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A method for assessing impacts of parameter uncertainty in sediment transport modeling applications

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dc.contributor.authorRuark, Morgan D., author
dc.contributor.authorNiemann, Jeffrey D., advisor
dc.contributor.authorKampf, Stephanie, committee member
dc.contributor.authorGriemann, Blair, committee member
dc.date.accessioned2022-09-28T21:27:43Z
dc.date.available2022-09-28T21:27:43Z
dc.date.issued2009
dc.descriptionCovers not scanned.
dc.descriptionPrint version deaccessioned 2022.
dc.description.abstractNumerical sediment transport models are widely used to evaluate impacts of water management activities on endangered species, to identify appropriate strategies for dam removal, and many other applications. The SRH-1D (Sedimentation and River Hydraulics - One Dimension) numerical model, formerly known as GST ARS, is used by the U.S. Bureau of Reclamation for many such evaluations. The predictions from models such as SRH-1D include uncertainty due to assumptions embedded in the model 's mathematical structure, uncertainty in the values of parameters, and various other sources. In this paper, we aim to develop a method that quantifies the degree to which parameter values are constrained by calibration data and determines the impacts of the remaining parameter uncertainty on model forecasts. Ultimately, this method could be used to assess how well calibration exercises have constrained model behavior and to identify data collection strategies that improve parameter certainty. The method uses a new multi-objective version of Generalized Likelihood Uncertainty Estimation (GLUE). In this approach, the likelihoods of parameter values are assessed using a function that weights different output variables using their first order global sensitivities, which are obtained from the Fourier Amplitude Sensitivity Test (FAST). The method is applied to SRH-1D models of two flume experiments: an erosional case described by Ashida and Michiue (1971) and a depositional case described by Seal et al. (1997). Overall, the results suggest that the sensitivities of the model outputs to the parameters can be rather different for erosional and depositional cases and that the outputs in the depositional case can be sensitive to more parameters. The results also suggest that the form of the likelihood function can have a significant impact on the assessment of parameter uncertainty and its implications for the uncertainty of model forecasts.
dc.format.mediummasters theses
dc.identifier.urihttps://hdl.handle.net/10217/235795
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado State University. Libraries
dc.relationCatalog record number (MMS ID): 991011651249703361
dc.relationC175.2.R937 2009
dc.relation.ispartof2000-2019
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.subject.lcshSediment transport -- Mathematical models
dc.titleA method for assessing impacts of parameter uncertainty in sediment transport modeling applications
dc.typeText
dc.typeStillImage
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 and Environmental Engineering
thesis.degree.grantorColorado State University
thesis.degree.levelMasters
thesis.degree.nameMaster of Science (M.S.)

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