Alpine biogeochemical modeling : case studies, improvements, and parameter estimation

Persistent Link:
http://hdl.handle.net/10150/191239
Title:
Alpine biogeochemical modeling : case studies, improvements, and parameter estimation
Author:
Meixner, Thomas.
Issue Date:
1999
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:
The geochemical, biogeochemical, and hydrologic controls on the stream chemical composition of alpine watersheds were investigated using the Alpine Hydrochemical Model (AHM). This model was successfully applied to the Emerald Lake watershed and two nearby watersheds as well as two watersheds in the Rocky Mountains, Andrews Creek and the Green Lakes Valley. The results reveal that snowmelt in alpine watersheds must come into contact with either soil, sub-talus, or reactive bedrock surfaces to explain the geochemistry observed in alpine lakes and streams. These materials do not differ geochemically but they do differ in their influence on the amount of mineral nitrogen observed in alpine lakes and streams. Improvements to the carbon-nitrogen dynamics portion of the ARM indicate that the Emerald Lake watershed is nearing nitrogen saturation. A robust multi-criteria sensitivity analysis technique was used to determine what processes were important for simulating the observed stream chemical composition. This sensitivity analysis revealed that concentration and mass flux representations of stream chemical composition contain different information about the watershed. The sensitivity analysis results were used to guide a multi-criteria parameter estimation algorithm. The results showed that stream chemical data is useful in discerning the importance of different processes and the role they play in determining stream chemical composition.
Type:
Dissertation-Reproduction (electronic); text
Keywords:
Hydrology.; Water -- Pollution -- Models.; Biogeochemical cycles -- Models.
Degree Name:
Ph. D.
Degree Level:
doctoral
Degree Program:
Hydrology and Water Resources; Graduate College
Degree Grantor:
University of Arizona
Committee Chair:
Bales, Roger

Full metadata record

DC FieldValue Language
dc.language.isoenen_US
dc.titleAlpine biogeochemical modeling : case studies, improvements, and parameter estimationen_US
dc.creatorMeixner, Thomas.en_US
dc.contributor.authorMeixner, Thomas.en_US
dc.date.issued1999en_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.abstractThe geochemical, biogeochemical, and hydrologic controls on the stream chemical composition of alpine watersheds were investigated using the Alpine Hydrochemical Model (AHM). This model was successfully applied to the Emerald Lake watershed and two nearby watersheds as well as two watersheds in the Rocky Mountains, Andrews Creek and the Green Lakes Valley. The results reveal that snowmelt in alpine watersheds must come into contact with either soil, sub-talus, or reactive bedrock surfaces to explain the geochemistry observed in alpine lakes and streams. These materials do not differ geochemically but they do differ in their influence on the amount of mineral nitrogen observed in alpine lakes and streams. Improvements to the carbon-nitrogen dynamics portion of the ARM indicate that the Emerald Lake watershed is nearing nitrogen saturation. A robust multi-criteria sensitivity analysis technique was used to determine what processes were important for simulating the observed stream chemical composition. This sensitivity analysis revealed that concentration and mass flux representations of stream chemical composition contain different information about the watershed. The sensitivity analysis results were used to guide a multi-criteria parameter estimation algorithm. The results showed that stream chemical data is useful in discerning the importance of different processes and the role they play in determining stream chemical composition.en_US
dc.description.notehydrology collectionen_US
dc.typeDissertation-Reproduction (electronic)en_US
dc.typetexten_US
dc.subjectHydrology.en_US
dc.subjectWater -- Pollution -- Models.en_US
dc.subjectBiogeochemical cycles -- Models.en_US
thesis.degree.namePh. D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.disciplineHydrology and Water Resourcesen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.chairBales, Rogeren_US
dc.contributor.committeememberDavis, Donalden_US
dc.contributor.committeememberGupta, Hoshinen_US
dc.contributor.committeememberDickinson, Roberten_US
dc.contributor.committeememberBetterton, Ericen_US
dc.identifier.oclc218841143en_US
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