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Integrating multi-fractal theory and geo-statistics method to characterize the spatial variability of particle size distribution of minesoils

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Abstract Opencast coal mining activities trigger considerable alteration of soil structure, and characterizing the spatial variability of soil particle size distribution (PSD) quantitatively can contribute to understand mined soil properties… Click to show full abstract

Abstract Opencast coal mining activities trigger considerable alteration of soil structure, and characterizing the spatial variability of soil particle size distribution (PSD) quantitatively can contribute to understand mined soil properties and perform mined land rehabilitation. In this study, a novel method combining multi-fractal and geo-statistics was used to quantify the spatial variability of PSD in an inner dump after dumping and before reclamation in the Shanxi Pingshuo Antaibao opencast coal-mine of China. Soil samples were collected from the depths of 0–20 cm and 20–40 cm at 78 sampling sites in the study area over an area of 0.44 km2. Five multi-fractal parameters (i.e., D(0), D(1), D(1)/D(0), Δα, and Δf(α)) of PSD of minesoils were calculated, and geo-statistics was used to demonstrated the spatial variability of multi-fractal parameters of PSD of minesoils. An expression quantifying spatial variability degree of PSD of minesoils was proposed. This novel method exhibited more advantages in characterizing variability of PSD of minesoils compared to single multi-fractal or geo-statistics method, and it can quantify the variability of whole PSD characteristics in detail, including PSD range, PSD concentration degree, PSD dispersion degree, PSD non-uniformity and PSD symmetry degree. PSD of minesoils basically presented a moderate spatial variability according to the method combining multi-fractal and geo-statistics, and opencast mining activities didn't give rise to severe spatial variability. This study provided a valuable reference for characterizing the spatial variability of soil PSD.

Keywords: multi fractal; geo statistics; spatial variability; variability; psd

Journal Title: Geoderma
Year Published: 2018

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