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Temporal Change Analysis Based on Data Characteristics and Nonparametric Test

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  • Dingfang Li
  • Huantian Xie
  • Lihua Xiong

Abstract

Based on data characteristics and nonparametric test, a new statistical temporal change analysis approach is proposed. The new approach consists of data characteristics analysis, temporal change analysis (including both change point and trend analysis), and result interpretation. Data characteristics are firstly investigated, especially with respect to the assumptions of independence and normality. Then proper nonparametric methods are chosen based on the detected characteristics of the observed data to analyze change points and monotonous linear trend for each of the segments divided by the change points. To avoid shortcoming of the traditional approach of carrying out the trend analysis before change point analysis, it is proposed in this paper that change point detection be performed before trend analysis. At last, statistical analysis results are interpreted according to the physical mechanism of observations. As a study case, the proposed approach has been carried out on three annual discharge series of the Yangtze River at the Yichang hydrological station. The investigations of data characteristics show that the observed data do not meet the assumptions of being independent and identically Gaussian-distributed. So the nonparametric Pettitt’s test was adopted to detect abrupt changes in the mean levels, followed by trend analysis using the nonparametric Mann-Kendall (MK) test. Results indicate the proposed approach is both reliable and reasonable for the temporal change analysis. Copyright Springer Science+Business Media Dordrecht 2014

Suggested Citation

  • Dingfang Li & Huantian Xie & Lihua Xiong, 2014. "Temporal Change Analysis Based on Data Characteristics and Nonparametric Test," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(1), pages 227-240, January.
    • Handle: RePEc:spr:waterr:v:28:y:2014:i:1:p:227-240
    DOI: 10.1007/s11269-013-0481-2
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    References listed on IDEAS

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    1. Qiang Zhang & Chong-Yu Xu & Tao Yang, 2009. "Variability of Water Resource in the Yellow River Basin of Past 50 Years, China," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 23(6), pages 1157-1170, April.
    2. Sheng Yue & ChunYuan Wang, 2004. "The Mann-Kendall Test Modified by Effective Sample Size to Detect Trend in Serially Correlated Hydrological Series," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 18(3), pages 201-218, June.
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    1. Lihua Xiong & Tao Du & Chong-Yu Xu & Shenglian Guo & Cong Jiang & Christopher Gippel, 2015. "Non-Stationary Annual Maximum Flood Frequency Analysis Using the Norming Constants Method to Consider Non-Stationarity in the Annual Daily Flow Series," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(10), pages 3615-3633, August.
    2. Hang Zeng & Ping Feng & Xin Li, 2014. "Reservoir Flood Routing Considering the Non-Stationarity of Flood Series in North China," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(12), pages 4273-4287, September.
    3. Jianzhu Li & Senming Tan & Zhaozhen Wei & Fulong Chen & Ping Feng, 2014. "A New Method of Change Point Detection Using Variable Fuzzy Sets Under Environmental Change," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(14), pages 5125-5138, November.
    4. Wentao Xu & Cong Jiang & Lei Yan & Lingqi Li & Shuonan Liu, 2018. "An Adaptive Metropolis-Hastings Optimization Algorithm of Bayesian Estimation in Non-Stationary Flood Frequency Analysis," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(4), pages 1343-1366, March.
    5. Huantian Xie & Dingfang Li & Lihua Xiong, 2016. "Exploring the Regional Variance using ARMA-GARCH Models," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(10), pages 3507-3518, August.
    6. Brian Thomas & James Famiglietti, 2015. "Sustainable Groundwater Management in the Arid Southwestern US: Coachella Valley, California," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(12), pages 4411-4426, September.
    7. Weibin Zhang & Xiaochun Zha & Jiaxing Li & Wei Liang & Yugai Ma & Dongmei Fan & Sha Li, 2014. "Spatiotemporal Change of Blue Water and Green Water Resources in the Headwater of Yellow River Basin, China," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(13), pages 4715-4732, October.

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