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首页> 外文期刊>Journal of Hydrology >Analysis of daily river flow fluctuations using empirical mode decomposition and arbitrary order Hilbert spectral analysis
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Analysis of daily river flow fluctuations using empirical mode decomposition and arbitrary order Hilbert spectral analysis

机译:基于经验模态分解和任意阶希尔伯特谱分析的每日河流量波动分析

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摘要

In this paper we presented the analysis of two long time series of daily river flow data, 32 years recorded in the Seine river (France), and 25 years recorded in the Wimereux river (Wimereux, France). We applied a scale based decomposition method, namely Empirical Mode Decomposition (EMD), on these time series. The data were decomposed into several Intrinsic Mode Functions (IMF). The mean frequency of each IMF mode indicated that the EMD method acts as a filter bank. Furthermore, the cross-correlation between these IMF modes from the Seine river and Wimereux river demonstrated correlation among the large scale IMF modes, which indicates that both rivers are likely to be influenced by the same maritime climate event of Northern France. As a confirmation we found that the large scale parts have the same evolution trend. We finally applied arbitrary order Hilbert spectral analysis, a new technique coming from turbulence studies and time series analysis, on the flow discharge of the Seine river. This new method provides an amplitude-frequency representation of the original time series, giving a joint pdf p(omega,A). When marginal moments of the amplitude are computed, one obtains an intermittency study in the frequency space. Applied to river flow discharge data from the Seine river, this shows the scaling range and characterizes the intermittent fluctuations over the range of scales from 4.5 to 60 days, between synoptic and intraseasonal scales.
机译:在本文中,我们对两个长期的每日河流流量数据序列进行了分析,分别是塞纳河(法国)记录的32年和维梅列克斯河(法国的Wimereux)记录的25年。在这些时间序列上,我们应用了基于标度的分解方法,即经验模式分解(EMD)。数据被分解为几个固有模式函数(IMF)。每个IMF模式的平均频率表明EMD方法充当了滤波器组。此外,来自塞纳河和维米尔纽克斯河的这些IMF模式之间的互相关证明了大规模IMF模式之间的相关性,这表明两条河流都可能受到法国北部同一海事气候事件的影响。作为确认,我们发现大型零件具有相同的演变趋势。我们最终在塞纳河的流量排放中应用了任意阶数的希尔伯特谱分析,这是一种来自湍流研究和时间序列分析的新技术。这种新方法提供了原始时间序列的幅度-频率表示,给出了联合pdf p(omega,A)。当计算出幅度的边际矩时,就可以对频率空间进行间歇性研究。将其应用到塞纳河的流量数据中,可以显示出尺度范围,并表征了天气尺度和季节内尺度之间4.5至60天范围内的间歇性波动。

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