Assessment of the dynamics of the surface area of the Shatsk Lakes over a long-term period based on remote sensing data in connection with fluctuations in their level (1985–2023)

The purpose of the article was to assess the long-term dynamics of the area of the Shatsk Lakes (Volyn region, Ukraine) and the spread of water blooms on their surface using remote sensing data in connection with fluctuations in the level of these water bodies for the period 1985-2023. Satellite images from the American Landsat-5,7,8 mission and the European Sentinel-2 L2A mission were used. Long-term data from state monitoring were also used to monitor: a) water level at the hydrological station of Svitiaz Lake; b) the amount of precipitation at the Svitiaz weather station. It was established that the area of the Shatsk Lakes (Svitiaz, Liutsymer, Chorne Velyke) over the long study period, obtained using satellite images using the NDWI (Normalized Difference Water Index), ranged as follows as a percentage of the average annual values of the lake’s surface: Svitiaz – 85–101 %; Liutsymer – 85–100 %; Chorne Velyke – 79–100 %. The area of water bloom in these lakes over the long study period, obtained using satellite images using the NDTI (Normalized Difference Turbidity Index), ranged as follows as a percentage of the average annual values of lake’s surface: Svitiaz – 0.04–4.43 %; Liutsymer – 0.2–7.9 %; Chorne Velyke – 0.1–11.9 %. Among the studied lakes, minimal water bloom was observed in the largest among them, Svitiaz, which indicates its better ecological condition. The maximum bloom of water was typical for the small Chorne Velyke Lake. Variations in the area of lakes, water levels and the amount of precipitation are interconnected, which was confirmed by the example of Svitiaz Lake. The resulting pair correlation coefficients (r) between these characteristics are 0.6–0.7. In 2023, the area of Svitiaz Lake was the largest in the last 10 years, as the water level in the lake was also the highest in a decade, which is mainly due to good winter snow reserves. The use of remote sensing techniques to study the morphometric parameters of lakes can provide valuable results for identifying environmental problems. An in-depth study of these problems can take place in nature using instrumental methods, water sampling and analysis.