AN ITERATIVE STOCHASTIC INVERSE METHOD: CONDITIONAL EFFECTIVE TRANSMISSIVITY AND HYDRAULIC HEAD FIELDS

Persistent Link:
http://hdl.handle.net/10150/614150
Title:
AN ITERATIVE STOCHASTIC INVERSE METHOD: CONDITIONAL EFFECTIVE TRANSMISSIVITY AND HYDRAULIC HEAD FIELDS
Author:
Yeh, T.-C. Jim; Jin, Minghui; Hanna, Samuel
Affiliation:
Department of Hydrology & Water Resources, The University of Arizona
Publisher:
Department of Hydrology and Water Resources, University of Arizona (Tucson, AZ)
Issue Date:
1995-08-29
Rights:
Copyright © Arizona Board of Regents
Collection Information:
This 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.
Abstract:
An iterative stochastic approach is developed to estimate transmissivity and head distributions in heterogeneous aquifers. This approach is similar to the classical cokriging technique and it uses a linear estimator that depends on the covariances of transmissivity and hydraulic head and their cross -covariance. The linear estimator is, however, improved successively by solving the governing flow equation and by updating the covariances and cross -covariance function of transmissivity and hydraulic head fields in an iterative manner. As a result, the nonlinear relationship between transmissivity and head is incorporated in the estimation and the estimated fields are approximate conditional means. The ability of the iterative approach is tested with some deterministic and stochastic inverse problems. The results show that the estimated transmissivity and hydraulic head fields have smaller mean square errors than those obtained by classical cokriging even in the aquifer with variance of transmissivity up to 3.
Series/Report no.:
Technical Reports on Hydrology and Water Resources, No. 95-030

Full metadata record

DC FieldValue Language
dc.contributor.authorYeh, T.-C. Jimen
dc.contributor.authorJin, Minghuien
dc.contributor.authorHanna, Samuelen
dc.date.accessioned2016-06-22T18:17:39Z-
dc.date.available2016-06-22T18:17:39Z-
dc.date.issued1995-08-29-
dc.identifier.urihttp://hdl.handle.net/10150/614150-
dc.description.abstractAn iterative stochastic approach is developed to estimate transmissivity and head distributions in heterogeneous aquifers. This approach is similar to the classical cokriging technique and it uses a linear estimator that depends on the covariances of transmissivity and hydraulic head and their cross -covariance. The linear estimator is, however, improved successively by solving the governing flow equation and by updating the covariances and cross -covariance function of transmissivity and hydraulic head fields in an iterative manner. As a result, the nonlinear relationship between transmissivity and head is incorporated in the estimation and the estimated fields are approximate conditional means. The ability of the iterative approach is tested with some deterministic and stochastic inverse problems. The results show that the estimated transmissivity and hydraulic head fields have smaller mean square errors than those obtained by classical cokriging even in the aquifer with variance of transmissivity up to 3.en
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. 95-030en
dc.rightsCopyright © Arizona Board of Regentsen
dc.sourceProvided by the Department of Hydrology and Water Resources.en
dc.titleAN ITERATIVE STOCHASTIC INVERSE METHOD: CONDITIONAL EFFECTIVE TRANSMISSIVITY AND HYDRAULIC HEAD FIELDSen_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
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