IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v533y2019ics0378437119311793.html
   My bibliography  Save this article

Understanding long-term persistence and multifractal behaviors in river runoff: A detailed study over eastern China

Author

Listed:
  • Wu, Wenlu
  • Yuan, Naiming
  • Xie, Fenghua
  • Qi, Yanjun

Abstract

Long-term persistence (LTP) and multifractality in river runoff fluctuations have been well recognized over the recent decades, but the origins of these characteristics are still under debate. In this study, 12 runoff and 12 precipitation data from eastern China are analyzed using detrended fluctuation analysis (DFA) and its generalized version, multifractal detrended fluctuation analysis (MF-DFA). By comparing the results between runoff and the nearby precipitation data, we find the nonlinear features in river runoff may be propagated from the nearby precipitation data, but the LTP is not inherited from precipitation. To explain the observed LTP in river runoff, catchment area is found as a potential factor and the relation is more pronounced for catchment area with larger size. Accordingly, the LTP in river runoff may arise from the spatial aggregation effect, while the observed multifractal behaviors may be related to the nonlinear features in the nearby precipitation. These findings are based on data from eastern China, which was not analyzed systematically due to the poor data availability. Since the existence of LTP and multifractality makes the runoff change not completely random, one should further introduce these characteristics into hydrological models, for improved water managements and better estimations of hazard risks.

Suggested Citation

  • Wu, Wenlu & Yuan, Naiming & Xie, Fenghua & Qi, Yanjun, 2019. "Understanding long-term persistence and multifractal behaviors in river runoff: A detailed study over eastern China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 533(C).
  • Handle: RePEc:eee:phsmap:v:533:y:2019:i:c:s0378437119311793
    DOI: 10.1016/j.physa.2019.122042
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437119311793
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2019.122042?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Gui, Jun & Zheng, Zeyu & Fu, Dianzheng & Fu, Yang & Liu, Zhi, 2021. "Long-term correlations and multifractality of toll-free calls in China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 567(C).
    2. Nurulkamal Masseran, 2022. "Multifractal Characteristics on Temporal Maximum of Air Pollution Series," Mathematics, MDPI, vol. 10(20), pages 1-15, October.
    3. Yoshioka, Hidekazu & Yoshioka, Yumi, 2024. "Generalized divergences for statistical evaluation of uncertainty in long-memory processes," Chaos, Solitons & Fractals, Elsevier, vol. 182(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:533:y:2019:i:c:s0378437119311793. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.