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Fractal analysis of river flow fluctuations

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  • Sadegh Movahed, M.
  • Hermanis, Evalds

Abstract

We use some fractal analysis methods to study river flow fluctuations. The result of the Multifractal Detrended Fluctuation Analysis (MF-DFA) shows that there are two crossover timescales at s1×∼12 and s2×∼130 months in the fluctuation function. We discuss how the existence of the crossover timescales are related to a sinusoidal trend. The first crossover is due to the seasonal trend and the value of second one is approximately equal to the well-known cycle of sun activity. Using Fourier Detrended Fluctuation Analysis, the sinusoidal trend is eliminated. The values of Hurst exponents of the runoff water of rivers without the sinusoidal trend show a long-range correlation behavior. For the Daugava river, the value of Hurst exponent is 0.52±0.01 and also we find that these fluctuations have multifractal nature. Comparing the MF-DFA results for the remaining data set of Daugava river to those for shuffled and surrogate series, we conclude that its multifractal nature is almost entirely due to the broadness of probability density function.

Suggested Citation

  • Sadegh Movahed, M. & Hermanis, Evalds, 2008. "Fractal analysis of river flow fluctuations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(4), pages 915-932.
    • Handle: RePEc:eee:phsmap:v:387:y:2008:i:4:p:915-932
    DOI: 10.1016/j.physa.2007.10.007
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    13. Chatterjee, Sucharita & Ghosh, Dipak, 2021. "Impact of Global Warming on SENSEX fluctuations — A study based on Multifractal detrended cross correlation analysis between the temperature anomalies and the SENSEX fluctuations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 571(C).
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    16. Braga, A.C. & Alves, L.G.A. & Costa, L.S. & Ribeiro, A.A. & de Jesus, M.M.A. & Tateishi, A.A. & Ribeiro, H.V., 2016. "Characterization of river flow fluctuations via horizontal visibility graphs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 1003-1011.
    17. Ausloos, Marcel & Cerqueti, Roy & Lupi, Claudio, 2017. "Long-range properties and data validity for hydrogeological time series: The case of the Paglia river," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 470(C), pages 39-50.
    18. Mulligan, Robert F., 2017. "The multifractal character of capacity utilization over the business cycle: An application of Hurst signature analysis," The Quarterly Review of Economics and Finance, Elsevier, vol. 63(C), pages 147-152.
    19. Liu, Chenggong & Shang, Pengjian & Feng, Guochen, 2017. "The high order dispersion analysis based on first-passage-time probability in financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 1-9.
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    23. Mihailović, Dragutin T. & Nikolić-Đorić, Emilija & Arsenić, Ilija & Malinović-Milićević, Slavica & Singh, Vijay P. & Stošić, Tatijana & Stošić, Borko, 2019. "Analysis of daily streamflow complexity by Kolmogorov measures and Lyapunov exponent," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 290-303.
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