Multifractal Detrended Fluctuation Analysis of Regional Precipitation Sequences Based on the CEEMDAN-WPT

Liu, Dong; Chen, Cheng; Fu, Qiang; Li, Mo; Faiz, Muhammad Abrar; Li, Tianxiao; Khan, Muhammad Imran; Cui, Song

doi:10.1007/s00024-018-1820-2

Cited by 7 publications

(7 citation statements)

References 24 publications

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“…All the generalized Hurts exponents (Hq) of the Th-K and Th-U distributions in each OAE3 and non-OAE segments are q dependent (decrease with the increasing of q). The slope of all the fluctuation functions at different scale decrease with the increase of q, implying that the Th-U and Th-K distributions of the studied OAE3 and non-OAE intervals have a multifractal property 34,70,71 . By analyzing the slopes, it appears that the scaling properties of the Th-K and Th-U distributions at SLB, DIB and DR are closer in the OAE3 interval than the non-OAE3 intervals (Figs.…”

Section: Resultsmentioning

confidence: 89%

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Multifractal characterization of the Coniacian–Santonian OAE3 in lacustrine and marine deposits based on spectral gamma ray logs

Kouamelan

Zou

Wang

et al. 2020

Sci Rep

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Limited to the Atlantic and its surrounding basins, the expression of the Coniacian-Santonian oceanic anoxic event (OAE3) was discovered in the non-marine Cretaceous Songliao Basin, Eastern Asia not long ago. In this study, based on spectral gamma ray logs data recorded in three basins, the self-similarity of the OAE3 was studied through the analysis of the scaling properties of thoriumpotassium and thorium-uranium distributions both in marine and terrestrial environments using the multifractal detrending fluctuation analysis. The results indicate that, in both marine and terrestrial systems, the OAE3 intervals are characterized by their multifractal nature due to long-range correlation. However, the multifractal features of the studied OAE3 intervals are different in the three basins, although some common trends were observed. By comparing the degree of multifractality of the OAE3 deposits with the clay minerals and the redox conditions, it appears that the changes of the multifractal features are controlled by local changes such as clay mineralogy and redox conditions in both milieus under different sedimentation patterns. At all sites, the left side shortened spectrum of the thorium-potassium distribution suggests the presence of local fluctuations with minor amplitudes during the OAE3. Furthermore, the shortened singularity spectrum of the thorium-uranium distribution reflects the existence of small-scale fluctuations with large amplitudes at marine sites while in the non-marine Songliao Basin, the thorium-uranium distribution suggests the presence of local fluctuations with small amplitudes during the OAE3. Therefore, a more local behavior of the event is considered although the regional character is not neglected. The Cretaceous is the last and longest period of the Mesozoic Era where the Earth experienced some major geological events such as oceanic anoxic events (OAEs) 1-5 , large-scale volcanic activities 5-8 whose footprints are concealed in both marine and continental environments. OAEs have been documented in the geological sedimentary record, particularly in Cretaceous marine sediments, as complex paleoenvironmental phenomena and climatically influenced major geological perturbations of the Earth system, especially the Earth's carbon cycle 4,9,10. These complex geological events are characterized by global deposits of organic shales associated with major carbon isotope excursions (CIEs) 4,11-13. Intensive investigations revealed that the Upper Cretaceous period recorded two important OAEs: (1) OAE2 (Cenomanian-Turonian) known as one of the severest and widespread oceanic anoxic events, and (2) OAE3 (late Coniacian-early Santonian) which represents the youngest Cretaceous oceanic anoxic event and potentially a regional rather than a global phenomenon, but which lasted much longer than OAE2 14-16. Dissimilar to OAE2, the geographical distribution of the OAE3 suggests that the Coniacian-Santonian oceanic anoxic events are restricted to the Atlantic and proximate basins 10 (Fig.

