小波分析方法在水文学研究中的应用现状及展望
Applications of wavelet analysis to hydrology: Status and prospects
查看参考文献58篇
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文摘
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本文首先介绍了小波分析的基本方法,主要包括小波函数、小波变换和小波消噪等。然后从6个方面,即基于连续小波变换的水文序列多时间尺度变化特性分析、基于离散小波变换的水文序列分解和重构、水文过程复杂性定量描述、水文序列小波消噪、水文序列小波互相关分析和基于小波方法的水文序列模拟预报技术,综述了小波分析方法在水文学各领域的研究应用现状和主要不足,以及存在的关键和难点问题。最后,对小波分析方法在今后的水文学研究中的应用进行了展望,并就小波函数选择、小波阈值消噪、小波分解、小波互相关分析、水文序列小波预报等具体问题提出了建议。 |
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其他语种文摘
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In this paper, wavelet analysis methods, mainly including wavelet basis function, continuous and discrete wavelet transform and wavelet threshold de-noising, were introduced first. Then, current researches and applications of the wavelet analysis methods to various aspects of hydrology were summarized and reviewed from three points of view: research significance, current researches and applications, and key and difficult problems and the inadequate applications to hydrology. The six aspects of wavelet-based hydrologic analysis include: continuous wavelet-based analysis of hydrologic time series' characteristics under multi-temporal scales, discrete wavelet decomposition and reconstruction different sub-signals of hydrologic time series, quantification of complicated variability of hydrologic processes, wavelet de-noising in hydrologic time series, wavelet cross-correlation analysis of hydrologic time series, and wavelet-based hydrologic time series simulation and forecasting. Finally, several suggestions and opinions on the future researches and applications of wavelet analysis methods in hydrology were discussed. They focus on selection of wavelet basis function, wavelet threshold de-noising, wavelet decomposition, wavelet cross-correlation analysis, and wavelet aided forecasting. |
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来源
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地理科学进展
,2013,32(9):1413-1422 【核心库】
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关键词
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水文时间序列分析
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小波分析
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水文预报
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水文水资源
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不确定性
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地址
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中国科学院地理科学与资源研究所, 中国科学院陆地水循环与地表过程重点实验室, 北京, 100101
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语种
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中文 |
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文献类型
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综述型 |
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ISSN
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1007-6301 |
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学科
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自然地理学 |
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基金
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国家自然科学基金项目
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文献收藏号
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CSCD:4951755
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