Modeling and forecasting the dynamics of the Buktarma reservoir using artificial intelligence

Abstract

This work is devoted to the study of the use of remote sensing methods for monitoring and forecasting the condition of the Buktarma reservoirs. Effective management of water bodies is becoming an urgent task in the context of climate change and increasing anthropogenic pressure on water resources.
The study examines modern remote sensing technologies, such as the use of satellite imagery and geographic information systems to estimate reservoir extent, water quality, and shoreline changes. Data analysis allows us to identify trends in water levels, as well as predict possible scenarios based on climate change and seasonal fluctuations.
The proposed approach uses convolutional neural networks to accurately identify and segment reservoirs in satellite images. The dataset consists of 196 RGB satellite images, including high-resolution images from
USGS Earth Explorer and ESA Sentinel Data Hub, from 2000 to 2023.