Estimation Of Spatially Distributed Model Parameters Using A Regularization Approach

Persistent Link:
http://hdl.handle.net/10150/193379
Title:
Estimation Of Spatially Distributed Model Parameters Using A Regularization Approach
Author:
Pokhrel, Prafulla
Issue Date:
2007
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:
The high dimensionality of the parameter search space can be solved by the introduction of additional information about the parameters. In this research the information contained in the apriori parameter estimates, derived using the Koren approach (Koren et al. 2000), was used to identify regularization equations that constrain the parameter variability during the calibration process and reduce the dimension of the calibration problem. The study of spatial variability of apriori parameters with respect to the NRCS based curve numbers and the depth of soil showed some recognizable trends that could be exploited in the form of some simple regression equations. These equations, along with some inter parameter relations, were used as regularization equations. Calibration of the coefficients of the regularization equations instead of the SACSMA parameters (Burnash et al.1973) reduced the dimension of the problem from 858 to 33 unknowns and resulted in significant reduction in the objective function values.
Type:
text; Electronic Thesis
Degree Name:
MS
Degree Level:
masters
Degree Program:
Hydrology; Graduate College
Degree Grantor:
University of Arizona
Advisor:
Gupta, Hoshin V.
Committee Chair:
Gupta, Hoshin V.

Full metadata record

DC FieldValue Language
dc.language.isoENen_US
dc.titleEstimation Of Spatially Distributed Model Parameters Using A Regularization Approachen_US
dc.creatorPokhrel, Prafullaen_US
dc.contributor.authorPokhrel, Prafullaen_US
dc.date.issued2007en_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.abstractThe high dimensionality of the parameter search space can be solved by the introduction of additional information about the parameters. In this research the information contained in the apriori parameter estimates, derived using the Koren approach (Koren et al. 2000), was used to identify regularization equations that constrain the parameter variability during the calibration process and reduce the dimension of the calibration problem. The study of spatial variability of apriori parameters with respect to the NRCS based curve numbers and the depth of soil showed some recognizable trends that could be exploited in the form of some simple regression equations. These equations, along with some inter parameter relations, were used as regularization equations. Calibration of the coefficients of the regularization equations instead of the SACSMA parameters (Burnash et al.1973) reduced the dimension of the problem from 858 to 33 unknowns and resulted in significant reduction in the objective function values.en_US
dc.typetexten_US
dc.typeElectronic Thesisen_US
thesis.degree.nameMSen_US
thesis.degree.levelmastersen_US
thesis.degree.disciplineHydrologyen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.advisorGupta, Hoshin V.en_US
dc.contributor.chairGupta, Hoshin V.en_US
dc.identifier.proquest2196en_US
dc.identifier.oclc659747312en_US
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