Methodological approaches to modeling the K factor of the RUSLE soil losses model from erosion

Abstract

The article discusses methodological approaches to modeling the soil erosion factor K, which is part of the RUSLE model, taking into account the spatial variability of its main subfactors – particle size distribution and macrostructural composition, soil organic carbon content and soil permeability. The aim of this study is to establish spatial patterns of particle size distribution and organic carbon content within slope landscapes and to substantiate approaches to their mathematical description. The study was conducted using field and laboratory data, geoinformation analysis, correlation, and regression methods. Statistically significant relationships were established between the topographic factor LS and key subfactors of the K factor. In particular, inverse relationships were identified between relief intensity and indicators characterizing soil mass accumulation. These relationships were shown to be predominantly nonlinear, leading to the limitations of linear models and the advisability of using power functions, which provide higher approximation accuracy (R² > 0.7). Further verification of the results was performed using the soil magnetic susceptibility index as an integrated indicator of its properties. The results confirm the threshold (intermittent) nature of accumulation processes within sloping lands and demonstrate the feasibility of effectively predicting the spatial distribution of the K factor based on topographic and soil parameters. The proposed approach can be used to improve the accuracy of erosion risk assessments and to justify soil conservation land management measures