Development and validation of a new maximum likelihood criterion suitable for data collected at unequal time intervals

Persistent Link:
http://hdl.handle.net/10150/191948
Title:
Development and validation of a new maximum likelihood criterion suitable for data collected at unequal time intervals
Author:
Duan, Qingyun,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:
A new Maximum Likelihood Criterion (MLE) suitable for data which are recorded at unequal time intervals and contain auto-correlated errors is developed. Validation of the new MLE criterion has been carried out both on a simple twoparameter reservoir model using synthetical data and on a more complicated hillslope model using real data from the Pukeiti Catchment in New Zealand. Comparison between the new MLE criterion and the Simple Least Squares (SLS) criterion reveals the superiority of the former over the latter. Comparison made between the new MLE and the MLE for auto-correlated case proposed by Sorooshian in 1978 has shown that both criteria would yield results with no practical difference if equal time interval data were used. However, the new MLE can work on variable time interval data which provide more information than equal time interval data, and therefore produces better visual results in hydrologic simulations.
Type:
Thesis-Reproduction (electronic); text
LCSH Subjects:
Hydrology.; Floods -- Mathematical models.; Rivers -- Mathematical models.
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.titleDevelopment and validation of a new maximum likelihood criterion suitable for data collected at unequal time intervalsen_US
dc.creatorDuan, Qingyun,1960-en_US
dc.contributor.authorDuan, Qingyun,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.abstractA new Maximum Likelihood Criterion (MLE) suitable for data which are recorded at unequal time intervals and contain auto-correlated errors is developed. Validation of the new MLE criterion has been carried out both on a simple twoparameter reservoir model using synthetical data and on a more complicated hillslope model using real data from the Pukeiti Catchment in New Zealand. Comparison between the new MLE criterion and the Simple Least Squares (SLS) criterion reveals the superiority of the former over the latter. Comparison made between the new MLE and the MLE for auto-correlated case proposed by Sorooshian in 1978 has shown that both criteria would yield results with no practical difference if equal time interval data were used. However, the new MLE can work on variable time interval data which provide more information than equal time interval data, and therefore produces better visual results in hydrologic simulations.en_US
dc.description.notehydrology collectionen_US
dc.typeThesis-Reproduction (electronic)en_US
dc.typetexten_US
dc.subject.lcshHydrology.en_US
dc.subject.lcshFloods -- Mathematical models.en_US
dc.subject.lcshRivers -- Mathematical models.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.oclc213339767en_US
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