Striking the Balance: Long-Term Groundwater Monitoring Design for Conflicting Objectives
Publication: Journal of Water Resources Planning and Management
Volume 130, Issue 2
Abstract
This study demonstrates the use of high-order Pareto optimization (i.e., optimizing a system for more than two objectives) on a long-term monitoring (LTM) application. The LTM application combines quantile kriging and the nondominated sorted genetic algorithm-II (NSGA-II) to successfully balance four objectives: (1) minimizing sampling costs, (2) maximizing the accuracy of interpolated plume maps, (3) maximizing the relative accuracy of contaminant mass estimates, and (4) minimizing estimation uncertainty. Optimizing the LTM application with respect to these objectives reduced the decision space of the problem from a total of 500 million designs to a set of 1,156 designs identified on the Pareto surface. Visualization of a total of eight designs aided in understanding and balancing the objectives of the application en route to a single compromise solution. This study shows that high-order Pareto optimization holds significant potential as a tool that can be used in the balanced design of water resources systems.
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Information
Published In
Journal of Water Resources Planning and Management
Volume 130 • Issue 2 • March 2004
Pages: 140 - 149
Copyright
Copyright © 2004 American Society of Civil Engineers.
History
Received: Apr 22, 2002
Accepted: Apr 18, 2003
Published online: Feb 19, 2004
Published in print: Mar 2004
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