A Method for Identifying Nonlinear Trends in Hydrological Time Series

A hydrological time series, nonlinear technology, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve the problem that wavelet analysis methods lack a reliable hydrological physical basis, and cannot effectively estimate the significance of nonlinear trends in hydrological series. and uncertainty

Active Publication Date: 2017-10-24
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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  • A Method for Identifying Nonlinear Trends in Hydrological Time Series
  • A Method for Identifying Nonlinear Trends in Hydrological Time Series
  • A Method for Identifying Nonlinear Trends in Hydrological Time Series

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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 (Discrete Wavelet Transform, DWT) can be expressed as:

[0039]

[0040] In the formula, a 0 and b 0 Both are constants, i represents the decomposition level (Decomposition Level, DL; also called th...

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Abstract

The invention discloses a method for identifying the nonlinear trend of hydrological time series, which includes: calculating the maximum wavelet decomposition level according to the sequence length, and determining a specific discrete wavelet transformation method; obtaining corresponding subsequences at different decomposition levels; calculating the subsequences of each subsequence The wavelet energy density value of the hydrological time series to be analyzed is obtained by using the wavelet energy density value; the white noise sequence is decomposed by the discrete wavelet transform method to obtain subsequences; the mean value of the wavelet energy density function of each white noise sequence is used as the standard wavelet energy density function to obtain The confidence interval of the standard wavelet energy density function; compare the positional relationship between the wavelet energy density value of the hydrological sequence subsequence to be analyzed on the largest time scale and the confidence interval of the standard wavelet energy density function. The invention solves the problem that the wavelet analysis method lacks a reliable hydrological physical basis in the recognition of the hydrological time series trend, and cannot effectively estimate the significance and uncertainty of the non-linear trend of the hydrological series.

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 ...

Claims

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Application Information

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Patent Type & Authority Patents(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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