FRACTAL ANALYSIS OF AGRICULTURAL SOILS FOR ASSESSMENT OF THEIR AGROPHYSICAL DEGRADATION

Abstract

The paper substantiates the applicability of fractal analysis of particle-size distribution for the quantitative assessment of agrophysical degradation of agricultural soils under intensive land use. It is shown that the conventional approach, in which particlesize composition is treated mainly as a classification characteristic, is methodologically limited and does not provide sufficient information on the physical condition of soils or the risks of degradation processes. A combined cumulative and fractal analysis of soil particle-size distribution is proposed to quantify the structural organization of the soil mass. The study is based on granulometric data obtained by standard laboratory methods, followed by the construction of cumulative distribution curves and their analysis in logarithmic coordinates. Fractal parameters were determined from the slope of power-law relationships using linear regression, and the quality of approximation was evaluated to ensure the reliability of the obtained indicators. The results demonstrate that the shape of cumulative curves and the characteristics of log–log dependencies reflect the degree of ordering of the granulometric structure and allow the identification of agrophysical degradation features, including disturbances of the hierarchical organization of soil structural elements. Deviations from fractal behavior of the particle-size distribution are shown to be a quantitative indicator of degradation changes caused by mechanical loading, soil compaction, and destruction of the aggregate structure. The obtained findings confirm the feasibility of integrating granulometric studies with cumulative and fractal analysis for the scientific substantiation of adaptive soil tillage systems aimed at reducing agrophysical degradation and maintaining soil fertility. The proposed approach enables soil differentiation according to resistance to compaction and structural breakdown, as well as the identification of critical thresholds of anthropogenic pressure.