Correlation-aided method for identification and gradation of periodicities in hydrologic time series
文献类型：期刊论文
| 作者 | Xie,Ping3; Wu,Linqian3; Sang,Yan-Fang4; Chan,Faith Ka Shun1,2; Chen,Jie3; Wu,Ziyi3; Li,Yaqing3 |
| 刊名 | Geoscience Letters
 |
| 出版日期 | 2021-04-08 |
| 卷号 | 8期号:1 |
| 关键词 | Periodicity Correlation analysis Significance evaluation Hydrologic time series analysis |
| DOI | 10.1186/s40562-021-00183-x |
| 通讯作者 | Xie,Ping(pxie@whu.edu.cn) ; Sang,Yan-Fang(sangyf@igsnrr.ac.cn) |
| 英文摘要 | AbstractIdentification of periodicities in hydrological time series and evaluation of their statistical significance are not only important for water-related studies, but also challenging issues due to the complex variability of hydrological processes. In this article, we develop a “Moving Correlation Coefficient Analysis” (MCCA) method for identifying periodicities of a time series. In the method, the correlation between the original time series and the periodic fluctuation is used as a criterion, aiming to seek out the periodic fluctuation that fits the original time series best, and to evaluate its statistical significance. Consequently, we take periodic components consisting of simple sinusoidal variation as an example, and do statistical experiments to verify the applicability and reliability of the developed method by considering various parameters changing. Three other methods commonly used, harmonic analysis method (HAM), power spectrum method (PSM) and maximum entropy method (MEM) are also applied for comparison. The results indicate that the efficiency of each method is positively connected to the length and amplitude of samples, but negatively correlated with the mean value, variation coefficient and length of periodicity, without relationship with the initial phase of periodicity. For those time series with higher noise component, the developed MCCA method performs best among the four methods. Results from the hydrological case studies in the Yangtze River basin further verify the better performances of the MCCA method compared to other three methods for the identification of periodicities in hydrologic time series. |
| 语种 | 英语 |
| WOS记录号 | BMC:10.1186/S40562-021-00183-X |
| 出版者 | Springer International Publishing |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/160491]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Xie,Ping; Sang,Yan-Fang |
| 作者单位 | 1.University of Nottingham Ningbo China; School of Geographical Sciences, Faculty of Science and Engineering 2.University of Leeds; Water@Leeds Research Institute 3.Wuhan University; State Key Laboratory of Water Resources and Hydropower Engineering Science 4.Chinese Academy of Sciences; Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research |
| 推荐引用方式 GB/T 7714 | Xie,Ping,Wu,Linqian,Sang,Yan-Fang,et al. Correlation-aided method for identification and gradation of periodicities in hydrologic time series[J]. Geoscience Letters,2021,8(1). |
| APA | Xie,Ping.,Wu,Linqian.,Sang,Yan-Fang.,Chan,Faith Ka Shun.,Chen,Jie.,...&Li,Yaqing.(2021).Correlation-aided method for identification and gradation of periodicities in hydrologic time series.Geoscience Letters,8(1). |
| MLA | Xie,Ping,et al."Correlation-aided method for identification and gradation of periodicities in hydrologic time series".Geoscience Letters 8.1(2021). |
入库方式： OAI收割
来源：地理科学与资源研究所
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