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dc.contributor.authorZhu, Junfeng
dc.contributor.authorYeh, Tian-Chyi J.
dc.date.accessioned2016-07-07T22:31:22Z
dc.date.available2016-07-07T22:31:22Z
dc.date.issued2004-11
dc.identifier.urihttp://hdl.handle.net/10150/615765
dc.description.abstractHydraulic tomography is a cost -effective technique for characterizing the heterogeneity of hydraulic parameters in the subsurface. During hydraulic tomography surveys, a large number of hydraulic heads (i.e., aquifer responses) are collected from a series of pumping or injection tests in an aquifer. These responses are then used to interpret the spatial distribution of hydraulic parameters of the aquifer using inverse modeling. In this study, we developed an efficient sequential successive linear estimator (SSLE) for interpreting data from transient hydraulic tomography to estimate three-dimensional hydraulic conductivity and specific storage fields of aquifers. We first explored this estimator for transient hydraulic tomography in a hypothetical one-dimensional aquifer. Results show that during a pumping test, transient heads are highly correlated with specific storage at early time but with hydraulic conductivity at late time. Therefore, reliable estimates of both hydraulic conductivity and specific storage must exploit the head data at both early and late times. Our study also shows that the transient heads are highly correlated over time, implying only infrequent head measurements are needed during the estimation. Applying this sampling strategy to a well -posed problem, we show that our SSLE can produce accurate estimates of both hydraulic conductivity and specific storage fields. The benefit of hydraulic tomography for ill -posed problems is then demonstrated. Finally, to affirm the robustness of our SSLE approach, we apply the SSLE approach to transient hydraulic tomography in a hypothetical two- dimensional aquifer with nonstationary hydraulic properties, as well as a hypothetical three-dimensional heterogeneous aquifer.
dc.language.isoen_USen
dc.publisherDepartment of Hydrology and Water Resources, University of Arizona (Tucson, AZ)en
dc.relation.ispartofseriesTechnical Reports on Hydrology and Water Resources, No. 04-01en
dc.rightsCopyright © Arizona Board of Regentsen
dc.sourceProvided by the Department of Hydrology and Water Resources.en
dc.subjecttransient hydraulic tomographyen
dc.subjectSSLEen
dc.subjectcokrigingen
dc.subjecttemporal correlationen
dc.subjecthydraulic conductivityen
dc.subjectspecific storageen
dc.titleCharacterization of aquifer heterogeneity using transient hydraulic tomographyen_US
dc.typetexten
dc.typeTechnical Reporten
dc.contributor.departmentDepartment of Hydrology & Water Resources, The University of Arizonaen
dc.description.collectioninformationThis title from the Hydrology & Water Resources Technical Reports collection is made available by the Department of Hydrology & Atmospheric Sciences and the University Libraries, University of Arizona. If you have questions about titles in this collection, please contact repository@u.library.arizona.edu.en
refterms.dateFOA2018-09-11T14:26:42Z
html.description.abstractHydraulic tomography is a cost -effective technique for characterizing the heterogeneity of hydraulic parameters in the subsurface. During hydraulic tomography surveys, a large number of hydraulic heads (i.e., aquifer responses) are collected from a series of pumping or injection tests in an aquifer. These responses are then used to interpret the spatial distribution of hydraulic parameters of the aquifer using inverse modeling. In this study, we developed an efficient sequential successive linear estimator (SSLE) for interpreting data from transient hydraulic tomography to estimate three-dimensional hydraulic conductivity and specific storage fields of aquifers. We first explored this estimator for transient hydraulic tomography in a hypothetical one-dimensional aquifer. Results show that during a pumping test, transient heads are highly correlated with specific storage at early time but with hydraulic conductivity at late time. Therefore, reliable estimates of both hydraulic conductivity and specific storage must exploit the head data at both early and late times. Our study also shows that the transient heads are highly correlated over time, implying only infrequent head measurements are needed during the estimation. Applying this sampling strategy to a well -posed problem, we show that our SSLE can produce accurate estimates of both hydraulic conductivity and specific storage fields. The benefit of hydraulic tomography for ill -posed problems is then demonstrated. Finally, to affirm the robustness of our SSLE approach, we apply the SSLE approach to transient hydraulic tomography in a hypothetical two- dimensional aquifer with nonstationary hydraulic properties, as well as a hypothetical three-dimensional heterogeneous aquifer.


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