Three-Dimensional Groundwater Contamination Source Identification Using Adaptive Simulated Annealing
Publication: Journal of Hydrologic Engineering
Volume 18, Issue 3
Abstract
Determination of groundwater contaminant source characteristics such as release histories of unknown groundwater pollutant sources from concentration observation data is an inverse problem. Often solution to this inverse problem is nonunique, and it is an ill-posed problem. A linked simulation-optimization approach can be used to solve this problem efficiently. However, this approach is computationally intensive, and the results obtained tend to be highly susceptible to errors in the measured data and estimated hydrogeological parameters. Apart from this, accuracy of the solutions is highly dependent on the choice of monitoring locations. An adaptive simulated annealing (ASA)-based solution algorithm is shown to be computationally efficient for optimal identification of the source characteristics in terms of execution time and accuracy. This computational efficiency appears to prevail even with moderate levels of errors in estimated parameters and concentration measurement errors. Also, the contaminant concentration monitoring locations are shown to be critical in the efficient characterization of the unknown contaminant sources. Optimal identification results for different monitoring networks are presented to demonstrate the relevance of a network suitable for efficient source identification.
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Information
Published In
Journal of Hydrologic Engineering
Volume 18 • Issue 3 • March 2013
Pages: 307 - 317
Copyright
© 2013 American Society of Civil Engineers.
History
Received: Mar 22, 2011
Accepted: Mar 23, 2012
Published online: Mar 26, 2012
Published in print: Mar 1, 2013
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