Applications of Fractals to Soil Studies

Anderson, Alison N.; McBratney, Alex B.; Crawford, John W.

doi:10.1016/s0065-2113(08)60241-2

Cited by 68 publications

(49 citation statements)

References 120 publications

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“…This distribution can be seen as the result of a fragmentation process, this is, an iterative processs acting within a range of scales. Experimental data on this distribution showed power scaling of the type reflected in Section 1 (ANDERSON et al, 1998). This fact suggests that the distribution should have scale-invariant behavior: If we zoom into the mass interval to see it at a finer scale, it should resemble (statistically) the structure of the whole interval: A photograph of soil looks similar at every scale; it is impossible to guess the size of elements in the picture.…”

Section: The Logselfsimilar Modelmentioning

confidence: 93%

Testing Logselfsimilarity of Soil Particle Size Distribution: Simulation with Minimum Inputs

García-Gutiérrez

Martı́n

2008

Pure appl. geophys.

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Abstract-Particle size distribution (PSD) greatly influences other soil physical properties. A detailed textural analysis is time-consuming and expensive. Soil texture is commonly reported in terms of mass percentages of a small number of size fractions (typically, clay, silt and sand). A method to simulate the PSD from such a poor description or even from the poorest description, consisting in the mass percentages of only two soil size fractions, would be extremly useful for prediction purposes. The goal of this paper is to simulate soil PSDs from the minimum number of inputs, i.e., two and three textural fraction contents, by using a logselfsimilar model and an iterated function system constructed with these data. High quality data on 171 soils are used. Additionally, the characterization of soil texture by entropy-based parameters provided by the model is tested. Results indicate that the logselfsimilar model may be a useful tool to simulate PSD for the construction of pedotransfer functions related to other soil properties when textural information is limited to moderate textural data.

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Section: The Logselfsimilar Modelmentioning

confidence: 93%

Testing Logselfsimilarity of Soil Particle Size Distribution: Simulation with Minimum Inputs

García-Gutiérrez

Martı́n

2008

Pure appl. geophys.

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“…Матеріально-енергетичний метаболізм наземних біогеоценозів у чималому ступені залежить від фізичного стану косної частини ґрунту (Karpachevsky, 2005). Ґрунт є найбільш консервативним компонентом біогеоценозу (Anderson et al, 1998). Його буферні властивості сприяють збереженню даного типу біогеоценозу, регуляції теплового і водного режимів у біогеоценозах, нейтралізації токсичних речовин, що утворюються в біогеоценозах під час його життя (Heuvelink, Webster, 2001;Rode, 1984).…”

Section: вступunclassified

Управління Функціональними Властивостями Моделей Техноземів За Допомогою Первинної Стратиграфії Насипок

Maslikova

2018

Ukr J Ecol

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The article examines the hypothesis that the structure of the soil-like body in zero-point of its existence directs the dynamics and trajectory of soil formation. To test the hypothesis at the Dnepropetrovsk State Agricultural and Environmental University science satiation the field experiment was laid out lizymetres, each contain a constructive combination of rock or chornozemlike mass. It is shown that the design of the soil-like body in zero-point of its existence controls the dynamics and trajectory of soil formation. Philip equation was modified to more suitable simulate the infiltration process in tehnozems which allows to accurately describe the water absorption process at the infiltration and filtration stages. The nature of the underlying rocks located at a certain depth impacts significantly on the process of soil formation within the whole soil profile. Underlying rock layer regulates the processes of the tehnozems contact with the environment, as well as determining the intensity profile migration of moisture and dissolved salts. The presence of water resistant biogenic origin aggregates smoothes the varying density clay soils resulting from swelling and shrinkage processes that can maintain stable structure of the pore space. As a result, the soil after reclamation phase gets such features as reduced infiltration rate, but increased level of filtration. Optimal values of sorptivity and filtering corresponds closely with relevant properties of soil that can be investigated using indicators of the soil mechanical impedance. Uniformity preparation and impermeable aggregate structure determines the optimal functional modes of the tehnozemes. Key words: reclamation; infiltration; technozems models; soil forming; Philippe equitation; sorptivity Управління функціональними властивостями моделей техноземів за допомогою первинної стратиграфії насипок К.П. МасліковаДніпровський державний аграрно-економічний університет Вул. С. Єфремова 25, м. Дніпро 49600, Україна, e-mail: mkaterina@ukr.net У статті розглянуто гіпотезу, що конструкція ґрунтоподібного тіла у нуль-момент свого існування визначає динаміку та траєкторію ґрунтотворного процесу. Для перевірки гіпотези на стаціонарі Дніпропетровського державного аграрно-екологічного університету у 90-ті роки минулого віку закладений польовий експеримент з лізиметрами, кожний з яких уміщує певну конструктивну комбінацію гірських порід або чорноземоподібної маси. Показано, що конструкція ґрунтоподібного тіла у нуль-момент свого існування визначає динаміку та траєкторію ґрунтотворного процесу. Для моделювання процесу водовбирання техноземів більш придатним є модифіковане рівняння Філіпа, яке дозволяє точно описати процес вбирання води як на етапі інфільтрації, так і на етапі фільтрації. Характер підстилаючої породи техноземів, яка знаходиться на певній глибині, значно впливає на перебіг процесів ґрунтоутворення у межах усього ґрунтового профілю. Підстилаюча порода регулює процеси контакту техноземів з навколишнім середовищем, так як визначає інтенсивність профільної міг...

