An Iterative Geostatistical Inverse Method For Steady-Flow In The Vadose Zone

Persistent Link:
http://hdl.handle.net/10150/614010
Title:
An Iterative Geostatistical Inverse Method For Steady-Flow In The Vadose Zone
Author:
Zhang, Jinqi; Yeh, T.-C. Jim
Affiliation:
Department of Hydrology & Water Resources, The University of Arizona
Publisher:
Department of Hydrology and Water Resources, University of Arizona (Tucson, AZ)
Issue Date:
1996-02-01
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 inverse technique utilizing both primary and secondary information is developed to estimate conditional means of unsaturated hydraulic conductivity parameters (saturated hydraulic conductivity and pore -size distribution parameters) in the vadose zone. Measurements of saturated hydraulic conductivity and pore -size distribution parameter are considered as the primary information, while measurements of steady -state flow processes (soil -water pressure head and degree of saturation) are regarded as the secondary information. This inverse approach is similar to the classical geostatistical approach, which utilizing a linear estimator that depends on the cross- covariance and covariance functions of unsaturated hydraulic conductivity parameters and flow processes. The linear estimator is, however, improved successively by solving the governing flow equation and by updating the residual covariance and cross- covariance functions, in an iterative manner. Using an approximate perturbation solution for steady, variably saturated flow under general boundary conditions, the covariances of secondary information and the cross -covariance between the primary and secondary information are derived. The approximate solution is formulated based on a first -order Taylor series expansion of a discretized finite element equation. The sensitivity matrices in the solution are evaluated by an adjoint state sensitivity approach for flow in heterogeneous media under variably saturated conditions. As a result, the nonlinear relationships between unsaturated hydraulic conductivity parameters and flow processes are incorporated in the estimation. Through some numerical examples, the iterative inverse model demonstrates its ability to improve the estimates of the spatial distribution of saturated hydraulic conductivity and pore -size distribution parameters compared to the classical geostatistical inverse approach. In addition, the inconsistency problem existing in classical geostatistical inverse approach is alleviated. The estimated fields of unsaturated hydraulic conductivity parameters and flow fields not only retain their observed values at sample locations, but satisfy the governing flow equation as well.
Series/Report no.:
Technical Reports on Hydrology and Water Resources, No.96-020

Full metadata record

DC FieldValue Language
dc.contributor.authorZhang, Jinqien
dc.contributor.authorYeh, T.-C. Jimen
dc.date.accessioned2016-06-21T23:20:42Z-
dc.date.available2016-06-21T23:20:42Z-
dc.date.issued1996-02-01-
dc.identifier.urihttp://hdl.handle.net/10150/614010-
dc.description.abstractAn iterative stochastic inverse technique utilizing both primary and secondary information is developed to estimate conditional means of unsaturated hydraulic conductivity parameters (saturated hydraulic conductivity and pore -size distribution parameters) in the vadose zone. Measurements of saturated hydraulic conductivity and pore -size distribution parameter are considered as the primary information, while measurements of steady -state flow processes (soil -water pressure head and degree of saturation) are regarded as the secondary information. This inverse approach is similar to the classical geostatistical approach, which utilizing a linear estimator that depends on the cross- covariance and covariance functions of unsaturated hydraulic conductivity parameters and flow processes. The linear estimator is, however, improved successively by solving the governing flow equation and by updating the residual covariance and cross- covariance functions, in an iterative manner. Using an approximate perturbation solution for steady, variably saturated flow under general boundary conditions, the covariances of secondary information and the cross -covariance between the primary and secondary information are derived. The approximate solution is formulated based on a first -order Taylor series expansion of a discretized finite element equation. The sensitivity matrices in the solution are evaluated by an adjoint state sensitivity approach for flow in heterogeneous media under variably saturated conditions. As a result, the nonlinear relationships between unsaturated hydraulic conductivity parameters and flow processes are incorporated in the estimation. Through some numerical examples, the iterative inverse model demonstrates its ability to improve the estimates of the spatial distribution of saturated hydraulic conductivity and pore -size distribution parameters compared to the classical geostatistical inverse approach. In addition, the inconsistency problem existing in classical geostatistical inverse approach is alleviated. The estimated fields of unsaturated hydraulic conductivity parameters and flow fields not only retain their observed values at sample locations, but satisfy the governing flow equation as well.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.96-020en
dc.rightsCopyright © Arizona Board of Regentsen
dc.sourceProvided by the Department of Hydrology and Water Resources.en
dc.titleAn Iterative Geostatistical Inverse Method For Steady-Flow In The Vadose Zoneen_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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