Nikita Romanovich Kryuchkov

Th e damage caused by soil and land degradation was assessed at three hierarchical levels (the region as a whole, the municipality, the agricultural sector) of the spatial organization of six test regions of the Russian Federation (Volgograd, Belgorod, Kaliningrad, Vladimir, Samara and Penza regions). Th e indicators of soil and land degradation for all test objects
were a decrease in the content of exchangeable potassium, a decrease in the content of mobile phosphorus, a decrease
in the content of humus, a change in the acidity index of soils. In addition, for the test objects of the Volgograd region, the indicator of land salinization was used, the Belgorod region — soil erosion, the Kaliningrad region — the indicator of the metabolic coeffi cient (qCO2) of soils. It was found that the minimum and maximum values of the specific total damage fr om degradation can be detected for regions with a similar composition of soil cover (Saratov and Belgorod regions, respectively, wh ere chernozem soils predominate). When the values of specifi c total damage from soil and land degradation are close to each other at various hierarchical levels of spatial organization of regions (Vladimir, Saratov, Belgorod and partly Penza regions), in terms of intensity and scale of manifestation of the studied degradation processes, the agricultural farm is «typical» for the entire municipal district, and the municipal district is «typical» for the entire region.

Water erosion is one of the most extensive processes of soil and land degradation. This process significantly deteri- orates the quality of ecosystem services provided. Studying the mechanism and consequences of this phenomenon will help develop strategies to mitigate its impact on the environment. One of the challenges in studying water erosion is the high cost of conducting field research over large areas. Another challenge is the limitation of existing models, which are often developed for specific regions. Our research aims to address these problems by adapting the widely used RUSLE2 model to local conditions. Beijing was chosen as the study area due to its rich information resources and extensive results from field measurements of soil water erosion. Calculations were performed using a raster data model, which included a slope angle model, slope length, soil erodibility, rainfall erosion potential factors from precipitation and snowmelt, land use types, and vegetation cover management factors. All data were taken from open sources. The average soil erosion in the studied area was 25 t·ha–¹ per year. The discrepancy with other studies was less than 1%. The modified RUSLE2 model showed good results, correlating with other studies in this area.