Nonparametric streamflow simulation by wavelet or Fourier analysis

M. Bayazit, B. ÖNÖZ, H. Aksoy

Research output: Contribution to journalArticlepeer-review

33 Citations (Scopus)

Abstract

Wavelet or Fourier analysis is proposed as an alternative nonparametric method to simulate streamflows. An observed series is decomposed into its components at various resolutions and then recombined randomly to generate synthetic series. The mean and standard deviation are perfectly reproduced and coefficient of skewness tends to zero as the number of simulations increases. Normalizing transforms can be used for skewed series. Autocorrelation coefficients and the dependence structure are better preserved when Fourier analysis is used, but the mean and variance remain constant when the simulated and observed series have the same length. Monthly as well as annual flows can be simulated by this technique as illustrated on some examples. Wavelet analysis should be preferred as it generates flow series that exhibit a wider range of required reservoir capacities.

Original languageEnglish
Pages (from-to)623-634
Number of pages12
JournalHydrological Sciences Journal
Volume46
Issue number4
DOIs
Publication statusPublished - 2001

Funding

Acknowledgements The authors would like to thank two reviewers for their constructive comments, which have helped in improving the quality of the paper. H. Aksoy appreciates supports by Istanbul Technical University (ITU) and the Scientific and Technical Research Council of Turkey (TUBITAK), enabling him to do his postdoctoral researches at the University of California at Davis, USA.

FundersFunder number
TUBITAK
University of California, Davis
Türkiye Bilimsel ve Teknolojik Araştirma Kurumu
Istanbul Teknik Üniversitesi

    Keywords

    • Data generation
    • Fourier analysis
    • Harmonics
    • Nonparametric modelling
    • Streamflow simulation
    • Synthetic series
    • Wavelet analysis

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