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dc.contributor.authorHay, Lauren E.*
dc.creatorHay, Lauren E.en_US
dc.date.accessioned2011-11-28T14:10:55Z
dc.date.available2011-11-28T14:10:55Z
dc.date.issued1987en_US
dc.identifier.urihttp://hdl.handle.net/10150/191925
dc.description.abstractA gradient based automatic calibration routie was implemented in the Salt River Project's long-term forecasting model. There is a choice of two estimation criteria; Maximium Likelihood or the Ordinary Least Squares. A comparison of the results of the calibration using the different estimation criteria and the original forecasts made by the SRP were made. A parameter sensitivity analysis was conducted and new statistics were implemented in the model. The forecasting results improved significantly with the implementation of an automatic calibration routine. Overall it was found that the Maximum Likelihood objective function using observed flows to calculate the weights performed better than the other objective functions when informative data were available for the watershed.
dc.language.isoenen_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.subject.lcshHydrology.en_US
dc.subject.lcshStreamflow -- Arizona -- Salt River Watershed -- Mathematical models.en_US
dc.subject.lcshStreamflow -- Arizona -- Salt River Watershed -- Forecasting.en_US
dc.titleThe automatic calibration of the SRP's long-term forecasting modelen_US
dc.typeThesis-Reproduction (electronic)en_US
dc.typetexten_US
dc.contributor.chairSorooshian, S. S.en_US
dc.identifier.oclc213416903en_US
thesis.degree.grantorUniversity of Arizonaen_US
thesis.degree.levelmastersen_US
thesis.degree.disciplineHydrology and Water Resourcesen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.nameM.S.en_US
dc.description.notehydrology collectionen_US
refterms.dateFOA2018-08-19T15:30:41Z
html.description.abstractA gradient based automatic calibration routie was implemented in the Salt River Project's long-term forecasting model. There is a choice of two estimation criteria; Maximium Likelihood or the Ordinary Least Squares. A comparison of the results of the calibration using the different estimation criteria and the original forecasts made by the SRP were made. A parameter sensitivity analysis was conducted and new statistics were implemented in the model. The forecasting results improved significantly with the implementation of an automatic calibration routine. Overall it was found that the Maximum Likelihood objective function using observed flows to calculate the weights performed better than the other objective functions when informative data were available for the watershed.


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