Abstract Modeling the variability of daily streamflows has received less analysis than those of monthly or annual streamflows. Since daily streamflows are affected by individual rainstorms, characterizing their features is more complicated. In this work, we analyze the complex behavior of daily streamflows and search for evidence of deterministic nonlinear dynamics. However, there is no evidence of chaotic behavior in the investigated streamflows. We also investigate the effect of aggregation process on chaotic time series. We suggest that the lack of evidence for nonlinear determinism in daily streamflows may be due to such aggregation process.


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    Titel :

    Effect of aggregation on chaotic time series


    Beteiligte:
    Kim, Hung Soo (Autor:in) / Yoon, Yong Nam (Autor:in) / Yi, Gyu-Sei (Autor:in) / Kim, Taegyun (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    01.12.2000


    Format / Umfang :

    8 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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