A Practical Guide to Discrete Wavelet Decomposition of Hydrologic Time Series

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	A Practical Guide to Discrete Wavelet Decomposition of Hydrologic Time Series
	Sang Yan-Fang
	2012
关键词	Wavelet decomposition Discrete wavelet transforms Intelligent systems Time series analysis Uncertainty analysis
英文摘要	Discrete wavelet transform (DWT) is commonly used for wavelet threshold de-noising, wavelet decomposition, wavelet aided hydrologic series simulation and prediction, as well as many other hydrologic time series analyses. However, its effectiveness in practice is influenced by many key factors. In this paper the "reference energy function" was firstly established by operating Monte-Carlo simulation to diverse noise types; then, energy function of hydrologic series was compared with the reference energy function, and four key issues on discrete wavelet decomposition were studied and the methods for solving them were proposed, namely wavelet choice, decomposition level choice, wavelet threshold de-noising and significance testing of DWT, based on which a step-by-step guide to discrete wavelet decomposition of hydrologic series was provided finally. The specific guide is described as: choose appropriate wavelet from the recommended wavelets and according to the statistical characters relations among original series, de-noised series and removed noise; choose proper decomposition levels by analyzing the difference between energy function of the analyzed series and reference energy function; then, use the chosen wavelet and decomposition level, estimate threshold according to series' complexity and set the same threshold under each level, and use the mid-thresholding rule to remove noise; finally, conduct significance testing of DWT by comparing energy function of the de-noised series with the reference energy function. Analyses of both synthetic and observed series indicated the better performance and easier operability of the proposed guide compared with those methods used presently. Following the guide step by step, noise and different deterministic components in hydrologic series can be accurately separated, and uncertainty can also be quantitatively estimated, thus the discrete wavelet decomposition result of series can be improved. 2012 Springer Science+Business Media B.V.
出处	Water Resources Management
卷	26 期:11 页:3345-3365
收录类别	EI
语种	英语
内容类型	EI期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/27669]
专题	地理科学与资源研究所_历年回溯文献
推荐引用方式 GB/T 7714	Sang Yan-Fang. A Practical Guide to Discrete Wavelet Decomposition of Hydrologic Time Series. 2012.