Reliability-based uncertainty analysis of groundwater contaminant transport and remediation

Failure to rigorously accommodate physical parameter uncertainty in groundwater transport models casts serious doubts on our ability to accurately delineate the contaminant plume at a given site. This failure could also considerably reduce the possibility of success of the remediation scheme intended to clean up a plume within the specified time.; In this research, the probability that a contaminant leaking from a waste source will exceed some predetermined target level at a downgradient well is estimated, along with the sensitivity of this probability to the basic uncertainty in input parameters. The relevant parameters are assumed random with prescribed probability distributions.; In this work, we present a probabilistic modeling tool based on first- and second-order reliability methods (FORM and SORM) to account for parameter uncertainty in groundwater contaminant transport and remediation. The methodology is applied to analytical groundwater models to provide simple screening tool for the assessment of contamination and remediation. In addition, numerical-based reliability models are developed to account for aquifer spatial heterogeneity and correlation structure in a more complex system.; In the analytical phase, the program PROBAN was used for the probabilistic analysis. Results indicate that the greatest impact on the probabilistic event is due to basic uncertainty in seepage velocity. However, chemical-related and source-related parameter uncertainty were also found to be very important factors to consider. In the numerical phase, the finite-element code FLOTRAN was linked to the reliability shell CALREL. Hydraulic conductivity was treated as a spatial random field. Considerable saving in computational time was achieved by using a coarse random variables mesh with a finer numerical mesh. Series system reliability was used to analyze failure at several wells. Probabilistic assessment of plume containment was also provided.; FORM and SORM are powerful tools for the probabilistic analysis of groundwater contaminant transport and remediation. Examples given in this work are only samples of the variety of applications that FORM and SORM can address. Their use in areas such as probabilistic risk assessment should be of great potential and interest to regulatory agencies and groundwater modelers alike.