Groundwater Remediation Strategy Using Global Optimization Algorithms
Publication: Journal of Water Resources Planning and Management
Volume 128, Issue 6
Abstract
The remediation of groundwater contamination by pumping and injection is generally a long-term and costly strategy. Aquifer cleanup time is a highly nonlinear and nonconvex function of pumping rates. The cleanup objective often involves minimizing or constraining the cleanup time or cleanup cost. Linear programming and nonlinear optimization cannot guarantee the global solution. In this study, four global optimization (GO) algorithms, including a popular genetic algorithm, are used to minimize both cleanup time and cleanup cost taking pumping rates and/or well locations as decision variables. Groundwater flow and particle-tracking models (MODFLOW and MODPATH) and a GO tool (GLOBE) are used. Real and hypothetical contaminated aquifers are considered for application. The results are satisfactory and show that GO techniques can be widely applied in groundwater remediation strategy and planning. The comparison of the performance of algorithms did not reveal a clear winner. The results also show that in the particle-tracking method, excluding few particles from removal can significantly reduce the cleanup time.
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Information & Authors
Information
Published In
Journal of Water Resources Planning and Management
Volume 128 • Issue 6 • November 2002
Pages: 431 - 440
Copyright
Copyright © 2002 American Society of Civil Engineers.
History
Received: Sep 27, 1999
Accepted: Oct 4, 2001
Published online: Oct 15, 2002
Published in print: Nov 2002
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