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应用生态学报 ›› 2018, Vol. 29 ›› Issue (4): 1042-1050.doi: 10.13287/j.1001-9332.201804.012

• 水文变异与非一致性专栏 • 上一篇    下一篇

基于相关系数的水文序列跳跃变异分级原理与方法

吴子怡1, 谢平1,2, 桑燕芳3*, 顾海挺1   

  1. 1武汉大学水资源与水电工程科学国家重点实验室, 武汉 430072;
    2国家领土主权与海洋权益协同创新中心, 武汉 430072;
    3中国科学院地理科学与资源研究所陆地水循环与地表过程重点实验室, 北京 100101;
  • 收稿日期:2017-06-03 出版日期:2018-04-18 发布日期:2018-04-18
  • 通讯作者: * E-mail: sangyf@igsnrr.ac.cn
  • 作者简介:吴子怡,女,1992年生,博士研究生.主要从事变化环境下的水文水资源研究.E-mail: wuziyi@whu.edu.cn
  • 基金资助:

    本文由国家自然科学基金项目(91547205,91647110,51579181)、湖南省水利科技项目(湘水科计【2015】13-21)和中国科学院地理科学与资源研究所“秉维”优秀青年人才计划项目资助

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.

摘要: 跳跃变异是环境变化影响下水文过程发生急剧变化的一种重要表现形式,体现了水文非线性系统对外界干扰的响应.目前研究主要是对序列跳跃变异发生的时间、次数等进行识别和检验,但缺乏对其变异程度进行定量描述和分级,给开展流域环境变化研究及其影响评价带来很大困难.本文选取相关系数作为基础指标,提出了一种理论严密且便于应用的水文序列跳跃变异分级方法,并利用统计试验验证了文中方法对变异点显著性的检验精度,以及跳跃变异分级原理的合理性和分级方法的可靠性.经推导相关系数与跳跃变异相对幅度的关系,选取不同显著水平下的若干典型相关系数值作为分级阈值,将跳跃变异程度划分为无变异、弱变异、中变异、强变异、巨变异5个等级.通过应用于分析我国不同气候区的5个实测水文序列,结合物理成因分析验证了该方法的实用性.

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.