Robust estimation of parameters in nonlinear subsurface flow models using adjoint state methods.

Persistent Link:
http://hdl.handle.net/10150/185329
Title:
Robust estimation of parameters in nonlinear subsurface flow models using adjoint state methods.
Author:
Wittmeyer, Gordon William
Issue Date:
1990
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:
Estimating the parameters of groundwater flow models by automatic calibration methods is an extremely difficult problem, but one which must be solved in order to produce reliable model predictions. The data upon which the model is calibrated are usually corrupted by measurement and model structure errors which can unduly affect the values of the parameter estimates. In this dissertation the statistically robust M-estimator of Huber is used to reduce the influence of large, outlying errors in the measured head data on the values of the estimated model parameters. The robust estimation procedure is implemented in a computer program which models unconfined, steady-state and transient flow as described by the Boussinesq equation for Dupuit-type flow. The program allows the user to estimate hydraulic conductivity, specific yield, specific storage, recharge rates, leakances, boundary heads and boundary fluxes. The nonlinear error criterion is minimized using conjugate gradient and quasi-Newton methods coupled with both accurate and innaccurate line search algorithms. The gradient of the error criterion is efficiently computed by using the adjoint state finite element method. Monte Carlo studies of a synthetic aquifer model are used to demonstrate the superior efficiency of the Huber M-estimator to that of ordinary least squares. The method is also applied to a large scale inverse modeling study of the Tucson basin regional aquifer.
Type:
text; Dissertation-Reproduction (electronic)
Degree Name:
Ph.D.
Degree Level:
doctoral
Degree Program:
Hydrology and Water Resources; Graduate College
Degree Grantor:
University of Arizona
Advisor:
Neuman, Shlomo P.

Full metadata record

DC FieldValue Language
dc.language.isoenen_US
dc.titleRobust estimation of parameters in nonlinear subsurface flow models using adjoint state methods.en_US
dc.creatorWittmeyer, Gordon Williamen_US
dc.contributor.authorWittmeyer, Gordon Williamen_US
dc.date.issued1990en_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.abstractEstimating the parameters of groundwater flow models by automatic calibration methods is an extremely difficult problem, but one which must be solved in order to produce reliable model predictions. The data upon which the model is calibrated are usually corrupted by measurement and model structure errors which can unduly affect the values of the parameter estimates. In this dissertation the statistically robust M-estimator of Huber is used to reduce the influence of large, outlying errors in the measured head data on the values of the estimated model parameters. The robust estimation procedure is implemented in a computer program which models unconfined, steady-state and transient flow as described by the Boussinesq equation for Dupuit-type flow. The program allows the user to estimate hydraulic conductivity, specific yield, specific storage, recharge rates, leakances, boundary heads and boundary fluxes. The nonlinear error criterion is minimized using conjugate gradient and quasi-Newton methods coupled with both accurate and innaccurate line search algorithms. The gradient of the error criterion is efficiently computed by using the adjoint state finite element method. Monte Carlo studies of a synthetic aquifer model are used to demonstrate the superior efficiency of the Huber M-estimator to that of ordinary least squares. The method is also applied to a large scale inverse modeling study of the Tucson basin regional aquifer.en_US
dc.typetexten_US
dc.typeDissertation-Reproduction (electronic)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.advisorNeuman, Shlomo P.en_US
dc.contributor.committeememberMaddock, Thomas, IIIen_US
dc.contributor.committeememberYeh, T.-C. Jimen_US
dc.contributor.committeememberWright, A. Larryen_US
dc.contributor.committeememberAskin, Ronald G.en_US
dc.identifier.proquest9114076en_US
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