Characterization of Parameters for a Spatially Heterogenous Aquifer from Pumping Test Data
Publication: Journal of Hydrologic Engineering
Volume 19, Issue 6
Abstract
This study considers the estimation of aquifer parameters for a spatially heterogenous aquifer from pumping test data. An approach is proposed that is based on modeling the unknown parameters as smooth Markov random fields. The associated inverse problem is formulated using the Bayesian framework and the posterior probability distribution of parameters is explored using Markov chain Monte Carlo. The method is evaluated by a numerical simulation in which measurements are taken in four observation wells. Even such a minimalist example presents significant computational challenges. Therefore, to obtain a computationally feasible solution, a model reduction is carried out and the estimation problem is reduced from over 1,000 parameters to 40 parameters. The approximate posterior distribution is then sampled using an adaptive Markov chain Monte Carlo sampler in order to quantify parameter uncertainty. This paper compares the parameter with predictive uncertainty and discusses the consequences of the model reduction.
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Acknowledgments
The authors would like to acknowledge their appreciation to Sam Falle and to three reviewers for some very helpful discussions and feedback on this work.
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Published In
Journal of Hydrologic Engineering
Volume 19 • Issue 6 • June 2014
Pages: 1203 - 1213
Copyright
© 2013 American Society of Civil Engineers.
History
Received: Oct 21, 2012
Accepted: Jun 27, 2013
Published online: Jul 1, 2013
Discussion open until: Dec 1, 2013
Published in print: Jun 1, 2014
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