class='kwd-title'>Keywords: Wavelet regression, '/> Wavelet regression: An approach for undertaking multi-time scale analyses of hydro-climate relationships
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Wavelet regression: An approach for undertaking multi-time scale analyses of hydro-climate relationships

机译:小波回归:一种进行水-气候关系的多时间尺度分析的方法

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摘要

class="kwd-title">Keywords: Wavelet regression, Multi-time scale analyses, Hydro-climate relationship, Northwest China class="head no_bottom_margin" id="abs0010title">AbstractPrevious studies showed that hydro-climate processes are stochastic and complex systems, and it is difficult to discover the hidden patterns in the and non-stationary data and thoroughly understand the hydro-climate relationships. For the purpose to show multi-time scale responses of a hydrological variable to climate change, we developed an integrated approach by combining wavelet analysis and regression method, which is called wavelet regression (WR). The customization and the advantage of this approach over the existing methods are presented below: class="first-line-outdent" id="lis0005">
  • • The patterns in the data series of a hydrological variable and its related climatic factors are revealed by the wavelet analysis at different time scales.
  • • The hydro-climate relationship of each pattern is revealed by the regression method based on the results of wavelet analysis.
  • • The advantage of this approach over the existing methods is that the approach provides a routing to discover the hidden patterns in the stochastic and non-stationary data and quantitatively describe the hydro-climate relationships at different time scales.
  • 机译:<!-fig ft0-> <!-fig @ position =“ anchor” mode =文章f4-> <!-fig mode =“ anchred” f5-> <!-fig / graphic | fig / alternatives / graphic mode =“ anchored” m1-> class =“ kwd-title”>关键字:小波回归,多时间尺度分析,水与气候的关系,中国西北 class =“ head no_bottom_margin“ id =” abs0010title“>摘要以前的研究表明,水文气候过程是随机且复杂的系统,很难发现非平稳数据中的隐藏模式并难以全面了解水文信息。气候关系。为了显示水文变量对气候变化的多时间尺度响应,我们通过结合小波分析和回归方法(称为小波回归(WR))开发了一种集成方法。下面介绍了这种方法相对于现有方法的定制和优点: class =“ first-line-outdent” id =“ lis0005”> <!-list-behavior =简单前缀-word = mark-type = none max-label-size = 9->
  • •通过小波分析在不同的时间尺度上揭示了水文变量及其相关气候因子数据系列中的模式。
  • •根据小波分析的结果,通过回归方法揭示了每种模式的水-气候关系。
  • •现有方法是,该方法提供了一种路线,以发现随机和非平稳数据中的隐藏模式,并定量描述了不同时间尺度的水-气候关系。
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