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.

The scales of concern in subsurface transport of contaminants from low-level radioactive waste disposal facilities are in the range of 1 to 1,000 m. Natural geologic materials generally show very substantial spatial variability in hydraulic properties over this range of scales. Such heterogeneity can significantly influence the migration of contaminants. It is also envisioned that complex earth structures will be constructed to isolate the waste and minimize infiltration of water into the facility. The flow of water and gases through such facilities must also be a concern. A stochastic theory describing unsaturated flow and contamination transport in naturally heterogeneous soils has been enhanced by adopting a more realistic characterization of soil variability. The enhanced theory is used to predict field-scale effective properties and variances of tension and moisture content. Applications illustrate the important effects of small-scale heterogeneity on large-scale anisotropy and hysteresis and demonstrate the feasibility of simulating two-dimensional flow systems at time and space scales of interest in radioactive waste disposal investigations. Numerical algorithms for predicting field scale unsaturated flow and contaminant transport have been improved by requiring them to respect fundamental physical principles such as mass conservation. These algorithms are able to provide realistic simulations of systems with very dry initial conditions and high degrees of heterogeneity. Numerical simulation of the movement of water and air in unsaturated soils has demonstrated the importance of air pathways for contaminant transport. The stochastic flow and transport theory has been used to develop a systematic approach to performance assessment and site characterization. Hypothesis-testing techniques have been used to determine whether model predictions are consistent with observed data.

The Intergovernmental Panel on Climate Change (IPCC) is the leading international body for assessing the science related to climate change. It provides policymakers with regular assessments of the scientific basis of human-induced climate change, its impacts and future risks, and options for adaptation and mitigation. This IPCC Special Report on the Ocean and Cryosphere in a Changing Climate is the most comprehensive and up-to-date assessment of the observed and projected changes to the ocean and cryosphere and their associated impacts and risks, with a focus on resilience, risk management response options, and adaptation measures, considering both their potential and limitations. It brings together knowledge on physical and biogeochemical changes, the interplay with ecosystem changes, and the implications for human communities. It serves policymakers, decision makers, stakeholders, and all interested parties with unbiased, up-to-date, policy-relevant information. This title is also available as Open Access on Cambridge Core.

Advanced-level view of the tools of random processes and field theory as applied to the analysis and synthesis of hydrologic phenomena. Topics include time-series analysis, optimal estimation, optimal interpolation (Kriging), frequency-domain analysis of signals, and linear systems theory. Techniques and examples chosen to illustrate the latest advances in hydrologic signal analysis. Useable as graduate-level text in water resource systems, stochastic hydrology, random processes and signal analysis. 202 illustrations.