Fluctuation dynamics in geoelectrical data: an investigation by using multifractal detrended fluctuation analysis

Telesca, Luciano; Colangelo, G.; Lapenna, Vincenzo; Macchiato, M.

doi:10.1016/j.physleta.2004.10.011

Cited by 65 publications

(28 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Let X j be a data series of length N with a compact support (j = 1, 2,···, N). The integrated series or the profile at location i, Y (i), is determined by taking the sum of deviations from the mean value Telesca et al, 2004) i.e.,…”

Section: A Biswas Et Al: Multifractal Detrended Fluctuation Analysismentioning

confidence: 99%

See 1 more Smart Citation

Multifractal detrended fluctuation analysis in examining scaling properties of the spatial patterns of soil water storage

Biswas

Zeleke²,

Cheng

2012

Nonlin. Processes Geophys.

View full text Add to dashboard Cite

Abstract. Knowledge about the scaling properties of soil water storage is crucial in transferring locally measured fluctuations to larger scales and vice-versa. Studies based on remotely sensed data have shown that the variability in surface soil water has clear scaling properties (i.e., statistically self similar) over a wider range of spatial scales. However, the scaling property of soil water storage to a certain depth at a field scale is not well understood. The major challenges in scaling analysis for soil water are the presence of localized trends and nonstationarities in the spatial series. The objective of this study was to characterize scaling properties of soil water storage variability through multifractal detrended fluctuation analysis (MFDFA). A field experiment was conducted in a sub-humid climate at Alvena, Saskatchewan, Canada. A north-south transect of 624-m long was established on a rolling landscape. Soil water storage was monitored weekly between 2002 and 2005 at 104 locations along the transect. The spatial scaling property of the surface 0 to 40 cm depth was characterized using the MFDFA technique for six of the soil water content series (all gravimetrically determined) representing soil water storage after snowmelt, rainfall, and evapotranspiration. For the studied transect, scaling properties of soil water storage are different between drier periods and wet periods. It also appears that local controls such as site topography and texture (that dominantly control the pattern during wet states) results in multiscaling property. The nonlocal controls such as evapotranspiration results in the reduction of the degree of multiscaling and improvement in the simple scaling. Therefore, the scaling property of soil water storage is a function of both soil moisture status and the spatial extent considered.

show abstract

Section: A Biswas Et Al: Multifractal Detrended Fluctuation Analysismentioning

confidence: 99%

“…where h(q) is the generalized Hurst scaling function (Telesca et al, 2004). For q = 2 we have the standard DFA analysis.…”

Section: A Biswas Et Al: Multifractal Detrended Fluctuation Analysismentioning

confidence: 99%

Multifractal detrended fluctuation analysis in examining scaling properties of the spatial patterns of soil water storage

Biswas

Zeleke²,

Cheng

2012

Nonlin. Processes Geophys.

View full text Add to dashboard Cite

show abstract

“…Because of the diverging exponent when q → 0 we employed in this limit a logarithmic averaging (Kantelhardt et al, 2002;Telesca et al, 2004).…”

Section: Wmf-dfa Algorithmmentioning

confidence: 99%

Discrete Wavelet Analyses for Time Series

Murguı́a¹,

Rosu²

2011

Discrete Wavelet Transforms - Theory and Applications

View full text Add to dashboard Cite

show abstract

“…The scale index meaning (Luciano Telesca et al, 2004& Ping Zhou et al, 2007: a) 1> a> 0.5, if the DFA exponent is between 0.5 and 1, the change trend will continue as the the former. b) 0 <a <0.5, If its DFA exponent is less than 0.5, the serie is a antipersistence sequence.…”

Section: Next For Each Interval V V=n H +1…2n H Here Y H (I) Is mentioning

confidence: 99%

Multiple Time Scales Analysis of Precipitation in Hotan, China

JiQing

Shen

2009

JSD

View full text Add to dashboard Cite

The wavelet transform and detrended fluctuation analysis (DFA) were introduced briefly. Then DFA and discrete wavelet were used to analyze the fluctuation characteristics of precipitation in Hotan from 1954 to 2003. It was shown by analysis with the methods of de-trend fluctuation and wavelet transform that the precipitation in Hotan will decreased in near future for several years, and will last 21 months at least.

show abstract

Fluctuation dynamics in geoelectrical data: an investigation by using multifractal detrended fluctuation analysis

Cited by 65 publications

References 20 publications

Multifractal detrended fluctuation analysis in examining scaling properties of the spatial patterns of soil water storage

Multifractal detrended fluctuation analysis in examining scaling properties of the spatial patterns of soil water storage

Discrete Wavelet Analyses for Time Series

Multiple Time Scales Analysis of Precipitation in Hotan, China

Contact Info

Product

Resources

About