groundwater flow and solute transport problems on supercomputers. The codes were developed for Cray Y-MP/C90 which is a shared memory vector/parallel computer and the connection machine CM-5 which is a distributed memory massively parallel computer. For the groundwater flow problem, a finite-element/finite-difference code coupled with a conjugate gradient matrix solver was developed to work efficiently on both machines. For the solute transport problem, a finite-element/finite-difference code coupled with a GMRES matrix solver and a particle tracking code were developed for both machines.U of I OnlyETDs are only available to UIUC Users without author permissio