摘要
用淮河流域代表性测站蚌埠站的多年逐日流量资料建立了洪水时间序列,在计算洪水序列的分维,定量证明洪水系统分形性和混沌性的基础上,对该序列作R/S分析,计算了序列的Hurst指数及其随时间的变化.分析表明:淮河流域洪水序列是分式布朗运动,具有明显的Hurst效应,H值的时间变化反映了洪水系统的演化特征.通过计算反映洪水相空间特征的参数Lyapunov指数和Kolmogorov熵,分析了洪水变化的可预报时间.淮河流域洪水具有短期可预报性,其可预报时间尺度为4～7年,平均可预报时间为5年.
The day-to-day mean flood discharge for the Huaihe River Basin on the basis of information accumulated in Bengbu Hydrolic Station was set up. Based on the flood time series, this paper calculates the fractional dimension of the flood series. The correlative dimension of the flood series reflects the system hierarchy and its fractals characteristics. The smaller the fractal dimension, the more obvious the tendency of the system, and vice versa. The correlative dimension is an important judgment on the complexity of a system. Reconstructing a dynamic system should have at least 8 independent parameters according to dimension (7.1) of the flood discharge series. This is a foundation for the simulation or reconstruction of the flood series. Then this paper conducts R/S analysis and calculates the Hurst exponent. The results show that the flood series of the Huaihe River Basin belong to fractional Brownian notion, and have obvious Hurst effect. The change of Hurst exponent with time demonstrates the evolution feature of flood system.Based on the calculation of the correlative dimension, this paper then calculates Kolmogorov and Lyapunov exponent of flood series, which are two basic parameters reflecting the evolution and inner characteristics of the flood system, and analyze the predictable time of the flood. According to the calculation and analysis results, the flood of the Huaihe River Basin has the characteristic of short-term predictability, and the predictable period is 4 -7 years, the mean predictable periood is 5 years. This sets a basis for the simulation or reconstruction of the flood series.
出处
《南京大学学报（自然科学版）》
CAS
CSCD
北大核心
2003年第1期113-119,共7页
Journal of Nanjing University（Natural Science）
基金
教育部博士点基金(98028432)
