BRIDGING THE GAP BETWEEN KACHINSKY AND FAO/USDA PARTICLE-SIZE DISTRIBUTION SYSTEMS: MATHEMATICAL MODELING AND PEDOGENETIC HARMONIZATION
DOI:
https://doi.org/10.31861/biosystems2025.03.436Keywords:
Soil texture, Particle-size distribution (PSD), Kachinsky system, FAO/WRB standards, LLSI algorithm, Fractal scaling, Retisols, Lithogenic heterogeneityAbstract
This study addresses the methodological challenges of converting soil particle-size distribution (PSD) data from the regional Kachinsky system to international FAO/USDA standards, focusing on the diagnostic of lithogenic heterogeneity in Retisols.
We compared various parametric models (Fredlund 4P, van Genuchten, Skaggs) and non-parametric spline functions. A specific Log-Linear Sectional Interpolation (LLSI) algorithm was developed to estimate the 2 µm clay threshold. To bridge the 1–2 mm data gap inherent in the Kachinsky method, a fractal power-law scaling approach was applied for sand fraction extrapolation.
Traditional fixed-ratio conversions (e.g., physical clay/2) proved inaccurate, yielding classification errors of 30–50%. The proposed LLSI algorithm, combined with fractal scaling and pedogenetic corrections for organic matter and carbonates, achieved high predictive accuracy (R2 > 0.95). Furthermore, we quantified the systematic bias of laser diffraction (LD), which underestimates clay content by 8–15% compared to sedimentation methods due to particle non-sphericity.
Effective harmonization requires continuous modeling of the PSD curve rather than simple arithmetic coefficients. The integration of the LLSI method and fractal extrapolation provides a robust framework for incorporating regional soil archives into global databases, ensuring the accurate representation of complex soil textures like those of the Precarpathian Retisols.
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