Method for identifying hydrologic time sequence nonlinear trend

A hydrological time series, nonlinear technology, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve the problem that the wavelet analysis method lacks a reliable hydrophysical basis and cannot effectively estimate the significance of the nonlinear trend of hydrological series and uncertainties

Active Publication Date: 2015-11-18
INST OF GEOGRAPHICAL SCI & NATURAL RESOURCE RES CAS
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Problems solved by technology

[0005] In view of the above problems, the purpose of the present invention is to provide a method for identifying the nonlinear trend of hydrological time series, so as to solve the problem that the wavelet analysis method in the prior art lacks a reliable hydrophysical basis in the identification of hydrological time series trends, and cannot effectively The Problem of Estimating Significance and Uncertainty in Nonlinear Trends in Hydrological Series

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  • Method for identifying hydrologic time sequence nonlinear trend
  • Method for identifying hydrologic time sequence nonlinear trend
  • Method for identifying hydrologic time sequence nonlinear trend

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Embodiment Construction

[0035] In order to facilitate the understanding of those skilled in the art, the present invention will be further described below in conjunction with the embodiments and accompanying drawings, and the contents mentioned in the embodiments are not intended to limit the present invention.

[0036] refer to Figure 1 to Figure 3 As shown, a method for identifying the nonlinear trend of hydrological time series of the present invention, in an embodiment, the specific implementation process is as follows:

[0037] 1. DWT discrete wavelet transform method

[0038] The measured hydrological time series are often discrete signals. Order L 2 (R) represents a measurable square-integrable function space defined on the real axis, and the signal f(t)∈L 2 (R) discrete wavelet transform (DiscreteWaveletTransform, DWT) can be expressed as:

[0039] W f ( i , k ) = ...

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Abstract

The invention discloses a method for identifying a hydrologic time sequence nonlinear trend. The method comprises: computing the maximum wavelet decomposition level according to a sequence length, and determining a specific discrete wavelet transformation method; obtaining corresponding sub-sequences at different decomposition levels; computing the wavelet energy density value of each sub-sequence to obtain a wavelet energy density function of a to-be-analyzed hydrologic time sequence; decomposing a white noise sequence by use of a discrete wavelet transform method to obtain a sub-sequence; taking the average value of the wavelet energy density function of each white noise sequence as a standard wavelet energy density function, and obtaining a confidence interval of the standard wavelet energy density function; and comparing the positional relationship between the wavelet energy density value of a to-be-analyzed hydrologic time sequence sub-sequence on the maximum time scale and the confidence interval of the standard wavelet energy density function. By adopting the method for identifying the hydrologic time sequence nonlinear trend, the problems that a wavelet analysis method is short of a reliable hydrologic physical basis in the aspect of hydrologic time sequence trend identification and cannot effectively estimate the significance and uncertainty of the hydrologic sequence nonlinear trend are solved.

Description

technical field [0001] The invention relates to the technical field of hydrological science, in particular to a method for identifying the nonlinear trend of hydrological time series. Background technique [0002] Hydrological time series analysis is an important means and technical approach to reveal and understand the changing characteristics of the natural water cycle process. In the process of actual hydrological time series analysis, trend identification and extraction is a very important content, and its main purpose is to reveal the change law of hydrological variables on a large time scale. In addition, in the hydrological time series correlation analysis and spectrum analysis process, it is also necessary to remove the trend item in the hydrological series first to prevent the serial correlation and spectrum analysis results from being affected by non-zero mean or trend. Although there have been a lot of related research on the trend identification of hydrological ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F19/00
Inventor 桑燕芳刘昌明
Owner INST OF GEOGRAPHICAL SCI & NATURAL RESOURCE RES CAS
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