Abstract
The article is related to the study of the localization of agronomic heterogeneities of the soil distributed on slopes. To study this important agricultural areas, we usedthe mathematical modeling of erosion processes and the survey of the magnetic susceptibility of the arable horizon of the soils. The experiment design includes the typical chernozemof the slope.The soil sampling was performed according to DSTU 4287:2004, determination of organic carbon content according to DSTU 4289:2004, and determination of statistical indicators using Statistica®. The visualization of the study results was carried out in the QGis software. Magnetic susceptibility (MS) was measured using a KLY-2 magnetometer. Modeling of soil erosion processes involved USLE universal soil loss equation. A 1:10,000 topographic map was adopted as the topographic basis. The research territory is the fields of the National Biotechnological University (V.V. Dokuchaev KhNAU) on the southern outskirts of the city of Kharkiv. The 70 soil samples were collected from the arable layer (horizon A). Due to the course of water erosion processes, a long-term soil washout and a widespread complex spatial complex of washed-out soils took place on the site, which is a typical case for eroded sloping lands of the Forest Steppe. In non-eroded watersheds (in the north-western direction), typical heavy loamy medium-humus chernozems are developed. Sampling was carried out using an irregular grid, the sampling density was about 5 samples per hectare.We detected that mathematical modeling of erosion processes can be used to predict the location of inhomogeneities in the agronomic properties of the ground cover of sloping lands. However, given the shortcomings of the main models of potential soil losses associated with the alternation of zones of erosion and deposition require to clarify and verify the obtained results. Hence, we propose to apply the statistical characteristics of the spatial distribution of values of the magnetic susceptibility of the soil. The most important parameters are the average values and coefficient of variation of MS.
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