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Chinese Journal of Applied Ecology ›› 2018, Vol. 29 ›› Issue (4): 1042-1050.doi: 10.13287/j.1001-9332.201804.012

• Special Features of Hydrological Variability and Inconsistency • Previous Articles     Next Articles

Correlation coefficient-based principle and method for the classification of jump degree in hydrological time series

WU Zi-yi1, XIE Ping1,2, SANG Yan-fang3*, GU Hai-ting1   

  1. 1State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China;
    2Collaborative Innovation Center for Territorial Sovereignty and Maritime Rights, Wuhan 430072, China;
    3Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;
  • Received:2017-06-03 Online:2018-04-18 Published:2018-04-18
  • Contact: * E-mail: sangyf@igsnrr.ac.cn
  • Supported by:

    This work was supported by the National Natural Science Foundation of China (91547205, 91647110, 51579181), the Water Engineering and Science Project of Hunan Province (Xiangshuikeji [2015]13-21) and the ‘Bingwei’ Youth Innovation Promotion Association of Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences.

Abstract: The phenomenon of jump is one of the importantly external forms of hydrological variabi-lity under environmental changes, representing the adaption of hydrological nonlinear systems to the influence of external disturbances. Presently, the related studies mainly focus on the methods for identifying the jump positions and jump times in hydrological time series. In contrast, few studies have focused on the quantitative description and classification of jump degree in hydrological time series, which make it difficult to understand the environmental changes and evaluate its potential impacts. Here, we proposed a theatrically reliable and easy-to-apply method for the classification of jump degree in hydrological time series, using the correlation coefficient as a basic index. The statistical tests verified the accuracy, reasonability, and applicability of this method. The relationship between the correlation coefficient and the jump degree of series were described using mathematical equation by derivation. After that, several thresholds of correlation coefficients under different statistical significance levels were chosen, based on which the jump degree could be classified into five levels: no, weak, moderate, strong and very strong. Finally, our method was applied to five diffe-rent observed hydrological time series, with diverse geographic and hydrological conditions in China. The results of the classification of jump degrees in those series were closely accorded with their physically hydrological mechanisms, indicating the practicability of our method.