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“…Soil and organic matter are fractal objects [10] [11] that interact with each other [12]. Organic matter is a mixture of objects of various sizes and biochemical compositions [6] [13].…”

Section: Introductionmentioning

confidence: 99%

“…A hierarchical soil aggregation model for physical protection of organic matter against microbial attacks in a fractal soil system has been conceptualized by [18], described numerically by fractal [10] and Euclidean [19] geometry, and illustrated by [20]. Plant residues and fungi decompose into fragments and various substances, providing a nucleus for the formation of micro-aggregates less than 250 µm in diameter within macro-aggregates [21].…”

Section: Introductionmentioning

confidence: 99%

Fractal Kinetics Parameters Regulating Carbon Decomposition Rate under Contrasting Soil Management Systems

Parent¹

2017

OJSS

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Agricultural soils can sequester and release large amounts of carbon. Accessibility of soil carbon to microbial attacks depends on biological, chemical, and physical protection mechanisms such as organic matter composition and particle size, soil aggregation, and chemical protection through the silt-clayorganic matter complex. While soil and organic matter are fractal objects controlling exposure of reactive surfaces to the environment, soil aggregation and biomass production and quality are regulated by agricultural practices. Organic matter decomposition in soil is generally described by the classical first-order kinetics equations fitted to define distinct carbon pools. By comparison, fractal kinetics assigns a coefficient to adjust time-dependent decomposition rate of total soil carbon to protection mechanisms. Our objective was to relate fractal parameters of organic matter decomposition to soil management systems. Retrieving published data, the decomposition of organic matter was modeled in a silt loam soil maintained under pasture, annual cropping or bare fallow during 11 years. The classical first-order kinetics model returned quadratic relationships indicating that reactive carbon decreased with time. Fractal kinetics rectified the relationships successfully.Initial decomposition rate (k 1 at t = 1) was 7 × 10 −4 for pasture, 1 × 10 −4 for annual cropping, and 0.5 × 10 −4 for bare-soil fallow. Fractal coefficients h were 0.71, 0.45, and 0.25 for pasture, annual cropping and fallow, respectively. Due to aggregation, physical protection against microbial attacks was highest under pasture management, leading to higher carbon sequestration despite higher biomass production and "priming" effects. Parameters k 1 and h proved to be useful indicators for soil quality classification integrating the opposite effects of labile carbon decomposition and carbon protection mechanisms that regulate the decomposition rate of organic matter with time as driven by soil management practices.

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Applications of Fractals to Soil Studies

Cited by 68 publications

References 120 publications

Testing Logselfsimilarity of Soil Particle Size Distribution: Simulation with Minimum Inputs

Testing Logselfsimilarity of Soil Particle Size Distribution: Simulation with Minimum Inputs

Управління Функціональними Властивостями Моделей Техноземів За Допомогою Первинної Стратиграфії Насипок

Fractal Kinetics Parameters Regulating Carbon Decomposition Rate under Contrasting Soil Management Systems

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