Statistical analyses and stochastic modeling of the Cortaro aquifer in southern Arizona

Persistent Link:
http://hdl.handle.net/10150/191060
Title:
Statistical analyses and stochastic modeling of the Cortaro aquifer in southern Arizona
Author:
Binsariti, Abdalla A.
Issue Date:
1980
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:
Transmissivity, specific capacity, and steady state hydraulic head data collected from the Cortaro aquifer in Southern Arizona are analyzed statistically by means of regression and Kriging techniques. The statistics obtained in this manner are used to develop a stochastic model of the aquifer based on the finite element and Monte Carlo simulation methods. Three stages of generated head uncertainties are considered; (1) non-conditional, (2) conditional on transmissivity data and (3) conditional on both transmissivity and initial hydraulic head data (or inverse method). We found that simulated head values in stage 1 and 2 are associated with high variance amounting to 144.0 ft². When the statistics obtained from regression and Kriging in stage 2 are processed by means of the statistical inverse method of Neuman (1980), the result is a drastic reduction in the input head variance amounting to 75 percent reduction in the input head variance (i.e., 144 ft²). From these results, one may conclude that in order to minimize the variance of outputs generated by stochastic aquifer models, the input into such models must be created with the aid of appropriate statistical inverse procedure.
Type:
Dissertation-Reproduction (electronic); text
Keywords:
Hydrology.; Aquifers -- Arizona -- Mathematical models.; Groundwater -- Arizona -- Mathematical models.; Stochastic analysis.
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 analyses and stochastic modeling of the Cortaro aquifer in southern Arizonaen_US
dc.creatorBinsariti, Abdalla A.en_US
dc.contributor.authorBinsariti, Abdalla A.en_US
dc.date.issued1980en_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.abstractTransmissivity, specific capacity, and steady state hydraulic head data collected from the Cortaro aquifer in Southern Arizona are analyzed statistically by means of regression and Kriging techniques. The statistics obtained in this manner are used to develop a stochastic model of the aquifer based on the finite element and Monte Carlo simulation methods. Three stages of generated head uncertainties are considered; (1) non-conditional, (2) conditional on transmissivity data and (3) conditional on both transmissivity and initial hydraulic head data (or inverse method). We found that simulated head values in stage 1 and 2 are associated with high variance amounting to 144.0 ft². When the statistics obtained from regression and Kriging in stage 2 are processed by means of the statistical inverse method of Neuman (1980), the result is a drastic reduction in the input head variance amounting to 75 percent reduction in the input head variance (i.e., 144 ft²). From these results, one may conclude that in order to minimize the variance of outputs generated by stochastic aquifer models, the input into such models must be created with the aid of appropriate statistical inverse procedure.en_US
dc.description.notehydrology collectionen_US
dc.typeDissertation-Reproduction (electronic)en_US
dc.typetexten_US
dc.subjectHydrology.en_US
dc.subjectAquifers -- Arizona -- Mathematical models.en_US
dc.subjectGroundwater -- Arizona -- Mathematical models.en_US
dc.subjectStochastic analysis.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.committeememberDavis, Stanley N.en_US
dc.contributor.committeememberSimpson, Eugene S.en_US
dc.contributor.committeememberMyers, Donald E.en_US
dc.identifier.oclc212908734en_US
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