Statistical methods of analyzing hydrochemical, isotopic, and hydrological data from regional aquifers

Persistent Link:
http://hdl.handle.net/10150/191115
Title:
Statistical methods of analyzing hydrochemical, isotopic, and hydrological data from regional aquifers
Author:
Samper Calvete, F. Javier(Francisco Javier),1958-
Issue Date:
1986
Publisher:
The University of Arizona.
Rights:
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
Abstract:
This dissertation is concerned with the development of mathematical aquifer models that combine hydrological, hydrochemical and isotopic data. One prerequisite for the construction of such models is that prior information about the variables and parameters be quantified in space and time by appropriate statistical methods. Various techniques using multivariate statistical data analyses and geostatistical methods are examined in this context. The available geostatistical methods are extended to deal with the problem at hand. In particular, a three-dimensional interactive geostatistical package has been developed for the estimation of intrinsic and nonintrinsic variables. This package is especially designed for groundwater applications and incorporates a maximum likelihood cross-validation method for estimating the parameters of the covariance function. Unique features of this maximum likelihood cross-validation method include: the use of an adjoint state method to compute the gradient of the likelihood function, the computation of the covariance of the parameter estimates and the use of identification criteria for the selection of a covariance model. In addition, it can be applied to data containing measurement errors, data regularized over variable lengths, and to nonintrinsic variables. The above methods of analysis are applied to synthetic data as well as hydrochemical and isotopic data from the Tucson aquifer in Arizona and the Madrid Basin in Spain. The dissertation also includes a discussion of the processes affecting the transport of dissolved constituents in groundwater, the mathematical formulation of the inverse solute transport problem and a proposed numerical method for its solution.
Type:
Dissertation-Reproduction (electronic); text
Keywords:
Hydrology.; Groundwater -- Arizona -- Tucson Region -- Mathematical models.; Groundwater -- Spain -- Madrid (Region) -- Mathematical models.
Degree Name:
Ph. D.
Degree Level:
doctoral
Degree Program:
Hydrology and Water Resources; Graduate College
Degree Grantor:
University of Arizona
Committee Chair:
Neuman, Shlomo P.

Full metadata record

DC FieldValue Language
dc.language.isoenen_US
dc.titleStatistical methods of analyzing hydrochemical, isotopic, and hydrological data from regional aquifersen_US
dc.creatorSamper Calvete, F. Javier(Francisco Javier),1958-en_US
dc.contributor.authorSamper Calvete, F. Javier(Francisco Javier),1958-en_US
dc.date.issued1986en_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.description.abstractThis dissertation is concerned with the development of mathematical aquifer models that combine hydrological, hydrochemical and isotopic data. One prerequisite for the construction of such models is that prior information about the variables and parameters be quantified in space and time by appropriate statistical methods. Various techniques using multivariate statistical data analyses and geostatistical methods are examined in this context. The available geostatistical methods are extended to deal with the problem at hand. In particular, a three-dimensional interactive geostatistical package has been developed for the estimation of intrinsic and nonintrinsic variables. This package is especially designed for groundwater applications and incorporates a maximum likelihood cross-validation method for estimating the parameters of the covariance function. Unique features of this maximum likelihood cross-validation method include: the use of an adjoint state method to compute the gradient of the likelihood function, the computation of the covariance of the parameter estimates and the use of identification criteria for the selection of a covariance model. In addition, it can be applied to data containing measurement errors, data regularized over variable lengths, and to nonintrinsic variables. The above methods of analysis are applied to synthetic data as well as hydrochemical and isotopic data from the Tucson aquifer in Arizona and the Madrid Basin in Spain. The dissertation also includes a discussion of the processes affecting the transport of dissolved constituents in groundwater, the mathematical formulation of the inverse solute transport problem and a proposed numerical method for its solution.en_US
dc.description.notehydrology collectionen_US
dc.typeDissertation-Reproduction (electronic)en_US
dc.typetexten_US
dc.subjectHydrology.en_US
dc.subjectGroundwater -- Arizona -- Tucson Region -- Mathematical models.en_US
dc.subjectGroundwater -- Spain -- Madrid (Region) -- Mathematical models.en_US
thesis.degree.namePh. D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.disciplineHydrology and Water Resourcesen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.chairNeuman, Shlomo P.en_US
dc.contributor.committeememberMyers, Donald E.en_US
dc.contributor.committeememberMaddock III, Thomasen_US
dc.contributor.committeememberSimpson, Eugene S.en_US
dc.contributor.committeememberDavis, Stanley N.en_US
dc.identifier.oclc213360459en_US
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