Multifractal analysis of hydrologic data using wavelet methods and fluctuation analysis
type: Item
instance of: scholarly article
title: Multifractal analysis of hydrologic data using wavelet methods and fluctuation analysis
zbMATH Open document ID: 1401.62224
DOI: 10.1155/2017/3148257
author: Tongzhou Zhao
author: Liang Wu
author: Dehua Li
author: Yiming Ding
published in: Discrete Dynamics in Nature and Society
publication date: 2018-09-27T00:00:00Z
review text: Summary: We study the multifractal properties of water level with a high-frequency and massive time series using wavelet methods (estimation of Hurst exponents, multiscale diagram, and wavelet leaders for multifractal analysis (WLMF)) and multifractal detrended fluctuation analysis (MF-DFA). The dataset contains more than two million records from 10 observation sites at a northern China river. The multiscale behaviour is observed in this time series, which indicates the multifractality. This multifractality is detected via multiscale diagram. Then we focus on the multifractal analysis using MF-DFA and WLMF. The two methods give the same conclusion that at most sites the records satisfy the generalized binomial multifractal model, which is robust for different times (morning, afternoon, and evening). The variation in the detailed characteristic parameters of the multifractal model indicates that both human activities and tributaries influence the multifractality. Our work is useful for building simulation models of the water level of local rivers with many observation sites.
Mathematics Subject Classification ID: 62P12
Mathematics Subject Classification ID: 62M10
Mathematics Subject Classification ID: 65T60
Mathematics Subject Classification ID: 86A05
zbMATH DE Number: 6944812
zbMATH Keywords: wavelet methods
zbMATH Keywords: fluctuation analysis
zbMATH Keywords: multifractal properties
zbMATH Keywords: water level
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2017/3148257
OpenAlex ID: W2765371418
cites work: Fractional Brownian Motions, Fractional Noises and Applications
cites work: Estimation of Hurst exponent revisited
cites work: Intermittent turbulence in self-similar cascades: divergence of high moments and dimension of the carrier
cites work: Singularity spectrum of fractal signals from wavelet analysis: Exact results
cites work: THE MULTIFRACTAL FORMALISM REVISITED WITH WAVELETS
cites work: Q4823031
cites work: Multifractality of river runoff and precipitation: comparison of fluctuation analysis and wavelet methods
cites work: Multifractal detrended fluctuation analysis of nonstationary time series
cites work: A wavelet-based joint estimator of the parameters of long-range dependence
cites work: Wavelet-based analysis of non-Gaussian long-range dependent processes and estimation of the Hurst parameter
cites work: Estimation of self-similar Gaussian fields using wavelet transform
cites work: Wavelet-based estimator for the Hurst parameters of fractional Brownian sheet
cites work: A multifractal wavelet model with application to network traffic
cites work: Q3436889
cites work: Multifractality Tests Using Bootstrapped Wavelet Leaders
cites work: Wavelet-based estimators of scaling behavior
cites work: Multifractal Formalism for Functions Part II: Self-Similar Functions
cites work: Q4524456
description: scientific article; zbMATH DE number 6944812