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Multifractality and cross-correlation analysis of streamflow and sediment fluctuation at the apex of the Pearl River Delta

The fluctuation and distribution of hydrological signals are highly related to the fluvial and geophysical regime at estuarine regions. Based on the long daily streamflow and sediment data of Makou (MK) and Sanshui (SS) stations at the apex of the Pearl River Delta, the scaling behavior of the strea...

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Detalles Bibliográficos
Autores principales: Wu, Yao, He, Yong, Wu, Menwu, Lu, Chen, Gao, Shiyou, Xu, Yanwen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6224538/
https://www.ncbi.nlm.nih.gov/pubmed/30410076
http://dx.doi.org/10.1038/s41598-018-35032-z
Descripción
Sumario:The fluctuation and distribution of hydrological signals are highly related to the fluvial and geophysical regime at estuarine regions. Based on the long daily streamflow and sediment data of Makou (MK) and Sanshui (SS) stations at the apex of the Pearl River Delta, the scaling behavior of the streamflow and sediment is explored by multifractal detrended fluctuation analysis (MF-DFA). The results indicated that there was significant multifractal structure present in the fluctuations of streamflow and sediment. Meanwhile, the multifractal degree and complexity of sediment were much stronger than streamflow. Although the scaling exponents of streamflow were larger than sediment at both MK and SS, no evident differences have been found on the scaling properties of streamflow and sediment for the ratios MK/SS. Moreover, the cross-correlation between streamflow and sediment is further detected by Multifractal Detrended Cross-Correlation Analysis (MF-DXA). The multifractal response between streamflow and sediment at small timescale is characterized by long-range correlations whereas it exhibits random behavior at large timescale. The interaction of the broadness of probability density function and the long-range correlations should be responsible for the multifractal properties of hydrological time series as the multifractal degree of surrogate and shuffled data was significantly undermined.