Abstract
The purpose. To carry out an analysis of climatic changes in the central part of the Forest-Steppe, to justify the feasibility of restoring irrigated drainage systems. Methods. Assessment of changes in the agrometeorological resources of the territory was carried out by the method of mathematical-statistical analysis of complex indicators of heat and moisture conditions: climate water balance and hydrothermal coefficient. The stationary experiment data were processed by the methods of system generalization, correlation, economic, calculation, and comparative analyses. Results. The climate of the region is determined by a sufficient level of heat resources and unsustainable moisture. Due to a steady increase in the temperature regime, the supply of active air temperatures increased from 2880 °C to 3300-3500 °C, the total annual deficit of the water balance increased to 150 mm. As a result, in 32% of cases, that is, 3 years out of 10, in the region strong and moderate arid conditions of the growing season are observed. Fluctuations in meteorological conditions over the years directly influence the yield of field crops, in particular, winter wheat and sugar beet. Years with high crop yields are characterized by close to optimal levels of natural moisture supply. It has been established that the coefficient of variation of winter wheat yield over the years depending on the predecessor and the background of fertilizer can reach 39, sugar beet — 41%. Conclusions. In the forest-steppe zone, the maximum realization of the potential of the existing agrometeorological (heat, light) and chemical-technogenic resources is possible only if the water regime is regulated with the obligatory consideration of other factors determining a high level of effective soil fertility. So, the natural background of the typical deep low-humus chernozem in the Right-Bank Forest-Steppe provides the yield of winter wheat at the level of 4 t/ha. With the improvement of nutrition and moisture conditions, the maximum crop yield increases 1.7 times, and with the optimization of all factors, it can be increased 2.5 times.
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