Based on Copula function and information entropy theory, a comprehensive hydrological network evaluation model

Abstract

The invention discloses an integrated hydrological station network evaluation model based on the combination of Copula function and information entropy theory, comprises the following steps: selectingpotential Archimedean family Copula by using semi-parametric evaluation method, calculating mutual information of two variables and total correlation (TC) of multiple variables; Based on the organiccombination of Copula function theory and information entropy principle, Copula function theory is use to determine that mutual information estimation value under the multi-dimensional variable, MACEsite optimization criterion (minimum value of copula entry, MACE) is proposed, which makes up for the shortcoming of single entropy estimation of mutual information. The invention also adopts three posterior evaluation indexes to have a final evaluation on the model effect: (1) Nash-Sutcliffe efficiency coefficient; (2) negative Copula entropy after averaging; (3) joint information entropy.

Description

technical field [0001] The invention relates to a hydrological station network optimization technology, in particular to a comprehensive hydrological station network evaluation model based on the combination of Copula function and information entropy theory. Background technique [0002] A hydrological station is a grass-roots hydrological institution set up on a river or a river basin, mainly used for observation and collection of hydrological and meteorological data related to water bodies such as rivers, lakes and reservoirs. The work on hydrological laws provides sufficient data support, which largely meets the basic needs of hydrological forecasting, hydrological information, water resources evaluation and water science research. Therefore, a well-planned hydrological station network can fully reflect the characteristics of hydrological spatio-temporal variation, so that accurate and detailed hydrological information can be collected. It is obviously necessary to explor...

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Problems solved by technology

[0003] 1. Mathematical statistics method, which is the earliest application, but requires researchers to have sufficient understanding of the structure of water resources systems; at the same time, limited by the principles of mathematical statistics, the choice of statistical analysis techniques and the number of samples will affect the conclusions of data analysis and this method can only determine the number of sites by estimating the relationship between the accuracy and the number of samples, which fails to achieve the purpose of optimizing the spatial layout of the sites

[0004] 2. Kriging interpolation method needs to make a subjective evaluation on the improvement of hydrological variable estimation error on the map. If the standard deviation of the estimation error is greater than the given standard deviation range, it is necessary to add more stations in the space, otherwise, it should reduce the number of stations , the subjectivity of this method is relatively high in practical applications, and the accuracy is not high enough

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