Quantitative sediment fingerprinting using a Bayesian uncertainty estimation framework

Ingrid F. Small, John S. Rowan (Lead / Corresponding author), Stewart W. Franks

    Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

    68 Citations (Scopus)

    Abstract

    Numerous studies have shown how selected physico-chemical
    properties of sediments may be used as tracers to identify catchment sediment
    sources. Sediment fingerprinting has value in elucidating the linkages between
    erosion and downstream sediment delivery and potentially offers the opportunity
    to validate deterministic erosion models. However, quantitative fingerprinting
    is subject to considerable uncertainty throughout the research process, i.e. the
    inherent variability of source group properties, the number and distinctiveness
    of source groups, the relative discriminating power of different tracers,
    numerical issues associated with the un-mixing models, and further complications associated with nonlinear additivity, tracer transformation and enrichment.
    A Bayesian statistical framework was employed to assess two of the sampling
    issues using laboratory-based and synthetic data sets. The analysis shows source
    group contributions can be robustly derived, but source group variability and
    number of samples collected are key issues influencing performance
    Original languageEnglish
    Title of host publicationThe Structure Function and Management Implications of Fluvial Sedimentary Systems
    EditorsFiona J. Dyer, Martin C. Thoms, Jon M. Olley
    Place of PublicationWallingford
    PublisherInternational Association of Hydrological Sciences (IAHS)
    Pages443-450
    Number of pages8
    ISBN (Print)978-1-901502-96-1
    Publication statusPublished - 2002

    Publication series

    NameIAHS Publications
    Number276

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