Adaptation of gas-dynamic protective technologies to minimize aerotechnogenic pollution of agroecosystems

The study suggests a methodology for reducing the aerotechnogenic impact on agroecosystems and the risks of soil degradation through the adaptation of gas-dynamic protective technologies and a digital twin. It is based on a cyber-physical architecture that integrates data from IoT sensors, remote sensing and UAVs into a geospatial database for model calibration by machine learning.
A comprehensive simulation was carried out at a hypothetical landfill (5000 ha): CFD analysis of gas dynamic screens (wind protection strips), hydrological modeling in SWAT and flood assessment in HEC-RAS. The results are aggregated into an integrated agro risk index. CFD modeling revealed a nonlinear dependence of screen efficiency on porosity. Excessive density increases turbulence and reduces the protection zone, while moderate porosity (35–45%) ensures optimal balance. The three-row configuration (∼38.7%) demonstrates maximum efficiency. SWAT confirmed that switching to no-till with cover crops reduces runoff by 64%, soil washout by 88% and nutrient loss by 75–77%. HEC-RAS has shown a significant increase in the scale of flooding during extreme floods, and the need to optimize land use.
The integrated assessment proved that the combination of optimized screens with soil protection practices reduces the total risk by 62.8%, and expected crop losses by up to 71.2%, demonstrating a synergistic effect. The digital twin serves as a tool for design and adaptive management, transferring the principles of gas dynamic protection from the space industry to the context of precision agriculture.

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