Time Varying Optimization for Monitoring Multiple Contaminants under Uncertain Hydrogeology

ABSTRACT

This study presents a method for identifying cost effective sampling designs for long-term monitoring of remediation of groundwater over multiple monitoring periods under uncertain flow conditions. A contaminant transport model is used to simulate plume migration under many equally likely stochastic hydraulic conductivity fields and provides representative samples of contaminant concentrations. Monitoring costs are minimized under a constraint to meet an acceptable level of error in the estimation of total mass for multiple contaminants simultaneously over many equiprobable realizations of hydraulic conductivity field. A new myopic heuristic algorithm (MS-ER) that combines a new error-reducing search neighborhood is developed to solve the optimization problem. A simulated annealing algorithm using the error-reducing neighborhood (SA-ER) and a genetic algorithm (GA) are also considered for solving the optimization problem. The method is applied to a hypothetical aquifer where enhanced anaerobic bioremediation of four toxic chlorinated ethene species is modeled using a complex contaminant transport model. The MS-ER algorithm consistently performed better in multiple trials of each algorithm when compared to SA-ER and GA. The best design of MS-ER algorithm produced a savings of nearly 25% in project cost over a conservative sampling plan that uses all possible locations and samples.

Keywords:

• groundwater
• monitoring
• multi-species
• uncertainty
• optimization
• heuristic algorithms
• chlorinated ethenes
• bioremediation
• anaerobic

ACKNOWLEDGEMENTS

This work was funded by National Science Foundation Award BES–0229176 to Christine Shoemaker from the Environmental Engineering Program. The authors are grateful to Patrick Reed of Pennsylvania State University for his suggestion on interpolation methods, and Bryan Tolson of Cornell University for his constructive comments and suggestions. We thank three anonymous reviewers for their thoughtful comments.

Notes

^a All biokinetic parameters are applicable at 25°C.

^a Average value over 5 trials.

^b Represents a conservative strategy that installs all wells and samples from every installed well during all monitoring periods.

^a Average and std. deviation values based on results from five trials.

^b Rounded off to the nearest integer.