Wu Yao, He Yong, Wu Menwu, Lu Chen, Gao Shiyou, Xu Yanwen
Key Laboratory of the Pearl River Estuarine Dynamics and Associated Process Regulation, Ministry of the Water Resources, Guangzhou, 510610, China.
Pearl River Hydraulic Research Institute, Pearl River Water Resources Commission, Guangzhou, 510610, China.
Sci Rep. 2018 Nov 8;8(1):16553. doi: 10.1038/s41598-018-35032-z.
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.
水文信号的波动和分布与河口地区的河流和地球物理状况高度相关。基于珠江三角洲顶端马口(MK)站和三水(SS)站长期的日流量和泥沙数据,采用多重分形去趋势波动分析(MF-DFA)探究流量和泥沙的标度行为。结果表明,流量和泥沙的波动中存在显著的多重分形结构。同时,泥沙的多重分形程度和复杂性比流量要强得多。尽管MK站和SS站流量的标度指数均大于泥沙,但对于MK/SS比值,流量和泥沙的标度特性未发现明显差异。此外,通过多重分形去趋势互相关分析(MF-DXA)进一步检测了流量与泥沙之间的互相关性。流量和泥沙在小时间尺度上的多重分形响应具有长程相关性,而在大时间尺度上表现出随机行为。由于替代数据和重排数据的多重分形程度显著降低,概率密度函数的宽度与长程相关性之间的相互作用应是水文时间序列多重分形特性的原因。