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Characterization of river flow fluctuations via horizontal visibility graphs

Author

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  • Braga, A.C.
  • Alves, L.G.A.
  • Costa, L.S.
  • Ribeiro, A.A.
  • de Jesus, M.M.A.
  • Tateishi, A.A.
  • Ribeiro, H.V.

Abstract

We report on a large-scale characterization of river discharges by employing the network framework of the horizontal visibility graph. By mapping daily time series from 141 different stations of 53 Brazilian rivers into complex networks, we present a useful approach for investigating the dynamics of river flows. We verified that the degree distributions of these networks were well described by exponential functions, where the characteristic exponents are almost always larger than the value obtained for random time series. The faster-than-random decay of the degree distributions is an another evidence that the fluctuation dynamics underlying the river discharges has a long-range correlated nature. We further investigated the evolution of the river discharges by tracking the values of the characteristic exponents (of the degree distribution) and the global clustering coefficients of the networks over the years. We show that the river discharges in several stations have evolved to become more or less correlated (and displaying more or less complex internal network structures) over the years, a behavior that could be related to changes in the climate system and other man-made phenomena.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:phsmap:v:444:y:2016:i:c:p:1003-1011
    DOI: 10.1016/j.physa.2015.10.102
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    References listed on IDEAS

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    1. Telesca, Luciano & Lovallo, Michele & Toth, Laszlo, 2014. "Visibility graph analysis of 2002–2011 Pannonian seismicity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 416(C), pages 219-224.
    2. Jánosi, Imre M & Gallas, Jason A.C, 1999. "Growth of companies and water-level fluctuations of the river Danube," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 271(3), pages 448-457.
    3. Yu, Zu-Guo & Leung, Yee & Chen, Yongqin David & Zhang, Qiang & Anh, Vo & Zhou, Yu, 2014. "Multifractal analyses of daily rainfall time series in Pearl River basin of China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 405(C), pages 193-202.
    4. Rybski, Diego & Holsten, Anne & Kropp, Jürgen P., 2011. "Towards a unified characterization of phenological phases: Fluctuations and correlations with temperature," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(4), pages 680-688.
    5. Kantelhardt, Jan W. & Rybski, Diego & Zschiegner, Stephan A. & Braun, Peter & Koscielny-Bunde, Eva & Livina, Valerie & Havlin, Shlomo & Bunde, Armin, 2003. "Multifractality of river runoff and precipitation: comparison of fluctuation analysis and wavelet methods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 330(1), pages 240-245.
    6. Yang, Yue & Wang, Jianbo & Yang, Huijie & Mang, Jingshi, 2009. "Visibility graph approach to exchange rate series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(20), pages 4431-4437.
    7. Livina, V. & Ashkenazy, Y. & Kizner, Z. & Strygin, V. & Bunde, A. & Havlin, S., 2003. "A stochastic model of river discharge fluctuations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 330(1), pages 283-290.
    8. Mihailović, D.T. & Nikolić-Đorić, E. & Drešković, N. & Mimić, G., 2014. "Complexity analysis of the turbulent environmental fluid flow time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 395(C), pages 96-104.
    9. Gao, Zhong-Ke & Jin, Ning-De, 2012. "Characterization of chaotic dynamic behavior in the gas–liquid slug flow using directed weighted complex network analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(10), pages 3005-3016.
    10. Zhang, Bo & Wang, Jun & Fang, Wen, 2015. "Volatility behavior of visibility graph EMD financial time series from Ising interacting system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 432(C), pages 301-314.
    11. Aleksandra Murks & Matjaž Perc, 2011. "Evolutionary Games On Visibility Graphs," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 14(03), pages 307-315.
    12. Dahlstedt, Kajsa & Jensen, Henrik Jeldtoft, 2005. "Fluctuation spectrum and size scaling of river flow and level," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 348(C), pages 596-610.
    13. Hajian, S. & Movahed, M. Sadegh, 2010. "Multifractal Detrended Cross-Correlation Analysis of sunspot numbers and river flow fluctuations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(21), pages 4942-4957.
    14. 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.
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    Cited by:

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    2. Peng, Xiaoyi & Zhao, Yi & Small, Michael, 2020. "Identification and prediction of bifurcation tipping points using complex networks based on quasi-isometric mapping," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 560(C).
    3. Gonçalves, Bruna Amin & Carpi, Laura & Rosso, Osvaldo A. & Ravetti, Martín G., 2016. "Time series characterization via horizontal visibility graph and Information Theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 464(C), pages 93-102.

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