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Contaminant release history identification in 2-D heterogeneous aquifers through a minimum relative entropy approach

The minimum relative entropy (MRE) method has been applied in a wide variety of fields since it was first introduced. Woodbury and Ulrych (Water Resour Res 29(8): 2847–2860, 1993, Water Resour Res 32(9): 2671–2681, 1996) adopted and improved this method to solve linear inverse problems in aquifers....

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Autores principales: Cupola, Fausto, Tanda, Maria Giovanna, Zanini, Andrea
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4628610/
https://www.ncbi.nlm.nih.gov/pubmed/26543790
http://dx.doi.org/10.1186/s40064-015-1465-x
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author Cupola, Fausto
Tanda, Maria Giovanna
Zanini, Andrea
author_facet Cupola, Fausto
Tanda, Maria Giovanna
Zanini, Andrea
author_sort Cupola, Fausto
collection PubMed
description The minimum relative entropy (MRE) method has been applied in a wide variety of fields since it was first introduced. Woodbury and Ulrych (Water Resour Res 29(8): 2847–2860, 1993, Water Resour Res 32(9): 2671–2681, 1996) adopted and improved this method to solve linear inverse problems in aquifers. In this work, the MRE method was improved to detect the source release history in 2-D aquifer characterized by a non-uniform flow-field. The approach was tested on two cases: a 2-D homogeneous conductivity field and a heterogeneous one (the hydraulic conductivity presents three orders of magnitude in terms of variability). In the latter case the transfer function cannot be described with an analytical formulation, thus, the transfer functions were estimated by means of a numerical procedure. In order to analyze the method performance in different conditions, two datasets have been used: observations collected at the same time at 20 different monitoring points, and observations collected at 2 monitoring points at several times. The observed data have been processed with and without a random error and the Boxcar and Gaussian probability distribution functions were considered as a priori information. The agreement between the true and the estimated data has been evaluated through the calculation of the normalized Root Mean Square error. The approach was able to recover the release history even in the most difficult case.
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spelling pubmed-46286102015-11-05 Contaminant release history identification in 2-D heterogeneous aquifers through a minimum relative entropy approach Cupola, Fausto Tanda, Maria Giovanna Zanini, Andrea Springerplus Research The minimum relative entropy (MRE) method has been applied in a wide variety of fields since it was first introduced. Woodbury and Ulrych (Water Resour Res 29(8): 2847–2860, 1993, Water Resour Res 32(9): 2671–2681, 1996) adopted and improved this method to solve linear inverse problems in aquifers. In this work, the MRE method was improved to detect the source release history in 2-D aquifer characterized by a non-uniform flow-field. The approach was tested on two cases: a 2-D homogeneous conductivity field and a heterogeneous one (the hydraulic conductivity presents three orders of magnitude in terms of variability). In the latter case the transfer function cannot be described with an analytical formulation, thus, the transfer functions were estimated by means of a numerical procedure. In order to analyze the method performance in different conditions, two datasets have been used: observations collected at the same time at 20 different monitoring points, and observations collected at 2 monitoring points at several times. The observed data have been processed with and without a random error and the Boxcar and Gaussian probability distribution functions were considered as a priori information. The agreement between the true and the estimated data has been evaluated through the calculation of the normalized Root Mean Square error. The approach was able to recover the release history even in the most difficult case. Springer International Publishing 2015-10-31 /pmc/articles/PMC4628610/ /pubmed/26543790 http://dx.doi.org/10.1186/s40064-015-1465-x Text en © Cupola et al. 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Research
Cupola, Fausto
Tanda, Maria Giovanna
Zanini, Andrea
Contaminant release history identification in 2-D heterogeneous aquifers through a minimum relative entropy approach
title Contaminant release history identification in 2-D heterogeneous aquifers through a minimum relative entropy approach
title_full Contaminant release history identification in 2-D heterogeneous aquifers through a minimum relative entropy approach
title_fullStr Contaminant release history identification in 2-D heterogeneous aquifers through a minimum relative entropy approach
title_full_unstemmed Contaminant release history identification in 2-D heterogeneous aquifers through a minimum relative entropy approach
title_short Contaminant release history identification in 2-D heterogeneous aquifers through a minimum relative entropy approach
title_sort contaminant release history identification in 2-d heterogeneous aquifers through a minimum relative entropy approach
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4628610/
https://www.ncbi.nlm.nih.gov/pubmed/26543790
http://dx.doi.org/10.1186/s40064-015-1465-x
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