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Gradation of the significance level of trends in precipitation over China
Xie, Ping1,2; Zhao, Yuxi1; Sang, Yan-Fang3,4; Gu, Haiting1; Wu, Ziyi1; Singh, Vijay P.5,6
2018-12-01
Source PublicationHYDROLOGY RESEARCH
ISSN0029-1277
Volume49Issue:6Pages:1890-1901
Corresponding AuthorSang, Yan-Fang(sangyf@igsnrr.ac.cn)
AbstractHow to accurately detect and estimate the significance level of trends in hydroclimate time series is a challenge. Building on correlation analysis, we propose an approach for evaluating and grading the significance level of trend in a series, and apply it to evaluate the changes in annual precipitation in China. The approach involved first formulating the relationship between the correlation coefficient and trend's slope. Four correlation coefficient thresholds are then determined by considering the influence of significance levels and data length, and the significance of trends is graded as five levels: no, weak, moderate, strong and dramatic. A larger correlation coefficient reflects a larger slope of trend and its higher significance level. Results of Monte-Carlo experiments indicated that the correlation coefficient-based approach not only reflects the magnitude of a trend, but also considers the influence of dispersion degree and mean value of the original series. Compared with the Mann-Kendall test used commonly, the proposed approach gave more accurate and specific gradation of the significance level of trends in annual precipitation over China. We find that the precipitation trends over China are not uniform, and the effects of global climate change on precipitation are not strong and limited to some regions.
Keyworddetection and attribution global climate change hydrological variability significance stochastic process trend
DOI10.2166/nh.2018.187
WOS KeywordMANN-KENDALL ; CLIMATE VARIABILITY ; CONTINENTAL US ; RIVER-BASIN ; TIME-SERIES ; ARID REGION ; STREAMFLOW ; CONSTRAINTS ; TEMPERATURE ; PATTERNS
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[91547205] ; National Natural Science Foundation of China[91647110] ; National Natural Science Foundation of China[51579181] ; Program for the 'Bingwei' Excellent Talents from the Institute of Geographic Sciences and Natural Resources Research, CAS ; Youth Innovation Promotion Association CAS[2017074] ; National Mountain Flood Disaster Investigation Project[SHZH-IWHR-57]
Funding OrganizationNational Natural Science Foundation of China ; Program for the 'Bingwei' Excellent Talents from the Institute of Geographic Sciences and Natural Resources Research, CAS ; Youth Innovation Promotion Association CAS ; National Mountain Flood Disaster Investigation Project
WOS Research AreaWater Resources
WOS SubjectWater Resources
WOS IDWOS:000452413800014
PublisherIWA PUBLISHING
Citation statistics
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/51388
Collection中国科学院地理科学与资源研究所
Corresponding AuthorSang, Yan-Fang
Affiliation1.Wuhan Univ, State Key Lab Water Resources & Hydropower Engn S, Wuhan 430072, Hubei, Peoples R China
2.Collaborat Innovat Ctr Terr Sovereignty & Maritim, Wuhan 430072, Hubei, Peoples R China
3.Chinese Acad Sci, Key Lab Water Cycle & Related Land Surface Proc, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
4.Univ Washington, Dept Atmospher Sci, Seattle, WA 98195 USA
5.Texas A&M Univ, Dept Biol & Agr Engn, 321 Scoates Hall,2117 TAMU, College Stn, TX 77843 USA
6.Texas A&M Univ, Zachry Dept Civil Engn, 321 Scoates Hall,2117 TAMU, College Stn, TX 77843 USA
Recommended Citation
GB/T 7714
Xie, Ping,Zhao, Yuxi,Sang, Yan-Fang,et al. Gradation of the significance level of trends in precipitation over China[J]. HYDROLOGY RESEARCH,2018,49(6):1890-1901.
APA Xie, Ping,Zhao, Yuxi,Sang, Yan-Fang,Gu, Haiting,Wu, Ziyi,&Singh, Vijay P..(2018).Gradation of the significance level of trends in precipitation over China.HYDROLOGY RESEARCH,49(6),1890-1901.
MLA Xie, Ping,et al."Gradation of the significance level of trends in precipitation over China".HYDROLOGY RESEARCH 49.6(2018):1890-1901.
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