JUSTIFICATION OF THE LIMITING MODULES OF SLOPE INFLOW DURING THE SPRING FLOOD ON THE RIVERS OF VINNYTSIA REGION UNDER CURRENT CLIMATE CONDITIONS

V.А. Ovcharuk; L.V. Kushchenko; О.S. Tymko; V.V. Roik

doi:10.32782/uhj.34-35.2025.05

V.А. Ovcharuk Odesa I. I. Mechnikov National University, 2 Vsevoloda Zmiienka Street, Odesa 65082, Ukraine https://orcid.org/0000-0001-5654-3731
L.V. Kushchenko Odesa I. I. Mechnikov National University, 2 Vsevoloda Zmiienka Street, Odesa 65082, Ukraine
О.S. Tymko Odesa I. I. Mechnikov National University, 2 Vsevoloda Zmiienka Street, Odesa 65082, Ukraine
V.V. Roik Odesa I. I. Mechnikov National University, 2 Vsevoloda Zmiienka Street, Odesa 65082, Ukraine

DOI: https://doi.org/10.32782/uhj.34-35.2025.05

Keywords: maximum runoff, spring flood, slope inflow, Vinnytsia Region, hydrological analysis, climate change, rational water use

Abstract

The relevance of this study is driven by the need to address a key scientific and applied problem—understanding the dynamics of maximum runoff formation during spring floods in the context of increasing climate variability. In Vinnytsia Region, the transformation of snow cover, altered flood genesis, and rising temperatures significantly influence maximum runoff values and associated flood risks. Therefore, identifying limiting characteristics of slope inflow under current climatic conditions is essential for sustainable water management and hydraulic engineering.

Numerous studies have highlighted climate-induced changes in the hydrological regime of Ukrainian rivers; however, the dynamics of slope inflow formation and the spatial variability of maximum runoff modules for the rivers of the Vinnytsia Region remain insufficiently studied. Existing gaps relate primarily to the lack of quantitative assessments of extreme slope inflow modules and their dependence on watershed characteristics under contemporary climate trends.

This article aims to determine the limiting values of maximum slope inflow modules and to assess the current hydrological conditions of spring flood formation using long-term observational data from hydrological stations across Vinnytsia Region.

The study employs classical statistical techniques (method of moments, maximum likelihood estimation, and Kritzky–Menkel gamma distribution), as well as numerical methods for determining slope inflow duration and unevenness, and an operator-based runoff formation model grounded in channel isochrone theory.

Presentation of the main research material. Based on multi-year observational data from 11 hydrological stations, the study demonstrates that current climatic conditions are characterized by a 1.5–2.0 °C rise in mean annual air temperature relative to 1961–1990, a marked decrease in snow cover depth, and a shortened snow-cover duration. These changes reduce the water yield of spring floods or transform them into mixed rain–snowmelt events. The mean spring flood runoff depth varies from 17 to 36 mm, with high spatial variability depending on basin morphology. Numerical calculations show that slope inflow duration ranges from 136 to 404 hours, while the limiting 1% slope inflow modules vary from 0.79 to 2.79 m³/s·km². Watershed elevation was identified as the dominant factor controlling spatial differences, whereas the influence of latitude and forest cover is less pronounced. The spatial distribution of the limiting modules shows the highest values in the northern part of the region (Dnieper basin) and in the upper reaches of the Southern Bug, while the lowest values are characteristic of the rivers of the Dnieper basin within Vinnytsia Region.

The obtained results form an important scientific basis for assessing spring flood hazards, estimating rare-probability maximum discharges, designing hydraulic structures, and developing river basin management plans for the Vinnytsia Region. The study demonstrates that the observed reduction in spring flood water yield under climate change must be integrated into future regional water management and adaptation strategies. Further research will involve expanding the analysis to additional watersheds within the region using broader empirical datasets.

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