• Login
    View Item 
    •   Home
    • UA Graduate and Undergraduate Research
    • UA Theses and Dissertations
    • Master's Theses
    • View Item
    •   Home
    • UA Graduate and Undergraduate Research
    • UA Theses and Dissertations
    • Master's Theses
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

    All of UA Campus RepositoryCommunitiesTitleAuthorsIssue DateSubmit DateSubjectsPublisherJournalThis CollectionTitleAuthorsIssue DateSubmit DateSubjectsPublisherJournal

    My Account

    LoginRegister

    About

    AboutUA Faculty PublicationsUA DissertationsUA Master's ThesesUA Honors ThesesUA PressUA YearbooksUA CatalogsUA Libraries

    Statistics

    Most Popular ItemsStatistics by CountryMost Popular Authors

    Application of snow distribution models within the Laguna Negra basin, Chile

    • CSV
    • RefMan
    • EndNote
    • BibTex
    • RefWorks
    Thumbnail
    Name:
    azu_td_hwr_0775_pg_sip1_w.pdf
    Size:
    94.84Mb
    Format:
    PDF
    Download
    Author
    Cadle, Brad James
    Issue Date
    1997
    Advisor
    Bales, Roger
    
    Metadata
    Show full item record
    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
    Spectral linear unmixing and binary regression trees were used to estimate the distribution of snow within the Laguna Negra basin in Chile. Spectral linear unmixing was performed for multi-band Landsat 5 images for the determination of sub-pixel snow fractions. We were interested in determining the number of bands needed for an adequate distribution of SCA. Results showed that for winter scenes (scenes with greater than 90% snow cover and portions of the basin covered by shadows) linear spectral unmixing can be used to model SCA using at least four bands with a rock, a snow and a shaded snow endmember, but that five bands, using two rock endmembers, a snow and a shaded rock endmember, are needed for the fall scenes (scenes with less than 10% snow cover and portions of the basin covered by shadows). The spring scenes (scenes with 50 percent and higher snow cover and no shadows) showed plausible results with three bands, but the need for a second rock endmember in the fall scenes suggest 4 bands may give a more accurate result. A binary regression tree model was used to determine distributed SWE at peak accumulation in the Echaurren basin, a sub basin of Laguna Negra. Regression trees grown from field snow survey data did an excellent job at explaining the variation of SWE in two of the three surveys examined when resubstitution was used to evaluate the model, but did a poor job in all cases when cross validation was used. However, cross validation may over estimate the errors associated with the model. Basin-wide SWE maps resulting from the application of the regression trees formed plausible structures. Normalized snow distribution was sufficiently different between years such that a "typical" SWE map could not be developed. Nonetheless, there were identifiable patterns that did occur in the SWE distributions from different years that gave insight into the factors affecting SWE in the basin. Such factors include a strong dependance on radiation in the lower portion of Echaurren for two of the years, and the presence of heavy SWE regions near cliffs. Insights such as these provided useful information on how the type of data and method of collection might be improved. The large SWE values near cliffs, for instance, suggest that use of an avalanche map might improve the modeled SWE distribution. The dependance of SWE on radiation in the lower basin suggest the SWE data should be obtained over the entire range of radiation values in the lower basin.
    Type
    text
    Thesis-Reproduction (electronic)
    Degree Name
    M.S.
    Degree Level
    masters
    Degree Program
    Graduate College
    Hydrology and Water Resources
    Degree Grantor
    University of Arizona
    Collections
    Master's Theses

    entitlement

     
    The University of Arizona Libraries | 1510 E. University Blvd. | Tucson, AZ 85721-0055
    Tel 520-621-6442 | repository@u.library.arizona.edu
    DSpace software copyright © 2002-2017  DuraSpace
    Quick Guide | Contact Us | Send Feedback
    Open Repository is a service operated by 
    Atmire NV
     

    Export search results

    The export option will allow you to export the current search results of the entered query to a file. Different formats are available for download. To export the items, click on the button corresponding with the preferred download format.

    By default, clicking on the export buttons will result in a download of the allowed maximum amount of items.

    To select a subset of the search results, click "Selective Export" button and make a selection of the items you want to export. The amount of items that can be exported at once is similarly restricted as the full export.

    After making a selection, click one of the export format buttons. The amount of items that will be exported is indicated in the bubble next to export format.