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Soil is a natural environment for food production that can suffer from pathogenic microorganisms due to their fast growth in degraded agricultural soils in contrast to normal soils. Soil degradation is reflected in its poor microbiological diversity which slows down fresh plant residues and fresh organic matter turnover. It leads to disruption of soil aggregates structure (compaction) and thus unoptimal air and water regimes. In this work we model soil aggregation processes in continuous feedback with organic matter cycle driven by microorganisms. We aim to model soil physical structure differentiation with its depth on a macroscale (and other physical and chemical properties distributions) as a result of aggregate size distribution-dependent nutrients transport (such as oxygen, water, mineral and organic substrates) which influences microscopic biological processes in soil profile. On the other hand, biological processes change porous structure, carbon content and etc. within the whole profileand seriously affect diffusion coefficients creating extremely complex and interesting feedback between macro- and micro-scale. Local part of mathematical model is formulated as a system of nonlinear ordinary differential equations, including chemical master equations for biological processes and coagulation/adsorption/adhesion kinetics and Smoluchowski type aggregation-fragmentation equations. The full self-consistent model describes possible mechanisms of feedback between the soil physical structure and rates of microbiological cycle and soil organic matter decay and aims to predict evolution of soil properties in conditions of external climate and anthropogenic stress. This work was done with partial financial support by RFBR (16-04-01624).