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dc.contributor.advisorGupta, Hoshin V.en_US
dc.contributor.authorMartinez Baquero, Guillermo Felipe
dc.creatorMartinez Baquero, Guillermo Felipeen_US
dc.date.accessioned2011-12-05T14:14:53Z
dc.date.available2011-12-05T14:14:53Z
dc.date.issued2007en_US
dc.identifier.urihttp://hdl.handle.net/10150/193357
dc.description.abstractWith increasing model complexity there is a pressing need for new methods that can be used to mine information from large volumes of model results and available data. This work explores strategies to identify and evaluate the causes of discrepancy between models and data related to hydrologic processes, and to increase our knowledge about watershed input-output relationships. In this context, we evaluate the performance of the abcd monthly water balance model for 764 watersheds in the conterminous United States. The work required integration of the Hydro-Climatic Data Network dataset with various kinds of spatial information, and a diagnostic approach to relating model performance with assumptions and characteristics of the basins. The diagnostic process was implemented via classification of watersheds, evaluation of hydrologic signatures and the identification of dominant processes. Knowledge acquired during this process was used to test modifications of the model for hydrologic regions where the performance was "poor".
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.subjectdiagnosisen_US
dc.subjectabcd modelen_US
dc.subjectwatershed classificationen_US
dc.subjectevaluationen_US
dc.subjectcomplexityen_US
dc.subjectdata-miningen_US
dc.titleDiagnostic Evaluation of Watershed Modelsen_US
dc.typetexten_US
dc.typeElectronic Thesisen_US
dc.contributor.chairGupta, Hoshin V.en_US
dc.identifier.oclc659748206en_US
thesis.degree.grantorUniversity of Arizonaen_US
thesis.degree.levelmastersen_US
dc.contributor.committeememberTroch, Peteren_US
dc.contributor.committeememberValdes, Juanen_US
dc.identifier.proquest2333en_US
thesis.degree.disciplineHydrologyen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.nameMSen_US
refterms.dateFOA2018-06-29T10:12:15Z
html.description.abstractWith increasing model complexity there is a pressing need for new methods that can be used to mine information from large volumes of model results and available data. This work explores strategies to identify and evaluate the causes of discrepancy between models and data related to hydrologic processes, and to increase our knowledge about watershed input-output relationships. In this context, we evaluate the performance of the abcd monthly water balance model for 764 watersheds in the conterminous United States. The work required integration of the Hydro-Climatic Data Network dataset with various kinds of spatial information, and a diagnostic approach to relating model performance with assumptions and characteristics of the basins. The diagnostic process was implemented via classification of watersheds, evaluation of hydrologic signatures and the identification of dominant processes. Knowledge acquired during this process was used to test modifications of the model for hydrologic regions where the performance was "poor".


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