Assessment of mountain river streamflow patterns and flood events using information and complexity measures
Assessment of mountain river streamflow patterns and flood events using information and complexity measures
复制标题
利用信息和复杂性措施评估山区河流径流模式和洪水事件
DOI：
10.1016/j.jhydrol.2020.125508
复制
发表时间：
2020
影响因子：
6.4
通讯作者：
K. Kawanisi
中科院分区：
文献类型：
--
作者：
Mohamad Basel Al Sawaf;K. Kawanisi
对不同气候事件的山区河流流量进行明确可解释的评估，可以提高我们对与水文过程有关的各种动态的理解。此外，信息和复杂性度量可以揭示有关系统中发生的不可见过程的宝贵信息。在这项研究中，分析了从山区河流的五个水文站获得的每小时径流记录，以量化不同的模式，并通过增加聚集长度来表征系统在低频和高频下的状态。此外，我们对信息和复杂性理论提出了一个新的扩展，允许它被定制用于洪水评估。此外，我们还阐明了如何通过信息和复杂性度量来适当地定义模式(即词长)。对于低频分析，我们与信息和复杂性度量相关的结果表明，河流流量有两种尺度机制，其中一种可能描述了河流记忆特征。关于高频分析，我们的发现表明，存在一个额外的标度区域，它发生在每小时尺度上，由水流数据捕捉，并使用一种新的水声系统获得。此外，功率谱密度结果证实了我们的发现。我们的研究的另一个重要结果是复杂性和分形波动之间的明显相关性，这一点应该在未来的研究中得到解决。综上所述，这项研究着眼于为检测和理解标准和极端事件期间的水流模式的时间结构而定制的信息和复杂性度量的新方面。
The availability of distinctly interpretable assessments to characterize and describe river discharge for mountainous rivers for different climatic events can improve our understanding of the various dynamics related to hydrological processes. Furthermore, information and complexity metrics can reveal invaluable information about the unseen processes that occur within a system. In this study, hourly streamflow records obtained from five gauging stations of a mountainous river were analyzed to quantify different patterns and characterize system states at both low and high frequencies using increasing aggregation lengths. In addition, we propose a new extension for the information and complexity theory, allowing it to be customized for flood assessment. Moreover, we clarify how a pattern (i.e., a word length) can be suitably defined by means of information and complexity metrics. Regarding low-frequency analyses, our results related to information and complexity metrics indicate two scaling regimes for river discharge, one of which may describe river memory characteristics. Regarding high-frequency analyses, our findings indicate the presence of an additional scaling regime that occurs along an hourly scale, captured by streamflow data, and is obtained using a novel hydroacoustic system. Additionally, power spectral density results confirmed our findings. A further significant result from our study is the clear correlation between complexity and fractal fluctuations, which should be addressed in future studies. In summary, this research focuses on new aspects of information and complexity metrics to be customized for the detection and understanding of temporal structures of streamflow patterns during both standard and extreme events.
DOI：
10.1016/j.ejrh.2018.12.003
发表时间：
2019-02
期刊：
Journal of Hydrology: Regional Studies
影响因子：
--
作者：
Makoto Higashino;H. Stefan
通讯作者：
Makoto Higashino;H. Stefan