A semi-supervised multi-sensor remote sensing pipeline for mapping irrigation dynamics in ground-truth deficient conflict zones: a case study of the Kakhovka Dam failure

The ongoing war in Ukraine has drawn international attention to the impact of conflict on global agricultural production and food security. On 6 June 2023, the Kakhovka Dam was destroyed. The loss of this critical agricultural and energy infrastructure has left most farmers on the East bank of the Dnipro River without irrigation in Kherson and Zaporizhzhia oblasts. This study develops a multi-sensor Earth Observation framework combining high resolution satellite imagery (Sentinel-2, Landsat) with meteorological data (CHIRPS) and water productivity data (FAO WaPOR), using a semi-supervised machine learning pipeline. Using a rigorous stratified random-sampling approach with photointerpretation, we found pre-war irrigated areas between 2019 to 2021 to be on average 187.94 ± 14.43 kHa, approximately 4% of pre-war baseline cropland and 8% of summer season cropland in Kherson and Zaporizhzhia oblasts. In 2022, these numbers contracted to 140.04 ± 17.44 kHa with the expanded occupation of these territories by Russia, seeing an additional decline in 2023 to 74.97 ± 17.84 kHa. Fields in 2023 also exhibited variability in irrigation, ranging from interrupted irrigation owing to the destruction of the Kakhovka reservoir, to those that were sufficiently irrigated with water remaining in the channels. Irrigated areas diminished further in 2024 to 15.95 ± 9.97 kHa, a ∼91% decline from pre-war averages. Based on inspection, formerly irrigated fields before 2023 were either systematically abandoned or converted to winter cropland with lower input requirements by 2024–a pattern that continued into 2025 (total irrigated area 5.76 ± 0.87 kHa). This study demonstrates the power of advanced EO workflows to precisely quantify agricultural transformation and infrastructural failure in ground-truth deficient, high-risk environments.