Determination of daily time series’ reasonable length during chaotic identification
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Abstract:
Chaotic theory is an important means of hydrology time series analysis. In order to get reliable analysis results, it is recommended to make a full use of time series. But the research about how the length of time series affects the identification of chaotic characteristics is rare. In this paper, we carried out a study about the responding effect of the maximum Lyapunov exponent to the length of time series with the use of daily runoff time series of gauged stations named Wulong and Beibei in Yangtze River. The result suggested that short daily runoff time series would affect the result of chaotic identification and make the result unreliable; besides, when the length of daily runoff time series reached 3000, the chaotic characteristics became stable and reliable, and it saved a lot of computing time at the same time.
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Project Supported:
National Natural Science Foundation of China (51479061).
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