Calibration of the soil moisture accounting model using a gradient-type algorithm and analytic derivatives

Persistent Link:
http://hdl.handle.net/10150/191932
Title:
Calibration of the soil moisture accounting model using a gradient-type algorithm and analytic derivatives
Author:
Hendrickson, Jene Diane,1960-
Issue Date:
1987
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:
In the pest, derivative-based optimization algorithms have not frequently been used to calibrate conceptual rainfall-runoff (CRR) models, partially due to difficulties associated with obtaining the required derivatives. This research applies a recently-developed technique of analytically computing derivatives of a CRR model to a complex, widely-used CRR model. The resulting least squares response surface was found to contain numerous discontinuities in the surface and derivatives. However, the surface and its derivatives were found to be everywhere finite, permitting the use of derivative-based optimization algorithms. Finite difference numeric derivatives were computed and found to be virtually identical to analytic derivatives. A comparison was made between gradient (Newton-Raphson) and direct (pattern search) optimization algorithms. The pattern search algorithm was found to be more robust. The lower robustness of the Newton-Raphson algorithm was thought to be due to discontinuities and a rough texture of the response surface.
Type:
Thesis-Reproduction (electronic); text
LCSH Subjects:
Hydrology.; Soil moisture -- Measurement.
Degree Name:
M.S.
Degree Level:
masters
Degree Program:
Hydrology and Water Resources; Graduate College
Degree Grantor:
University of Arizona
Committee Chair:
Sorooshian, Soroosh

Full metadata record

DC FieldValue Language
dc.language.isoenen_US
dc.titleCalibration of the soil moisture accounting model using a gradient-type algorithm and analytic derivativesen_US
dc.creatorHendrickson, Jene Diane,1960-en_US
dc.contributor.authorHendrickson, Jene Diane,1960-en_US
dc.date.issued1987en_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.abstractIn the pest, derivative-based optimization algorithms have not frequently been used to calibrate conceptual rainfall-runoff (CRR) models, partially due to difficulties associated with obtaining the required derivatives. This research applies a recently-developed technique of analytically computing derivatives of a CRR model to a complex, widely-used CRR model. The resulting least squares response surface was found to contain numerous discontinuities in the surface and derivatives. However, the surface and its derivatives were found to be everywhere finite, permitting the use of derivative-based optimization algorithms. Finite difference numeric derivatives were computed and found to be virtually identical to analytic derivatives. A comparison was made between gradient (Newton-Raphson) and direct (pattern search) optimization algorithms. The pattern search algorithm was found to be more robust. The lower robustness of the Newton-Raphson algorithm was thought to be due to discontinuities and a rough texture of the response surface.en_US
dc.description.notehydrology collectionen_US
dc.typeThesis-Reproduction (electronic)en_US
dc.typetexten_US
dc.subject.lcshHydrology.en_US
dc.subject.lcshSoil moisture -- Measurement.en_US
thesis.degree.nameM.S.en_US
thesis.degree.levelmastersen_US
thesis.degree.disciplineHydrology and Water Resourcesen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.chairSorooshian, Sorooshen_US
dc.identifier.oclc213340158en_US
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