Цифровое картографирование эрозионных структур почвенного покрова на основе имитационной модели смыва (северная лесостепь Среднерусской возвышенности)

The spatial structure of the habitat for plant communities based on soil functions in virgin forest-steppe of the Central Russian Upland is the focus of this study. The objectives include the identification of the leading factors of soil function variety and to determine the spatial heterogeneity of the soil function. A detailed topographic survey was carried out on a key site (35 hectares), 157 soil, and 34 geobotanical descriptions were made. The main factor of soil and plant cover differentiation is the redistribution of soil moisture along the microrelief. Redistributed runoff value was modelled in SIMWE and used as a tool for spatial prediction of soils due to their role in a habitat for plant communities’ functional context. The main methods of the study are the multidimensional scaling and discriminant analysis. We model the composition of plant communities (accuracy is 95%) and Reference Soil Group (accuracy is 88%) due to different soil moisture conditions. There are two stable soil habitat types: mesophytic communities on the Phaeozems (with additional water runoff more than 80 mm) and xerophytic communities on Chernozems (additional runoff less than 55 mm). A transitional type corresponded to xero- mesophytic communities on the Phaeozems with 55–80 mm additional redistributed runoff value. With acceptable accuracy, the habitat for natural plant communities based on soil function model predicts the position of contrastingly different components of biota in relation to their soil moisture requirements within the virgin forest-steppe of the Central Russian Upland.

Soil degradation resulting from water erosion poses a serious threat to food and environmental security, therefore the research of soil erosion features and soil erosion mapping do not lose their relevance. The paper presents the results of large-scale digital mapping of the erosion degree of the arable soils in the Prokhorovsky district of the Belgorod region (85 thousand hectares), based on two approaches: (1) linking the factors of erosion-accumulative processes and the erosion degree of soil directly (factor -property model), and (2) due to imitation erosion model WaTEM/SEDEM (factor - process - property model). The inclusion of the process component into the digital soil mapping algorithm allows taking into account not only the spatial but also the temporal soil erosion features. It was revealed that the agricultural development of the Prokhorovsky district was primarily carried out on lands that are weakly prone to erosion, with the rate of erosion almost two times lower than on younger arable lands. As a result, the soil erosion maps, based on the factor - process - property model, with and without taking into account the duration of agricultural use, largely correspond to each other. Dominant soil categories (the map pixel corresponds to one soil taxa - noneroded and slightly eroded, medium, highly eroded), mapping by factor -property and factor - process - property models, have a high degree of correspondence to each other (prediction identity for 90% of pixels), while the soil combinations (the map pixel has information on the proportion of soils with different erosion degrees of soil) more significant (identity for less than 60% of pixels). The areas of zonal, erosion-zonal, and weakly eroded soil combinations differ 1.5-2 times, in the direction of a greater degree of soil erosion on the factor - process - property map.

In semi-arid ecoregions of temperate zones, focused snowmelt water infiltration in topographic depressions is a key, but imperfectly understood, groundwater recharge mechanism. Routine monitoring is precluded by the abundance of depressions. We have used remote-sensing data to construct mass balances and estimate volumes of temporary ponds in the Tambov area of Russia. First, small water bodies were automatically recognized in each of a time series of high-resolution Planet Labs images taken in April and May 2021 by object-oriented supervised classification. A training set of water pixels defined in one of the latest images using a small unmanned aerial vehicle enabled high-confidence predictions of water pixels in the earlier images (Cohen’s Κ = 0.99). A digital elevation model was used to estimate the ponds’ water volumes, which decreased with time following a negative exponential equation. The power of the exponent did not systematically depend on the pond size. With adjustment for estimates of daily Penman evaporation, function-based interpolation of the water bodies’ areas and volumes allowed calculation of daily infiltration into the depression beds. The infiltration was maximal (5–40 mm/day) at onset of spring and decreased with time during the study period. Use of the spatially variable infiltration rates improved steady-state shallow groundwater simulations.

The results of experimental studies of the postagrogenic transformation of loamy soddy-podzolic soils on the southern slope of the Klin-Dmitrov Moraine Ridge are discussed. A chronosequence of soils (arable soils (cropland)-soils under fallow with meadow vegetation-soils under secondary forests of different ages-soils under a conventionally initial native forest) was examined, and the stages of the postagrogenic transformation of the automorphic soddy-podzolic soils were identified. The differentiation of the former plow horizon into the A1 and A1A2 horizons (according to the differences in the humus content, texture, and acidity) served as the major criterion of the soil transformation. A stage of textural differentiation with clay depletion from the uppermost layer was identified in the soils of the 20- to 60-year-old fallows. The specificity of the postagrogenic transformation of the soils on the slopes was demonstrated. From the methodological point of view, it was important to differentiate between the chronosequences of automorphic and semihydromorphic soils of the leveled interfluves and the soils of the slopes. For this purpose, a series of maps reflecting the history of the land use and the soil cover pattern was analyzed. The cartographic model included the attribute data of the soil surveys, the cartographic sources (a series of historical maps of the land use, topographic maps, remote sensing data, and a digital elevation model), and two base maps: (a) the integral map of the land use and (b) the map of the soil combinations with the separation of the zonal automorphic, semihydromorphic, and erosional soil combinations. This scheme served as a matrix for the organization and analysis of the already available and new materials.