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Design of groundwater monitoring networks (GMN) of an aquifer has been one of the key concerns of researchers who deal with the management of groundwater contamination. To control, prevent, and remediation groundwater contamination, large number of monitoring well locations is required in a 3-D transient system. A state of the art groundwater monitoring network design, which combines groundwater flow and transport results with a Genetic Algorithm optimization procedure to identify optimal monitoring well location in 3-D, is presented in this book. The design approach differs from other (GMN)designs by placing the emphasis on maximizing the probability of tracking a transient contamination plume by determining sequential monitoring locations. It also addresses the issue of enhancing modelling accuracy when the hydrogeologic and hydrochemical data such as contaminant concentration measurement data are sparse. The groundwater contamination simulation results are introduced as input to the optimization model (Genetic Algorithm) to identify the groundwater optimal monitoring network design, based on several candidate monitoring locations.

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Ph.D (Civil Engineering, Dalhousie University, Halifax, NS, Canada) MSc. (Civil Engineering, University of Waterloo, Waterloo, ON, Canada) BSc. (Shahid Chamran University, Ahwaz, Iran) Assistant Professor at: Research Institute of Water Scarcity and Drought, Tehran, Iran

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