Striking the balance: Long-term groundwater monitoring design for conflicting objectives

Patrick M. Reed, Barbara S. Minsker

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish (US)
Pages (from-to)140-149
Number of pages10
JournalJournal of Water Resources Planning and Management
Issue number2
StatePublished - Mar 2004


  • Design
  • Groundwater
  • Monitoring
  • Water resources management

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Geography, Planning and Development
  • Water Science and Technology
  • Management, Monitoring, Policy and Law


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