The problem of salinization/spreading of saline soils is becoming more urgent in many regions of the world, especially in context of climate change. The monitoring of salt-affected soils’ properties is a necessary procedure in land management and irrigation planning and is aimed to obtain high crop harvest and reduce degradation processes. In this work, a machine learning method was applied for modeling of the spatial distribution of topsoil (0–20 cm) properties—in particular: soil organic carbon (SOC), pH, and salt content (dry residue). A random forest (RF) machine learning approach was used in combination with environmental variables to predict soil properties in a semi-arid area (Trans-Ural steppe zone). Soil, salinity, and texture maps; topography attributes; and remote sensing data (RSD) were used as predictors. The coefficient of determination (R²) and the root mean square error (RMSE) were used to estimate the performance of the RF model. The cross-validation result showed that the RF model achieved an R² of 0.59 and an RMSE of 0.68 for SOM; 0.36 and 0.65, respectively, for soil pH; and 0.78 and 1.21, respectively for dry residue prediction. The SOC content ranged from 0.8 to 2.8%, with an average value of 1.9%; soil pH ranged from 5.9 to 8.4, with an average of 7.2; dry residue varied greatly from 0.04 to 16.8%, with an average value of 1.3%. A variable importance analysis indicated that remote sensing variables (salinity indices and NDVI) were dominant in the spatial prediction of soil parameters. The importance of RSD for evaluating saline soils and their properties is explained by their absorption characteristics/reflectivity in the visible and near-infrared spectra. Solonchak soils are distinguished by a salt crust on the land surface and, as a result, reduced SOC contents and vegetation biomass. However, the change in saline and non-saline soils over a short distance with mosaic structure of soil cover requires high-resolution RSD or aerial images obtained from unmanned aerial vehicle/drones for successful digital mapping of soil parameters. The presented results provide an effective method to estimate soil properties in saline landscapes for further land management/reclamation planning of degraded soils in arid and semi-arid regions.

It has been revealed that, in the years when the freezing depth of leached chernozems on slopes in the southern Cis-Ural region is in the range of 30–38 cm, no surface runoff is observed in the spring regardless of the snow cover, soil wetting, or vegetation; the critical freezing depth under forest is half that on the open surfaces. When the freezing depth is deeper, the critical volume of the spring runoff is mainly determined by the meteorological conditions, the water permeability of the soil, and its protection by plants.

The effect of rainfall intensity on the erosion of residual calcareous agrogray soils and clay-illuvial agrochernozems in the Southern Cis-Ural region on slopes of different inclination and vegetation type has been studied by simulating with a small-size sprinkler. It has been shown that soil loss linearly depends on rainfall intensity (2, 4, and 6 mm/min) and slope inclination (3° and 7°). When the rainfall intensity and duration, and the slope inclination increase, soil loss by erosion from agrogray soils increases higher than from agrochernozems. On the plowland with a slope of 3°, runoff begins 12, 10, and 5 min, on the average, after the beginning of rains at these intensities. When the slope increases to 7°, runoff begins earlier by 7, 6, and 4 min, respectively. After the beginning of runoff and with its increase by 1 mm, the soil loss from slopes of 3° and 7° reaches 4.2 and 25.7 t/ha on agrogray soils and 1.4 and 4.7 t/ha on agrochernozems, respectively. Fallow soils have higher erosion resistance, and the soil loss little depends on the slope gradient: it gradually increases to 0.3–1.0 t/ha per 1 mm of runoff with increasing rainfall intensity and duration. The content of physical clay in eroded material is higher than in the original soils. Fine fractions prevail in this material, which increases their humus content. The increase in rainfall intensity and duration to 4 and 6 mm/min results in the entrapment of coarse silt and sand by runoff.

Temporal changes of eroded soils in the southern Cis-Ural region (Republic of Bashkortostan) depending on their agricultural use during the period from 1975 to 2011 were studied. In the northern foreststeppe zone, the development of erosion processes was retarded upon the use of soil-saving management practices and grain-fallow-grass crop rotations. In slightly eroded light gray forest soils (Eutric Retisols (Cutanic)), the thickness of humus-accumulative horizons and the content of humus increased; the conversion of cropland into permanent fallow was found to be the most efficient measure to control soil erosion. In podzolized chernozems (Luvic Greyzemic Chernic Phaeozems) and typical chernozems (Haplic Chernozems) of the Cis-Ural steppe, the content of humus in the plow layer under grain-row crop rotation and classical soil management decreased, especially in moderately eroded soils. The development of water and wind erosion on slopes depended on the slope shape: the texture of soils at different degrees of erosion on slopes with free runoff became coarser by one gradation after 35 years; in the presence of linear obstacles in the lower part of slopes, the content of fine fractions in moderately and strongly eroded soils increased.

The influence of ground fires of different ages on the morphological, hydrophysical, and physicochemical properties and on the humus status of dark gray soils (Luvic Retic Greyzemic Someric...