Application of a Genetic Algorithm to the Design of Groundwater Monitoring Well Networks under Conditions of Uncertainty

摘要

Monitoring networks are designed based on a newly developed methodology linking contaminant transport simulations and optimization models. Advection and dispersion simulation generates plume realizations, while the use of the Latin Hypercube Sampling accounts for uncertainty in transport parameters and in contaminant source characteristics. The optimization model using a Genetic Algorithm adequately designs a given number of wells in order to maximize the detection probability and to cover the vacant area where plumes can pass through.