Mapping of the spatiotemporal transformations of the former Kakhovka reservoir bed after dam destruction using Sentinel-2 satellite imagery
DOI:
https://doi.org/10.36023/ujrs.2025.12.4.296Keywords:
Kakhovka Reservoir, hydrological regime, surface water occurrence, ecosystems, ecotopes, remote sensing, Sentinel-2, NDWIAbstract
After the destruction of the Kakhovka Reservoir dam on June 6, 2023, a rapid water outflow occurred, resulting in the extensive exposure of the reservoir bed. The spatiotemporal transformations of this bed are ongoing, resulting in the formation of new natural complexes with heterogeneous moisture conditions. The dynamics of water area distribution within the bed depend not only on geomorphological features but also on climatic factors such as seasonal temperature variations, precipitation levels, and evaporation rates. Assessing these indicators is crucial for forecasting future landscape changes and evaluating their potential use.
However, due to active military actions in the region, ground-based research was not feasible; therefore, remotely sensed data was utilized. An algorithm was developed to construct a Surface Water Occurrence Map (SWOM) using Sentinel-2 multispectral imagery. The SWOM construction involves four steps: 1) selection of satellite images due to the specified requirements; 2) calculation of the NDWI spectral index for each image; 3) conversion of each NDWI layer into a binary water mask; and 4) fusion of all water masks into a single SWOM that reflects the frequency of surface water occurrence in each pixel.
Following this algorithm, the SWOM of the former Kakhovka Reservoir bed was generated based on 12 cloud-free Sentinel-2 images acquired between June 20, 2023, and September 26, 2024. For visualization and interpretation, the obtained SWOM was divided into six classes. Class 1 represents pixels that were never covered by water (dry land), while Class 6 includes those where water was present throughout the entire study period. Classes 2 – 5 reflect intermediate frequencies. For each class, the area and ecological characteristics (i.e., ecotopes and vegetation) were analyzed in detail. Considering that meteorological conditions (precipitation and air temperature) affect the hydrological regime, data from weather stations in the cities of Zaporizhia, Nikopol, and Kherson were also analyzed. The study reveals a correspondence between observed meteorological conditions and the dynamics of the water surface area within the bed.
Thus, the constructed SWOM provides an effective tool for forecasting the regime and development of future ecosystems in the area.
Author Contributions: Conceptualization: L. P. Lischenko and A. O. Kozlova; Methodology: A. A. Andreiev; Formal Analysis and Data Processing: A. A. Andreiev; Investigation: A.A. Andreiev and L. P. Lischenko; Writing – Original Draft Preparation: A.A. Andreiev and L. P. Lischenko; Writing – Review & Editing: A. O. Kozlova. All authors have read and agreed to the published version of the manuscript.
Funding: This research was carried out within the framework of the R&D project “Remote methods for addressing sustainable development and rational land use issues based on comprehensive analysis of heterogeneous geospatial data”, RC 0224U000990.
Data Availability Statement: Data available on reasonable request from the authors.
Acknowledgments: The authors are grateful to the National Academy of Sciences of Ukraine for supporting this research. We are also grateful to the reviewers and editors for their valuable comments, recommendations, and attention to the work.
Conflicts of Interest: The authors declare no conflict of interest
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