Fractal dimension of soil aggregates as an index of soil erodibility

Ahmadi, Abbas; Neyshabouri, M R; Rouhipour, H; Asadi, Hossein

doi:10.1016/j.jhydrol.2011.01.045

Cited by 94 publications

(40 citation statements)

References 28 publications

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“…Therefore, according to equations (4), the probability density () h  can be transformed into a grain size (or pore size) probability density or (normalized) distribution, which would control in turn the transition between low and high frequencies in equation (1). Note that if the soil has a fractal nature for instance in terms of grain size distribution (e.g., Hyslip and Vallejo [1997]; Ahmadi et al [2011]), we can expect the complex conductivity to be characterized a very broad distribution of relaxation times so that the phase may appear rather flat at least over few decades in frequency [Vinegar and Waxman, 1984]. We will come back to this point below (in terms of what we call Drake's model) since it calls for simplification of the model.…”

Section: Complex Conductivity Modelmentioning

confidence: 99%

Complex conductivity of soils

Revil

Coperey

Shao

et al. 2017

Water Resources Research

138

191

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The complex conductivity of soils remains poorly known despite the growing importance of this method in hydrogeophysics. In order to fill this gap of knowledge, we investigate the complex conductivity of 71 soils samples (including four peat samples) and one clean sand in the frequency range 0.1 Hz to 45 kHz. The soil samples are saturated with six different NaCl brines with conductivities (0.031, 0.53, 1.15, 5.7, 14.7, and 22 S m−1, NaCl, 25°C) in order to determine their intrinsic formation factor and surface conductivity. This data set is used to test the predictions of the dynamic Stern polarization model of porous media in terms of relationship between the quadrature conductivity and the surface conductivity. We also investigate the relationship between the normalized chargeability (the difference of in‐phase conductivity between two frequencies) and the quadrature conductivity at the geometric mean frequency. This data set confirms the relationships between the surface conductivity, the quadrature conductivity, and the normalized chargeability. The normalized chargeability depends linearly on the cation exchange capacity and specific surface area while the chargeability shows no dependence on these parameters. These new data and the dynamic Stern layer polarization model are observed to be mutually consistent. Traditionally, in hydrogeophysics, surface conductivity is neglected in the analysis of resistivity data. The relationships we have developed can be used in field conditions to avoid neglecting surface conductivity in the interpretation of DC resistivity tomograms. We also investigate the effects of temperature and saturation and, here again, the dynamic Stern layer predictions and the experimental observations are mutually consistent.

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Section: Complex Conductivity Modelmentioning

confidence: 99%

Complex conductivity of soils

Revil

Coperey

Shao

et al. 2017

Water Resources Research

138

191

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show abstract

“…Moreover, aggregate state, aggregate degree, and dispersion rate determine the ability of soil to resist disturbance and serve as indicators of soil structure [24]. Fractal dimension is also a powerful tool used to characterize aggregate-sized distributions for monitoring soil structure [25][26][27]. Using the fractal method to estimate soil structure changes under practices in conventional tillage/no tillage rotation, Wang et al [28] found that MWD and GMD were increased while fractal dimension decreased.…”

mentioning

confidence: 99%

Soil Aggregate Stability and Associated Structure Affected by Long-Term Fertilization for a Loessial Soil on the Loess Plateau of China

Tuo¹,

Xu²,

Li³

et al. 2017

Pol. J. Environ. Stud.

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“…The value of k ranged from 1 to 6 to make sure that every subinterval contained at least one measured value (Peng et al , ). Thus, the multifractal parameters including capacity dimension ( D 0 ), information dimension ( D 1 ), correlation dimension ( D 2 ), and information dimension/capacity dimension ( D 1 / D 0 ) were calculated as in the following equations (Ahmadi et al, ):

D ((), q) \approx lim_{ε \to 0} \frac{1}{q - 1} \times \frac{log ([], \sum_{i = 1}^{n ((), ε)} u_{i} {(ε)}^{q})}{log ε} q \neq 1,

D_{1} \approx \frac{\sum_{i = 1}^{n ((), ε)} u_{i} ((), ε) log u_{i} ((), ε)}{log ε} q = 1 .

…”

Section: Methodsmentioning

confidence: 99%

Influence of natural regeneration on fractal features of residue microaggregates in bauxite residue disposal areas

Zhu

Cheng

et al. 2017

Land Degrad Dev

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Bauxite residue is often physically degraded, which limits vegetation establishment on the disposal areas. Microaggregate stability is an important physical property due to its significant effect on erosion and surface runoff; however, this is rarely reported for bauxite residue. Native plant encroachment on a bauxite residue disposal area in Central China has revealed that natural regeneration may ameliorate the residue and help to support plant growth. Residue samples from 5 different disposal ages were collected to determine microaggregate stability and to identify their fractal features. Following natural regeneration, the aggregate fraction 250-50 μm increased significantly from 27.4% to 40.3%, whilst the silt + clay size aggregate fraction decreased from 58.4% to 30.7%. With increasing disposal age, the residue clay dispersion ratio (CDR) ranged from 7.7% to 22.5%, whilst aggregated silt and clay ranged from 15.3% to 19.0%, Residues from mineral ore processing are disposed on land in large residue disposal areas, which may eventually create a series of ecological and environmental issues (Smart, Callery, & Courtney, 2016;Wu et al., 2016;Xue et al., 2017). In the aluminium industry, bauxite residue is an alkaline solid by-product generated when alumina is extracted from bauxite ore by the Bayer process (Goloran, Phillips, & Chen, 2016;Kong, Guo et al., 2017). The global inventory has reached 3.4 billion tons, with an annual increase of 120 million tons (Kong, Li et al., 2017;Xue, Kong, et al., 2016a). Large volumes of bauxite residue are deposited in bauxite residue disposal areas, which cause potential environmental risks, as these bare areas are sensitive to erosion by wind and water, and can be regarded as a potential source of contamination due to their high alkalinity and salinity (Gelencsér et al., 2011;Ruyters et al., 2011). In situ rehabilitation and revegetation may, however, stabilize the residue surface and minimize wind erosion (Courtney, Jordan, & Harrington, 2009;Kaur, Phillips, & Fey, 2016;Schmalenberger, O Sullivan, Gahan, Cotter, & Courtney, 2013). Its poor physical structure is nevertheless a major limitation to support plant growth (Liu, Naidu, & Ming, 2013;Zhu, Huang, Xue, William, Li, Zou, 2016a With the development of soil fractal theory, the limitation of single-fractal dimension has been stressed to describe soil particle size distribution. In order to obtain more detailed information of soil structure, multifractal theory was introduced to soil science (Li, Liu, & Jiang, 2016). Rodríguez-Lado and Lado (2016) found that particle size distribution behaved as multifractals, with scaling properties varying in different soil samples, whilst values of fractal dimension may be related to the degree of evolution of the soils. Peng et al. (2014) found that the single-fractal and multifractal parameters could describe soil particle size distribution and the influences of soil structure effectively. inductively coupled plasma atomic emission spectroscopy (Jones et al., 2011). Exchan...

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Fractal dimension of soil aggregates as an index of soil erodibility

Cited by 94 publications

References 28 publications

Complex conductivity of soils

Complex conductivity of soils

Soil Aggregate Stability and Associated Structure Affected by Long-Term Fertilization for a Loessial Soil on the Loess Plateau of China

Influence of natural regeneration on fractal features of residue microaggregates in bauxite residue disposal areas

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