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基于Hurst系数法和Bartels检验的水文变异联合分级方法可以从整体上识别与检验时间序列变异及其变异程度,但无法判断序列的具体变异形式(趋势、跳跃、周期等).基于相关系数描述序列与时序的相关性大小以及表征序列趋势变异程度的特性,提出了基于相关系数的水文趋势变异分级方法.该方法首先计算序列的相关系数,然后作假设检验:依据统计学原理和经验选用不同的阈值作为不同变异程度的划分依据,并将相关系数划分成5个区间,对应于无变异、弱变异、中变异、强变异和巨变异5个等级.实际应用中,根据相关系数的大小判断其落在哪个区间,即可确定序列是否发生趋势变异及变异程度的大小.对5个实例序列42年资料的变异分析表明,枝城站年径流序列无趋势变异,兰州站和花园口站年径流分别为趋势弱变异和中变异,荆江三口分流量为趋势强变异,红崖山站年径流为趋势巨变异,上述结果与采用Hurst系数法所得整体变异分级结果是一致的;成因分析表明,不同强度的人类活动导致了序列发生不同程度的变异.
Based on the Hurst coefficient method and the Bartels test, the joint classification of hydrological variables can identify and test the time series variation and its degree of variation as a whole, but can not judge the specific variation forms (trends, jumps, periods, etc.) of the sequences. And the correlation between the trend and the degree of sequence characterization, this paper proposes a method of classification and classification of hydrological trend based on the correlation coefficient, which first calculates the correlation coefficient of the sequence and then makes a hypothesis test: According to the statistical principle and experience, The threshold value is used as the basis for dividing different degrees of variation, and the correlation coefficient is divided into five intervals corresponding to five levels of no variation, weak variation, medium variation, strong variation and huge variation.In practice, according to the size of the correlation coefficient In which interval, we can determine whether the trend of the sequence variation and the degree of variation.The analysis of the 42-year data of five sample sequences shows that there is no trend variation in the annual runoff sequence of Zhicheng station, and the annual runoff of Lanzhou station and Huayuankou station Respectively, the trend of weak variation and variation, Jingjiang three sub-flow trend of strong variation, Hongyashan Station Runoff is a huge trend of variation, variation of the above results with the classification results obtained with the overall method is the same coefficient of Hurst; cause analysis showed different intensities of human activities of varying degrees of sequence variability occurs.