Прогнозная модель воздействия трелевочной системы на лесной почвогрунт в сложных сезонно-климатических условиях

Abstract

In the Russian Federation logging operations are traditionally carried out in winter. This is due to the predominance of areas with swamped and water-logged (class III and IV) soils in the forest fund, where work of forestry equipment is difficult, and sometimes impossible in the warm season. The work of logging companies in the forests of the cryolithozone, characterized by a sharply continental climate, with severe frosts in winter, is hampered by the fact that forest machines are not recommended to operate at temperatures below –40 °C due to the high probability of breaking of metal structures and hydraulic system. At the same time, in the warm season, most of the cutting areas on cryosolic soils become difficult to pass for heavy forest machines. It turns out that the convenient period for logging in the forests of the cryolithozone is quite small. This results in the need of work in the so-called off-season period, when the air temperature becomes positive, and the thawing processes of the soil top layer begin. The same applies to the logging companies not operating in the conditions of cryosolic soils, for instance, in the Leningrad, Novgorod, Pskov, Vologda regions, etc. The observed climate warming has led to a significant reduction in the sustained period of winter logging. Frequent temperature transitions around 0 °C in winter, autumn and spring necessitate to work during the off-season too, while cutting areas thaw. In bad seasonal and climatic conditions, which primarily include off-season periods in general and permafrost in particular, it is very difficult to take into account in mathematical models features of soil freezing and thawing and their effect on the destruction nature. The article shows that the development of long-term predictive models of indicators of cyclic interaction between the skidding system and forest soil in adverse climatic conditions of off-season logging operations in order to improve their reliability requires rapid adjustment of the calculated parameters based on the actual experimental data at a given step of the cycles.