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Section: Resultsmentioning

confidence: 89%

“…According to San José Martínez et al 97 and Liu et al 34 , the shape features of the multifractal spectrum defined by Δ D = − can estimate the probability of the dominate subset in time series. When Δ D < 0, a small probability subset dominates, while a large probability subset dominates when Δ D > 0.…”

Section: Discussionmentioning

confidence: 99%

Multifractal characterization of the Coniacian–Santonian OAE3 in lacustrine and marine deposits based on spectral gamma ray logs

Kouamelan

Zou

Wang

et al. 2020

Sci Rep

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“…Applications of the CEEMDAN method in hydrology include by Antico et al (2014), Adarsh and Reddy ( 2016), Reddy and Adarsh (2016), and Liu et al (2018). Antico et al (2014) used the CEEMDAN method to decompose and analyze the monthly mean discharge of the Parana River, South America.…”

Section: Complete Ensemble Empirical Mode Decomposition With Adaptive Noisementioning

confidence: 99%

A Comparison of Time‐Frequency Signal Processing Methods for Identifying Non‐Perennial Streamflow Events From Streambed Surface Temperature Time Series

Partington

Shanafield

Turnadge

2021

Water Resources Research

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Nonperennial stream networks constitute over half of total stream lengths worldwide (Datry et al., 2014). However, knowledge of the spatial and temporal variability of non-perennial flows is often limited (Costigan et al., 2016) and stream gauging networks are typically biased toward perennial streams (De Girolamo et al., 2015;Eng et al., 2016). Even where gauges on nonperennial streams exist, often insufficient data are available to identify spatial variations in flows within a catchment. Since the duration and volume of surface flows control both the availability and quality of water for flora and fauna along stream reaches (Datry et al., 2016), as well as the potential for groundwater recharge (Shanafield et al., 2012;Morin et al., 2009;Tooth, 2000), identifying and quantifying nonperennial flow patterns is critical.The need for low-cost technologies that can be widely deployed has spurred several efforts to develop methods of streamflow detection and quantification beyond the traditional gauging station. The availability of inexpensive, easily programmable sensors has led to the development of several types of streamflow

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“…This new method can more precisely decompose nonlinear series and distinguish the variation patterns of different time scales in complex data [19,20]. Recently, many hydrologists have applied the CEEMDAN method to hydrological time series analysis [21][22][23] and built runoff prediction models combined with the "decomposition-prediction-reconstruction" principle [6,[24][25][26][27].…”

Section: Introductionmentioning

confidence: 99%

Study on the Improvement of the Application of Complete Ensemble Empirical Mode Decomposition with Adaptive Noise in Hydrology Based on RBFNN Data Extension Technology

Zhang¹,

Jin²,

Sun³

et al. 2021

Computer Modeling in Engineering &Amp; Sciences

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The complex nonlinear and non-stationary features exhibited in hydrologic sequences make hydrological analysis and forecasting difficult. Currently, some hydrologists employ the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) method, a new time-frequency analysis method based on the empirical mode decomposition (EMD) algorithm, to decompose non-stationary raw data in order to obtain relatively stationary components for further study. However, the endpoint effect in CEEMDAN is often neglected, which can lead to decomposition errors that reduce the accuracy of the research results. In this study, we processed an original runoff sequence using the radial basis function neural network (RBFNN) technique to obtain the extension sequence before utilizing CEEMDAN decomposition. Then, we compared the decomposition results of the original sequence, RBFNN extension sequence, and standard sequence to investigate the influence of the endpoint effect and RBFNN extension on the CEEMDAN method. The results indicated that the RBFNN extension technique effectively reduced the error of medium and low frequency components caused by the endpoint effect. At both ends of the components, the extension sequence more accurately reflected the true fluctuation characteristics and variation trends. These advances are of great significance to the subsequent study of hydrology. Therefore, the CEEMDAN method, combined with an appropriate extension of the original runoff series, can more precisely determine multi-time scale characteristics, and provide a credible basis for the analysis of hydrologic time series and hydrological forecasting. KEYWORDSComplete ensemble empirical mode decomposition with adaptive noise; data extension; radial basis function neural network; multi-time scales; runoff

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Multifractal Detrended Fluctuation Analysis of Regional Precipitation Sequences Based on the CEEMDAN-WPT

Cited by 7 publications

References 24 publications

Multifractal characterization of the Coniacian–Santonian OAE3 in lacustrine and marine deposits based on spectral gamma ray logs

Multifractal characterization of the Coniacian–Santonian OAE3 in lacustrine and marine deposits based on spectral gamma ray logs

A Comparison of Time‐Frequency Signal Processing Methods for Identifying Non‐Perennial Streamflow Events From Streambed Surface Temperature Time Series

Study on the Improvement of the Application of Complete Ensemble Empirical Mode Decomposition with Adaptive Noise in Hydrology Based on RBFNN Data Extension Technology

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