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Environmental Monitoring and Assessment

, Volume 169, Issue 1–4, pp 133–142 | Cite as

Using a hybrid approach to optimize experimental network design for aquifer parameter identification

  • Liang-Cheng Chang
  • Hone-Jay Chu
  • Yu-Pin Lin
  • Yu-Wen Chen
Article

Abstract

This research develops an optimum design model of groundwater network using genetic algorithm (GA) and modified Newton approach, based on the experimental design conception. The goal of experiment design is to minimize parameter uncertainty, represented by the covariance matrix determinant of estimated parameters. The design problem is constrained by a specified cost and solved by GA and a parameter identification model. The latter estimates optimum parameter value and its associated sensitivity matrices. The general problem is simplified into two classes of network design problems: an observation network design problem and a pumping network design problem. Results explore the relationship between the experimental design and the physical processes. The proposed model provides an alternative to solve optimization problems for groundwater experimental design.

Keywords

Groundwater Experimental design Genetic algorithm 

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Copyright information

© Springer Science+Business Media B.V. 2009

Authors and Affiliations

  • Liang-Cheng Chang
    • 1
  • Hone-Jay Chu
    • 2
  • Yu-Pin Lin
    • 2
  • Yu-Wen Chen
    • 1
  1. 1.Department of Civil EngineeringNational Chiao Tung UniversityHsinchuTaiwan, Republic of China
  2. 2.Department of Bioenvironmental Systems EngineeringNational Taiwan UniversityTaipeiTaiwan, Republic of China

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