# Analysis of the Relationship Between Enguri Large Dam Monitoring Entropic Features

## TL;DR

This study analyzes the monitoring data of the Enguri Large Dam to understand how factors like water level and geodynamics affect its stability over time.

## Contribution

The paper introduces the use of nonlinear analysis methods to assess dam stability risks based on long-term monitoring data.

## Key findings

- Nonlinear dynamics of deformation and filling/reloading near the dam are influenced by natural geodynamics and water level changes.
- Long-term monitoring from 1974 to 2024 reveals patterns linked to dam stability and potential risks.
- Modern data analysis techniques like entropy and mutual information help detect changes in dam behavior.

## 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.