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

Research output: Contribution to journalArticle

1 Citation (Scopus)

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.

Original languageEnglish
Pages (from-to)133-142
Number of pages10
JournalEnvironmental Monitoring and Assessment
Volume169
Issue number1-4
DOIs
Publication statusPublished - 2010 Oct

All Science Journal Classification (ASJC) codes

  • Environmental Science(all)
  • Pollution
  • Management, Monitoring, Policy and Law

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