水文时间序列分析方法研究进展

doi:10.11820/dlkxjz.2013.01.002

Abstract

Abstract: Hydrological time series are usually composed of various components with complicated characteristics.At present it is generally thought that hydrological time series mainly show stochastic,fuzzy,nonlinear, non-stationary,and multi-temporal scale characteristics.In this paper,research progresses on the time series analysis methods to study the characteristics of hydrological processes and their applications are summarized,including serial correlation analysis methods,hydrological frequency analysis methods,fuzzy analysis methods,chaos theories and methods,information entropy theories,and wavelet analysis methods.The main issues and the problems to be solved with regard to the methods mentioned above are discussed,namely,the disadvantages and limitations in their applications to hydrological time series analysis.Finally,it is pointed out that further improvement and optimization of the methods,combination and coupling between the methods,emphasis on the combination of the analyses of physical mechanisms and mathematical statistics,are the key not only to improving the results of hydrological time series analysis,but also to studying and solving the hydrology and water resources issues caused by environmental change.

Key words: chaos, coupling, hydrological time series analysis, information entropy, nonlinearity, uncertainty, wavelet analysis

SANG Yanfang, WANG Zhonggen, LIU Changming. Research progress on the time series analysis methods in hydrology[J].PROGRESS IN GEOGRAPHY, 2013, 32(1): 20-30.

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Research progress on the time series analysis methods in hydrology

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