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Multiscaling Analysis of Monthly Runoff Series Using Improved MF-DFA Approach

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  • Xiaohui Yuan
  • Bin Ji
  • Hao Tian
  • Yuehua Huang

Abstract

An improved multifractal detrended fluctuation analysis(MF-DFA) method is applied to analyze the long-term monthly runoff records of a hydrological station in the Yangtze River with seasonal trend eliminated, through which the long-range correlation and the multifractal characteristics have been found. The multifractal spectrum has been fitted by a generalized expression of the multiplicative cascade model, and the results show that the monthly runoff series has strong multifractal characteristics. Comparing the results for the original runoff series with those of shuffled and surrogate series, it concludes that the multifractal characteristics of the monthly runoff time series is due to the broadness of both the probability density function and long-range correlation, and the broadness of the probability density function is dominant. Copyright Springer Science+Business Media Dordrecht 2014

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  • Xiaohui Yuan & Bin Ji & Hao Tian & Yuehua Huang, 2014. "Multiscaling Analysis of Monthly Runoff Series Using Improved MF-DFA Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(12), pages 3891-3903, September.
    • Handle: RePEc:spr:waterr:v:28:y:2014:i:12:p:3891-3903
    DOI: 10.1007/s11269-014-0715-y
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    2. Hasan Tatli & H. Nüzhet Dalfes, 2020. "Long-Time Memory in Drought via Detrended Fluctuation Analysis," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(3), pages 1199-1212, February.
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    4. Morales Martínez, Jorge Luis & Segovia-Domínguez, Ignacio & Rodríguez, Israel Quiros & Horta-Rangel, Francisco Antonio & Sosa-Gómez, Guillermo, 2021. "A modified Multifractal Detrended Fluctuation Analysis (MFDFA) approach for multifractal analysis of precipitation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    5. Dong Liu & Mingjie Luo & Qiang Fu & Yongjia Zhang & Khan M. Imran & Dan Zhao & Tianxiao Li & Faiz M. Abrar, 2016. "Precipitation Complexity Measurement Using Multifractal Spectra Empirical Mode Decomposition Detrended Fluctuation Analysis," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(2), pages 505-522, January.
    6. Zhong-kai Feng & Wen-jing Niu & Zhi-qiang Jiang & Hui Qin & Zhen-guo Song, 2020. "Monthly Operation Optimization of Cascade Hydropower Reservoirs with Dynamic Programming and Latin Hypercube Sampling for Dimensionality Reduction," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(6), pages 2029-2041, April.
    7. Wang, Jian & Huang, Menghao & Wu, Xinpei & Kim, Junseok, 2023. "A local fitting based multifractal detrend fluctuation analysis method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 611(C).
    8. Dong Liu & Mingjie Luo & Qiang Fu & Yongjia Zhang & Khan Imran & Dan Zhao & Tianxiao Li & Faiz Abrar, 2016. "Precipitation Complexity Measurement Using Multifractal Spectra Empirical Mode Decomposition Detrended Fluctuation Analysis," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(2), pages 505-522, January.

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