Use of Genetic Programming Based Surrogate Models to Simulate Complex Geochemical Transport Processes in Contaminated Mine Sites

Abstract

Reactive transport of chemical species in contaminated groundwater systems, especially with multiple species, is a complex and highly non-linear geochemical process. Simulation of such complex geochemical processes using efficient numerical models is generally computationally intensive. In order to increase the model reliability for real field data, uncertainties in hydrogeological parameters and boundary conditions are needed to be considered as well. The development and performance evaluation of ensemble Genetic Programming (GP) models to serve as computationally efficient approximate simulators of complex groundwater contaminant transport process with reactive chemical species under aquifer parameters uncertainties are presented. The GP models are developed by training and testing of the models using sets of random input contaminated sources and the corresponding aquifer responses in terms of resulting spatio-temporal concentrations of the contaminants obtained as solution of the hydrogeological and geochemical numerical simulation model. Three dimensional transient flow and reactive contaminant transport process is considered. Performance evaluation of the ensemble GP models as surrogate models for the reactive species transport in groundwater demonstrates the feasibility of its use and the associated computational advantages. The evaluation results show that it is feasible to use ensemble GP models as approximate simulators of complex hydrogeologic and geochemical processes in a contaminated groundwater aquifer incorporating uncertainties in describing the physical system.