Trend detection method for parameterized hydrometeorological extreme value sequence

A detection method and parameterized technology, applied in forecasting, data processing applications, instruments, etc., can solve the problems of hydrometeorological extreme value sequence trend detection only monotonic trend monitoring, etc., to ensure the accuracy of trend detection and simplify the estimation process Effect

Pending Publication Date: 2022-07-05
YANGZHOU UNIV
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Problems solved by technology

[0004] Purpose of the invention: The present invention aims to provide a trend detection method for hydrometeorological extreme value sequences, to solve the problem that the trend detection of hydrometeorological extreme value sequences can only monitor the monotonic trend

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  • Trend detection method for parameterized hydrometeorological extreme value sequence
  • Trend detection method for parameterized hydrometeorological extreme value sequence
  • Trend detection method for parameterized hydrometeorological extreme value sequence

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Embodiment Construction

[0044] The technical solutions of the present invention will be further described below with reference to the accompanying drawings.

[0045] In order to facilitate the understanding of the present invention, firstly, the following description is made to the non-parametric trend test method of hydrometeorological extreme value series—Mann-Kendall trend test method:

[0046] For a two-sided test, the null hypothesis is that the data follow no monotonic trend In order to be able to judge whether the extreme value sequence obeys or obey Assuming that there is a monotonic trend, the Mann-Kendall test statistic is obtained according to the following formula:

[0047]

[0048] In the formula, x j and x k are the jth and kth observations in the extreme value sequence, respectively; sgn(.) is based on x j with x k The sign judgment function of relative size; meanwhile, the variance of statistic S can be obtained according to the following formula:

[0049]

[0050] whe...

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Abstract

The invention discloses a trend detection method of a parameterized hydrometeorological extreme value sequence. The method comprises the following steps: (1) establishing a trend model of the hydrometeorological extreme value sequence by adopting a generalized extreme value distribution GEV function; (2) estimating parameters of a trend model of the hydrometeorological extreme value sequence based on a Bayesian inference framework; and (3) obtaining a Bayesian log-likelihood ratio according to the parameter estimation value of the trend model, and then obtaining the trend of the hydrometeorological extreme value sequence. According to the method, the trend detection precision of the hydrometeorological extreme value sequence is effectively ensured from the parameterization angle; based on the use of a Bayesian statistical inference framework, on one hand, the estimation precision of the distribution parameters of the hydro meteorological extreme value sequence is not influenced by introducing excessive parameters under the condition of a complex trend mode, and on the other hand, the estimation process of the distribution parameters of the hydro meteorological extreme value sequence is simplified by adopting a Gibbs sampling algorithm.

Description

technical field [0001] The invention relates to a trend detection method, in particular to a trend detection method of a hydrometeorological extreme value sequence. Background technique [0002] A major threat to the planet is global warming, which is the result of increased anthropogenic greenhouse gas emissions and is gradually changing the planet's climate patterns. According to the Intergovernmental Panel on Climate Change (IPCC), increasing temperatures have caused dramatic changes in the characteristics of the hydrological water cycle. Therefore, global warming will affect the hydrological process and increase the risk of hydrometeorological extreme events in different parts of the world. In order to effectively predict and prevent the risk of hydrometeorological extreme events, the most critical step is to effectively trend the hydrometeorological extreme events. detection and identification. At present, the trend detection method of the non-parametric method is the...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q10/06G06Q50/26
CPCG06Q10/04G06Q10/0635G06Q50/26
Inventor 徐鹏程仇建春李帆刘赛艳蒋新跃
Owner YANGZHOU UNIV
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