LONG-TERM SPATIAL FORECASTING OF MAXIMUM MELT-RAINFALL RUNOFF OF RIVERS OF UKRAINIAN POLISSYA
RAINFALL RUNOFF OF RIVERS OF UKRAINIAN POLISSYA

Climate change induces water resource redistribution and increases the risk of flooding in Ukraine. The application of the EU Flood Directive and the adaptation of Ukraine's legislation to EU standards are crucial for effectively managing hydrological risks and ensuring environmental protection concerning water resource utilization. Furthermore, predictive monitoring of water bodies during periods of maximum river discharge is of paramount importance for planning protective measures against territorial inundation and safeguarding critical infrastructure.

The research focuses on the rivers of Ukrainian Polissya, which are characterized by the formation of maximum runoff from snowmelt and rainfall during the winter-spring period. The purpose of this study is to utilize a mathematical model for spatial long-term forecasting of characteristics related to maximum melt-rainfall runoff in lowland rivers and to apply automated methods for annual hydrological monitoring of the sizes of maximum runoff through prediction and cartographic representation using computer tools.

Analyzing the beginning dates of spring floods over a long period (from the beginning of flow observations on rivers up to 2023), it can be observed that there is a tendency towards earlier development of spring processes in rivers of the Ukrainian Polissya region. Hence, in recent years, the notable features, under the conditions of an unstable winter temperature regime, low snow accumulation, and uneven snow accumulation, have been the occurrence of floods from snowmelt and rainfall in earlier, almost winter periods (in 2019, 2020, 2021, 2022, 2023, etc.).

The basis for long-term forecasting of characteristics related to maximum melt-rainfall runoff in lowland rivers is regional dependencies of modular coefficients of flow layers or maximum water discharge on cumulative water reserves in the snow cover and spring precipitation. These characteristics are expressed relative to their average values over a long period. The preliminary assessment of the water content of maximum melt-rainfall runoff is carried out using the discriminant analysis method by combining hydrometeorological factors. The values of flow layers or maximum water discharge are forecasted based on regional dependencies while determining the average long-term values of flow layers or maximum water discharge (modules).

For the automation of the forecasting process, a computer system named "Pripyat" is proposed, which allows for a preliminary prognostic evaluation of flood hazards. For this purpose, a cartographic representation of characteristics related to maximum melt-rainfall runoff in the form of modular coefficients of flow layers or maximum water discharge is utilized. Alongside the maps of predicted values of modular coefficients, a schematic map depicting the probability of exceeding forecasted values over a multi-year period (in percentages) is provided for any part of the territory, regardless of the degree of its hydrometeorological study.

Conclusions: The proposed methodology can be effectively used to prevent negative consequences associated with the formation of maximum melt-rainfall runoff in the rivers of the Ukrainian Polissya region. The prognostic cartographic monitoring of maximum runoff values has confirmed its potential for successful management of hydrological risks and environmental threats, particularly during extraordinary situations.

Keywords: floods, melt-rainfall runoff, modeling, forecast.