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Modeling the uncertainty of hydrologic processes exhibiting changes

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dc.contributor.authorSaada, Nidhal, author
dc.contributor.authorSalas, Jose D., advisor
dc.contributor.authorYevjevich, Vujica M., 1913-, committee member
dc.contributor.authorBoes, Duane C., committee member
dc.contributor.authorRamírez, Jorge A., committee member
dc.date.accessioned2007-01-03T04:27:24Z
dc.date.available2007-01-03T04:27:24Z
dc.date.issued1998
dc.descriptionDepartment Head: Marvin E. Criswell.
dc.description.abstractThe Geometric-Normal-Normal (GNN) model was analyzed and tested for the purpose of simulating hydrologic processes that exhibit changes. The general moment equations of the GNN model were derived, particularly the lag-k autocorrelation function. They can be used to estimate the model parameters based on the method of moments. Other estimation methods were also suggested. They include regression analysis, fitting the autocorrelation function (ACF), using the range properties, and using the run properties. The performance of these methods was tested by using simulation experiments. The results showed that in terms of bias and mean square error the regression and range methods are better than the other methods for estimating the model parameters. The GNN model was applied to the White Nile River flows at Malakal and the annual net basin supply (NBS) data for Lake St. Clair of the Great Lakes system. Simulation experiments were conducted to test the ability of the GNN model to preserve a number of observed statistics such as the mean, standard deviation, skewness, rescaled range, Hurst coefficient, longest drought, maximum deficit, and surplus. Results show that the GNN model, in general, performs quite well in preserving these statistics. An extended version of the GNN model was also formulated and analyzed in this study. Different methods of estimation were suggested to estimate the model parameters. However, application of this model to Malakal flows and Lake St.Clair NBS data did not show any advantage over simpler GNN.
dc.format.mediumdoctoral dissertations
dc.identifier1998_summer_Saada.pdf
dc.identifierETDF1998100001CVEE
dc.identifier.urihttp://hdl.handle.net/10217/5681
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado State University. Libraries
dc.relationCatalog record number (MMS ID): 991005192579703361
dc.relationGB665.S23 1998
dc.relation.ispartof1980-1999
dc.rightsCopyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.
dc.subjectGreat Lakes system
dc.subjectGNN model
dc.subjectWhite Nile River flows
dc.subjectMalakal
dc.subjectLake St. Clair
dc.subjectnet basin supply
dc.subjectNBS
dc.subjectgeometric-normal-normal model
dc.subject.lcshHydrologic models
dc.subject.lcshStochastic processes
dc.titleModeling the uncertainty of hydrologic processes exhibiting changes
dc.typeText
dcterms.rights.dplaThis Item is protected by copyright and/or related rights (https://rightsstatements.org/vocab/InC/1.0/). You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).
thesis.degree.disciplineCivil Engineering
thesis.degree.grantorColorado State University
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy (Ph.D.)

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