Satellite-Based Assessment of Post-Disaster Landscape Renaturalization in the Former Kakhovka Reservoir (2023–2026)

Remote Sensing for Environmental Monitoring

Authors

First and Last Name Academic degree E-mail Affiliation
Yevhen Tsyhanok Ph.D. e.tsiganok [at] gmail.com Taras Shevchenko National University of Kyiv
Kyiv, Ukraine
Kateryna Kinash No Kateryna.Kinash [at] lnu.edu.ua Ivan Franko National University of Lviv
Lviv, Ukraine
Yelyzaveta Temchenko No elizatem211 [at] gmail.com Taras Shevchenko National University of Kyiv
Kyiv, Ukraine

I and my co-authors (if any) authorize the use of the Paper in accordance with the Creative Commons CC BY license

First published on this website: 03.07.2026 - 17:25
Abstract 

The destruction of the Kakhovka Dam in 2023 triggered one of the largest hydrological disturbances in contemporary Europe, resulting in the rapid drainage of the 2,155 km² Kakhovka Reservoir and exposing the former floodplain landscapes of the historic Velykyi Luh. Initial assessments predicted prolonged land degradation, extensive aeolian erosion, and regional desertification. This study evaluates the subsequent trajectory of landscape transformation using multi-temporal Sentinel-2 imagery acquired between 2023 and 2026. Surface reflectance Level-2A products were processed to derive the Normalized Difference Vegetation Index (NDVI) and the Gao Normalized Difference Water Index (NDWI). The complementary application of these spectral indices enabled simultaneous assessment of vegetation development and substrate moisture dynamics throughout the post-disaster succession. The NDWI time series documents the abrupt collapse of the reservoir's hydrological regime immediately after dam failure, followed by the stabilization of moisture conditions along relic river channels and newly developing floodplain corridors. Concurrently, NDVI reveals exceptionally rapid vegetation establishment, progressing from nearly barren exposed sediments in June 2023 to dense vegetation cover by June 2026. The results demonstrate that the former reservoir has followed a rapid natural renaturalization pathway rather than the previously anticipated desertification scenario. The combined use of NDVI and NDWI derived from freely available Sentinel-2 imagery provides an efficient, reproducible framework for monitoring post-disaster landscape dynamics, particularly within conflict-affected regions where conventional field investigations remain severely constrained. The findings provide an important scientific basis for future ecological restoration planning, protected area expansion, and long-term environmental monitoring of the recovering Velykyi Luh landscape.

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