PROBABILISTIC SCREENING TOOL FOR GROUNDWATER CONTAMINATION ASSESSMENT

This paper presents a methodology for assessing the effects of source- , chemical-, and aquifer-related parameter uncertainty on the response of a semianalytical transport model using first- and second-order rel iability methods. A probabilistic model is developed by coupling the d eterministic transport model with a general-purpose probability analys is program. Ground-water contamination risk is addressed by evaluating the probability that a given contaminant exceeds the regulated standa rds at a well downgradient from a waste source. The general applicabil ity of the methodology is demonstrated on two simple hypothetical case studies of transport of nonreactive and reactive solutes in the subsu rface. Sensitivities of the probabilistic outcome to the basic uncerta inties in the input random variables are provided through importance f actors. The reliability-method results are checked against those obtai ned using the classical Monte Carlo-simulation method, and the results are in good agreement except for very low probability events in which the reliability methods provide accurate results much more efficientl y than the Monte Carlo method. The need for a careful trade-off analys is between accuracy and computer time is highlighted.