关键词: Brown-Forsythe检验, 变异点, 水文时间序列

Abstract:

The dramatic change of hydrological cycle and natural condition and the increasing intensity of human activity usually result in the step trend of streamflow. Change point detection in streamflow series is an important way to understand and diagnose the step trend. Up to now, many methods have been developed to detect the change point, among which the one derived from basic statistics theory is most widely used for its simplicity, but is also limited for its much assumption for data at the same time. In terms of theory of analysis of variance, a detection method based on Brown-Forsythe test is proposed in this paper, which retains the virtue of simplicity and loose the limitation for data. The method based on Brown-Forsythe test is used in change point detection of Kaidu streamflow of Xinjiang which indicates that 1973 and 1986 are two change points. However, other traditional methods take 1990 as the second change point. Which is true? On the one hand, Kaidu river is mainly influenced by climate, especially precipitation and some researches have indicated that the characteri stics of climate and hydrology of Xinjiang changed acutely in 1973 and 1987. On the other hand, taking 1986 as a change point will make not only the level diff erence between separated series but also the step between change point and next year more significant than in 1990. So it is reasonable to make 1973 and 1986 as the real change points and the method based on Brown-Forsythe test is suitable for hydrological time series. The normality and randomness violation of Kaidu streamflow data is probably the main reason for traditional method to get false results. In the future, the research about change point detection will still be focused on improving the sturdiness of methods for skew data.

Key words: Brown-Forsythe test, change points, hydrological time series