Moving correlation coefficient-based method for jump points detection in hydroclimate time series

doi:10.1007/s00477-019-01727-6

	Moving correlation coefficient-based method for jump points detection in hydroclimate time series
	Wu, Ziyi 2; Xie, Ping 2,3; Sang, Yan-Fang 1; Chen, Jie 2; Ke, Wei 2; Zhao, Jiangyan 2; Zhao, Yuxi 4
刊名	STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
	2019-10-01
卷号	33 期号:10 页码:1751-1764
关键词	Jump point Correlation analysis Significance evaluation Hydroclimatic process Upper-Mekong River
ISSN号	1436-3240
DOI	10.1007/s00477-019-01727-6
通讯作者	Xie, Ping(pxie@whu.edu.cn) ; Sang, Yan-Fang(sangyf@igsnrr.ac.cn)
英文摘要	The jump points detection is critical to the understanding of hydrologic variability, especially in investigating the anthropogenic effects. Conventional methods are mainly statistical and cannot directly reflect the jump change degrees. This article proposes a moving correlation coefficient-based detection (MCCD) method for the detection of jump points (JPs) in hydroclimate data. The correlation coefficient (CC) between the potential jump component and the original data is calculated, and the CC series is realized by moving from the starting to the ending points of the original time series. Bigger CC value reflects higher jump degree; the position with the biggest absolute CC value is the JP that is the most expected. Its significance is evaluated by comparing its value with the CC threshold value at the relevant significance level. Monte-Carlo experimental results verify the MCCD method's higher efficiency compared with four commonly used conventional methods. It is especially noteworthy that the results indicate its stable efficiency, even when encountering the influences of some unfavorable factors. By applying the MCCD method to the Lancang River Basin, the JP of runoff in 2004 is detected at the Yunjinghong station in the lower reach. It is mainly attributed to the construction and operation of some major water hydropower projects, while the stable variations of areal precipitation and actual evapotranspiration, as well as the stable land-cover conditions, contribute little to the abrupt decrease in runoff. The MCCD method can be an effective alternative for the detection of JPs in hydroclimate data.
资助项目	National Natural Science Foundation of China[91547205] ; National Natural Science Foundation of China[91647110] ; National Natural Science Foundation of China[51579181] ; National Natural Science Foundation of China[51779176] ; Strategic Priority Research Program of Chinese Academy of Sciences[XDA20060402] ; Youth Innovation Promotion Association CAS[2017074]
WOS关键词	ABRUPT CHANGES ; WATER-BALANCE ; MEKONG RIVER ; EL CHICHON ; PRECIPITATION ; RUNOFF ; BASIN ; VARIABILITY ; ERUPTIONS
WOS研究方向	Engineering ; Environmental Sciences & Ecology ; Mathematics ; Water Resources
语种	英语
出版者	SPRINGER
WOS记录号	WOS:000491084300006
资助机构	National Natural Science Foundation of China ; Strategic Priority Research Program of Chinese Academy of Sciences ; Youth Innovation Promotion Association CAS
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/129786]
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.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Water Cycle & Related Land Surface Proc, Beijing 100101, Peoples R China 2.Wuhan Univ, State Key Lab Water Resources & Hydropower Engn S, Wuhan 430072, Hubei, Peoples R China 3.Collaborat Innovat Ctr Terr Sovereignty & Maritim, Wuhan 430072, Hubei, Peoples R China 4.Southwest Branch State Grid, Chengdu 610000, Sichuan, Peoples R China
推荐引用方式 GB/T 7714	Wu, Ziyi,Xie, Ping,Sang, Yan-Fang,et al. Moving correlation coefficient-based method for jump points detection in hydroclimate time series[J]. STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT,2019,33(10):1751-1764.
APA	Wu, Ziyi.,Xie, Ping.,Sang, Yan-Fang.,Chen, Jie.,Ke, Wei.,...&Zhao, Yuxi.(2019).Moving correlation coefficient-based method for jump points detection in hydroclimate time series.STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT,33(10),1751-1764.
MLA	Wu, Ziyi,et al."Moving correlation coefficient-based method for jump points detection in hydroclimate time series".STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT 33.10(2019):1751-1764.