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Analysis of Streamflow Complexity Based on Entropies in the Weihe River Basin, China

机译:基于渭河流域熵的流流复杂性分析

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摘要

The study on the complexity of streamflow has guiding significance for hydrologic simulation, hydrologic prediction, water resources planning and management. Utilizing monthly streamflow data from four hydrologic control stations in the mainstream of the Weihe River in China, the methods of approximate entropy, sample entropy, two-dimensional entropy and fuzzy entropy are introduced into hydrology research to investigate the spatial distribution and dynamic change in streamflow complexity. The results indicate that the complexity of the streamflow has spatial differences in the Weihe River watershed, exhibiting an increasing tendency along the Weihe mainstream, except at the Linjiacun station, which may be attributed to the elevated anthropogenic influence. Employing sliding entropies, the variation points of the streamflow time series at the Weijiabu station were identified in 1968, 1993 and 2003, and those at the Linjiacun station, Xianyang station and Huaxian station occurred in 1971, 1993 and 2003. In the verification of the above points, the minimum value of t-test is 3.7514, and that of Brown−Forsythe is 7.0307, far exceeding the significance level of 95%. Also, the cumulative anomaly can detect two variation points. The t-test, Brown−Forsythe test and cumulative anomaly test strengthen the conclusion regarding the availability of entropies for identifying the streamflow variability. The results lead us to conclude that four entropies have good application effects in the complexity analysis of the streamflow time series. Moreover, two-dimensional entropy and fuzzy entropy, which have been rarely used in hydrology research before, demonstrate better continuity and relative consistency, are more suitable for short and noisy hydrologic time series and more effectively identify the streamflow complexity. The results could be very useful in identifying variation points in the streamflow time series.
机译:关于流流的复杂性研究对水文模拟,水文预测,水资源规划和管理的指导意义。利用来自中国渭河主流的四个水文控制站的每月流流程数据,将熵,样品熵,二维熵和模糊熵的方法引入水文研究,以研究流流的空间分布和动态变化复杂。结果表明,流流的复杂性在渭河流域中具有空间差异,除了林群地址外,沿着渭河主流的趋势越来越大,临床驻地,这可能归因于升高的人为影响。采用滑动熵,威杰亚站的流流时间序列的变化点于1968年,1993年,2003年确定,凌阳站和华县站在1971年,1993年和2003年。在核实中上面的点,T检验的最小值为3.7514,棕色叉子的最低值为7.0307,远远超过95%的重要性水平。此外,累积异常可以检测两个变异点。 T检验,棕色叉效果测试和累积异常测试加强了关于识别流流量变异性的熵的可用性的结论。结果导致我们得出结论,四个熵在流流时间序列的复杂性分析中具有良好的应用效果。此外,之前已经很少用于水文研究的二维熵和模糊熵,证明了更好的连续性和相对一致性,更适合于短路和嘈杂的水文时间序列,更有效地识别流流络合性。结果对于识别流流时间序列中的变化点来说非常有用。

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