Analysis of the Relationship Between Enguri Large Dam Monitoring Entropic Features

In this research, the results of the analysis of Enguri Large Dam (West Georgia) monitoring features, such as foundation displacement data and water level (WL) variation in the reservoir, were investigated. A statistical approach based on calculating time series helps us determine the research area's dynamic picture. In this article, we have used various nonlinear analysis methods. Nonlinear dynamics of deformation and filling/reloading near grand dams reflect the complexity of the mentioned time series, connected with the natural agents (regional and local geodynamics), which were presented even before dam erection, and the effects of the water level variation in the reservoir. Both these effects are documented by observations from 1974 to 2024 at the Enguri Large Dam. Modern linear and nonlinear primarily data analysis techniques will be used for analysis of monitoring characteristics of the Enguri Large Dam: Kullback-Leibler divergence, mutual information, Shannon entropy, and Tsallis entropy. The obtained data on the dynamics of deformation and filling/reloading near a large dam can be used for the assessment of the possible risks connected with abrupt changes in the routine dynamics of construction.

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Journal
Entropy
Published
2025-04-11
DOI
https://doi.org/10.3390/e27040413
Primary Topic
Neural Networks and Applications
Type
article
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article

Analysis of the Relationship Between Enguri Large Dam Monitoring Entropic Features

Ekaterine Mepharidze, Aleksandre Sborshchikovi, Dimitri Tepnadze, T. Chélidzé et al.
Entropy
Neural Networks and Applications
article

Analysis of the Relationship Between Enguri Large Dam Monitoring Entropic Features

Ekaterine Mepharidze, Aleksandre Sborshchikovi, Dimitri Tepnadze, T. Chélidzé, Levan Laliashvili, Teimuraz Matcharashvili
article en

Abstract

In this research, the results of the analysis of Enguri Large Dam (West Georgia) monitoring features, such as foundation displacement data and water level (WL) variation in the reservoir, were investigated. A statistical approach based on calculating time series helps us determine the research area's dynamic picture. In this article, we have used various nonlinear analysis methods. Nonlinear dynamics of deformation and filling/reloading near grand dams reflect the complexity of the mentioned time series, connected with the natural agents (regional and local geodynamics), which were presented even before dam erection, and the effects of the water level variation in the reservoir. Both these effects are documented by observations from 1974 to 2024 at the Enguri Large Dam. Modern linear and nonlinear primarily data analysis techniques will be used for analysis of monitoring characteristics of the Enguri Large Dam: Kullback-Leibler divergence, mutual information, Shannon entropy, and Tsallis entropy. The obtained data on the dynamics of deformation and filling/reloading near a large dam can be used for the assessment of the possible risks connected with abrupt changes in the routine dynamics of construction.

EntropyVol. 27(4)
Tbilisi State University (GE)
Clean water and sanitation
Openalex Percentile: Top 97%
Neural Networks and Applications
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