Journal Article10.1111/ejss.13354
A universal grain‐size distribution of soil with scaling invariance
2
TL;DR: In this paper , the authors proposed a universal GSD function for a general form of P(D)~D−μexp(−D/Dc)n, which introduces a new exponent n for the grain size scale.
read more
Abstract: Soils are composed of wide‐ranged grains and grain size distribution (GSD) is the fundamental characteristic determining the physical and hydraulic properties. Previously we have proposed a GSD function for various soils. However, the remarkable discrepancy in the distribution occurs in some soils, which not only limits the applicability of the function but also raises doubt as to the possibility of a universal GSD function. In this study we modify the GSD function to a general form of P(D) ~ D−μexp(−D/Dc)n, which introduces a new exponent n for the grain size scale. It turns out that this modification has eliminated the discrepancies and universally applies to a great variety of soils from around the world (hence to be a universal GSD function, UGSD). The exponent n is proved to be a scaling factor of grain size in log‐scale and divides soils into three categories of n < 1 n > 1, and n = 1. Furthermore, soils of surface processes (e.g., erosion, tillage, desertification, landslides, avalanches, deposition, and sediment transportation) remain in the same category and preserve the UGSD function. Thus, the UGSD not only provides parameters μ and Dc as synthetic indices for soil properties (e.g., as indices for spatial heterogeneity or variables for pedotransfer functions), but also describes texture changes in dynamic processes. The UGSD function represents a ‘conservative law’ underlying soil genesis and processes, which fills the knowledge gaps related to the lack of universally applicable indices for soil properties, and thus has universal applications in soil classification, spatial variability, as well as dynamical processes.
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
A <scp>GSD</scp>‐driven approach to deriving stochastic soil strength parameters under hybrid machine learning models
Hu Jiang,Yong Li,Qiang Zou,Jun Zhang,Jiazhi Cui,Jie Cheng,Bin Zhou,Siyu Chen,Wentao Zhou,Hongkun Yao +9 more
TL;DR: A GSD-driven approach is proposed to derive stochastic soil strength parameters using hybrid machine learning models, accounting for soil spatial variability and grain-size distribution, improving predictive performance by 24.72-35.53% in a case study on vegetated slopes.
Livestock trampling routes regulate biocrust composition in drylands: Implications for geodiversity and functioning
Ilan Stavi,Arnon Karnieli,Eli Argaman,Yagil Osem,Eli Zaady +4 more
References
A closed-form equation for predicting the hydraulic conductivity of unsaturated soils
van Genuchten,M. Th. +1 more
TL;DR: Van Genuchten et al. as mentioned in this paper proposed a closed-form analytical expression for predicting the hydraulic conductivity of unsaturated soils based on the Mualem theory, which can be used to predict the unsaturated hydraulic flow and mass transport in unsaturated zone.
26.8K
Brazos River bar [Texas]; a study in the significance of grain size parameters
Robert L. Folk,William C. Ward +1 more
TL;DR: In this paper, a bar on the Brazos River near Calvert, Texas, has been analyzed in order to determine the geologic meaning of certain grain size parameters and to study the behavior of the size fractions with transport.
7.2K
Fractals and Chaos in Geology and Geophysics
Donald L. Turcotte
- 01 Jul 1997
TL;DR: In this article, the fundamental concepts of fractal geometry and chaotic dynamics are introduced and related to a variety of geological and geophysical problems, illustrating just what chaos theory and fractals really tell us and how they can be applied to the earth sciences.
1.8K
Formation of fractal clusters and networks by irreversible diffusion-limited aggregation
TL;DR: A model for diffusion-controlled aggregation in which growing clusters as well as individual particles are mobile has been investigated in this article, and two versions of the model in which the cluster diffusion coefficient is either size independent or inversely proportional to number of particles (mass) give very similar results.
1.6K