Teaches, using simple analytical models how physical, chemical, and biological processes in the subsurface affect contaminant transport Uses simple analytical models to demonstrate the impact of subsurface processes on the fate and transport of groundwater contaminants Includes downloadable modeling tool that provides easily understood graphical output for over thirty models Modeling tool and book are integrated to facilitate reader understanding Collects analytical solutions from many sources into a single volume and, for the interested reader, shows how these solutions are derived from the governing model equations

This book presents, in an accessible and self-consistent way, the theory of diffusion in random velocity fields, together with robust numerical simulation approaches. The focus is on transport processes in natural porous media, with applications to contaminant transport in groundwater. Starting from basic information on stochastic processes, more challenging issues are subsequently addressed, such as the correlation structure of the diffusion process in random fields, the relation between memory effects and ergodic properties, derivation and parameterizations of evolution equations for probability densities, and the relation between measurements and spatio-temporal upscaling. Written for readers with a background in applied mathematics, engineering, physics or geophysics, the book offers an essential basis for further research in the stochastic modeling of groundwater systems.

This research project investigated the coupled effects of uncertain contaminant source morphology (organic immiscible liquids distribution and composition) and aquifer properties on predicting solute transport in saturated groundwater systems contaminated with residual Organic Immiscible Liquids (OIL's). Research efforts focused on the development of multiple stochastic inverse models for characterizing contaminant fluxes in the near field and for characterizing NAPL distributions within source. In addition, work was conducted on the forward stochastic modeling, that is, to evaluate individual and collective impacts of uncertain spatially and temporally variable source morphological characteristics on subsurface solute transport predictions. The study also involved 1-, 2-, and 3-dimensional experimental efforts to study bench-scale and intermediate-scale uncertainties associate with OIL sources. These studies focused on describing dissolution from multi-component OIL's at varying residual fluid saturations and distributions, and the characterization of OIL sources using partitioning and interfacial tracers. As a final component of the project, the various stochastic models developed were evaluated using data from the pilot-scale field experiments conducted at Hill AFB, Columbus AFB, and Base Borden, Ontario, Canada. Data derived from partitioning/interfacial tracers and far-field dissolved OIL component distributions were used with the stochastic models to characterize OIL sources at each site.