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    The Gaussian copula model for the joint deficit index for droughts

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    Authors
    Van de Vyver, Hans
    Van den Bergh, Joris
    Discipline
    Natural sciences
    Mathematics
    Earth and related Environmental sciences
    Agricultural sciences
    Subject
    Drought; Joint deficit index; Gaussian copula; Geostatistics
    Audience
    Scientific
    Date
    2018-06
    Publisher
    Elsevier
    Metadata
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    Description
    The characterization of droughts and their impacts is very dependent on the time scale that is involved. In order to obtain an overall drought assessment, the cumulative effects of water deficits over different times need to be examined together. For example, the recently developed joint deficit index (JDI) is based on multivariate probabilities of precipitation over various time scales from 1- to 12-months, and was constructed from empirical copulas. In this paper, we examine the Gaussian copula model for the JDI. We model the covariance across the temporal scales with a two-parameter function that is commonly used in the specific context of spatial statistics or geostatistics. The validity of the covariance models is demonstrated with long-term precipitation series. Bootstrap experiments indicate that the Gaussian copula model has advantages over the empirical copula method in the context of drought severity assessment: (i) it is able to quantify droughts outside the range of the empirical copula, (ii) provides adequate drought quantification, and (iii) provides a better understanding of the uncertainty in the estimation.
    Citation
    Van de Vyver, H.; Van den Bergh, J. The Gaussian copula model for the joint deficit index for droughts. J. Hydrol. 2018, 561, 987–999.
    Identifiers
    uri: https://orfeo.belnet.be/handle/internal/7058
    doi: http://dx.doi.org/10.1016/j.jhydrol.2018.03.064
    Type
    Article
    Peer-Review
    Yes
    Language
    eng
    Links
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