DEVELOPMENT OF A DECISION SUPPORT SYSTEM BASED ON STOCHASTIC NONLINEAR OPTIMIZATION FOR PETROLEUM-CONTAMINATED SITE MANAGEMENT

In this study, a decision support system based on a stochastic optimization model under modeling uncertainty and parameter certainty (SOMUM-DSS) is developed for petroleum-contaminated sites management. The SOMUM-DSS incorporates scenario analysis, numerical simulation, multivariate analysis, nonlinear optimization within a decision support system. It provides an effective tool for decision makers to select the optimal remediation strategy. The developed SOMUM-DSS is then applied to a petroleum-contaminated aquifer located at the town of Kindersley in western Canada. A number of scenarios are initiated respectively corresponding to different levels of groundwater quality satisfying the environmental standard, as well as various durations of groundwater remedia-tion. The results indicate that the environmental standard and remediation duration play an important role in determining the optimal remediation strategy. The successful real-world application of the SOMUM-DSS also indicates its potential of solving other groundwater remediation problems.