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When assessing the risk from an underground environment that is contaminated by radioactive nuclides and hazardous chemicals and planning for remediation, the contaminant plume distribution and the associated uncertainty from measured data should be estimated accurately. While the release history of the contaminant plume may be unknown, the extent of the plume caused by a known source and the associated uncertainty can be calculated inversely from the concentration data using a geostatistical method that accounts for the temporal correlation of its release history and groundwater flow modeling. However, the preceding geostatistical approaches have three drawbacks: (1) no applications of the three-dimensional plume estimation using concentration data from multiple depths in real situations, (2) no constraints for the estimation of the plume distribution, which can yield negative concentration and large uncertainties, and (3) few applications to actual cases with multiple contaminants. To address these problems, the non-negativity constraint using Gibbs sampling was incorporated into the geostatistical method with groundwater flow modeling for contaminant plume estimation. This method was then tested on groundwater contamination in the Gloucester landfill in Ontario, Canada, using three-dimensional contaminant transport model and concentration data from multiple depths. The method was applied to three water soluble organic contaminants: 1,4-dioxane, tetrahydrofuran, and diethyl ether. The effectiveness of the proposed method was verified by the general agreement of the calculated plume distributions of the three contaminants with concentration data from 66 points in 1982 (linear correlation coefficient of about 0.7). In particular, the reproduced peak of 1,4-dioxane corresponding to the large disposal in 1978 was more accurate than the result of preceding minimum relative entropy-based studies. The same peak also appeared in the tetrahydrofuran and diethyl ether distributions approximately within the range of the retardation factor derived from the fraction of organic carbon. • Three-dimensional contaminant plume is well reproduced by a geostatistical approach. • Non-negativity constraint improves the approach with groundwater flow modeling. • Applicability of the approach is verified for 3 water soluble organic contaminants. • Unknown release history is estimated accurately for a case of actual large disposal. [ABSTRACT FROM AUTHOR]

The performance of a combined sewer overflow (CSO) storage/treatment facility in North Toronto, Ont., Canada, was investigated by conjunctive numerical and physical (hydraulic) modeling. The main objectives of the study were to (1) assess the feasibility of increasing the hydraulic loading of the CSO facility without bypassing; and (2) establish a verified numerical model of the facility for future work. The numerical model [a commercial computational fluid dynamics (CFD), PHOENICS] was validated and verified using results from a hydraulic scale model (1:11.6). The results obtained show that the CFD model can simulate hydraulic conditions in the facility well, as demonstrated by accurate reproduction of the filling rate, water levels at various locations, flow velocities in feed pipes, and overflows from the inflow channel. Numerical simulations identified excessive local head losses and helped select structural changes to reduce such losses. The analysis of the facility showed that with respect to hydraulic operation, the facility is a complex, highly nonlinear hydraulic system. Within the existing constraints, a few structural changes examined by numerical simulation could increase the maximum treatment flow rate in the CSO storage/treatment facility by up to 31%. [ABSTRACT FROM AUTHOR]