Improving estimation of pore size distribution to predict the soil water retention curve from its particle size distribution

Chang, Chih Horng; Cheng, Donghui; Xiao-ying, Qiao

doi:10.1016/j.geoderma.2019.01.011

Cited by 27 publications

(22 citation statements)

References 25 publications

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“…There are numerous approaches in the literature to model soil water retention behavior. A common approach is the conversion of a grain size distribution (GSD) to a pore size distribution (PSD), with each pore in the PSD associated with a volume of water it contains and a suction at which it will drain [11][12][13][14][15][16][17]. This information allows a water retention curve to be built.…”

Section: Key Phenomena For Water Retention Curve Modelsmentioning

confidence: 99%

“…The determination of the PSD from a GSD is arguably the most important aspect of the GSD-WRC approach, as it has the greatest impact on the prediction. Particle packing and determination of the resulting PSD is a complicated non-linear problem, thus it is common to simplify the particle packing for soils by assuming particles within a certain size range pack discretely and have pores of a similar size range [11][12][13][14][15][16]20,21], with a two-dimensional framework typically adopted. An example of this assumption in a two-dimensional basis is mathematically described in Equation (1):…”

Section: Pore Dimension and Pore Fillingmentioning

confidence: 99%

“…The contact angle of a mineral soil grain is an important factor affecting the predicted suctions of GSD-WRC models, as it determines the drainage suction of a pore from the capillarity law. However, because most soil minerals are hydrophilic with relatively low contact angle values (for example, as low as 17 • for quartz [35,36]), many GSD-WRC models assume a contact angle of zero and achieve good predictions for many soils [11][12][13][14][15][16][17]. In contrast, the materials of interest in this study include coal tailings that have significant coal content, and coal is known to be hydrophobic [37][38][39][40][41][42], which means that a contact angle of 0 • cannot be used nor justified.…”

Section: Contact Angle Between Water and Soil Surfacementioning

confidence: 99%

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A Simple Water Retention Model Based on Grain Size Distribution

2021

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The Hunter valley region in NSW Australia is an area with a heavy coal mining presence. As some mines come to their end of life, options are being investigated to improve the topsoil on post mining land for greater plant growth, which may allow economically beneficial farmland to be created. This research is part of an investigation into mixing a mine waste material, coal tailings, with topsoil in order to produce an improved soil for plant growth. Implementing such a solution requires estimation of the drying path of the water retention curves for the tailings and topsoil used. Instead of a lengthy laboratory measurement, a prediction of the drying curve is convenient in this context. No existing prediction models were found that were suitable for these mine materials, hence this paper proposes a simple and efficient model that can more accurately predict drying curves for these mine materials. The drying curves of two topsoils and two tailings from Australian coal mines were measured and compared with predictions using the proposed model, which performs favorably compared to several existing models in the literature. Additionally, the proposed model is assessed using data from a variety of fine- and coarse-grained materials in the literature. It is shown that the proposed model is overall more accurate than every other model assessed, indicating the model may be useful for various materials other than those considered in this study.

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Section: Key Phenomena For Water Retention Curve Modelsmentioning

confidence: 99%

Section: Pore Dimension and Pore Fillingmentioning

confidence: 99%

Section: Contact Angle Between Water and Soil Surfacementioning

confidence: 99%

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A Simple Water Retention Model Based on Grain Size Distribution

2021

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“…Stabilization can be best characterized by mixing concerning atterberg limits and particle size distribution curve. Different trials and classi􀅫ication indicate the best-expected derivation for the suitability of the soil to enhance its shear strength and load-bearing capacity as desired requirement [9,10].…”

Section: Introductionmentioning

confidence: 99%

Utilizing Alumina-Silica Enriched Bricks Debris Determining End Product of ML-CL Fill Soil: Advanced Stabilization Practices with Innovating Discarded Material

Afzaal¹,

Shah²,

Sheraz³

et al. 2021

J. ICT des. eng. technol. sci.

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Testing soil and knowing its strength parameters is one of the basic components in construction. Testing of 􀅮ill soil is carried out to 􀅮ind whether the existing soil can endure the burden of structure withheld upon it or not. In the case of weak soil, one can 􀅮ind it dif􀅮icult to pursue construction or any development project. While talking of solutions, there are many methods to improve its strength and properties: one of them which we decided to work on is 'stabilization of 􀅮ill soil using bricks waste which is normally easily available material. The main objective of our test is to check the effectiveness of bricks waste on the mechanical properties of 􀅮illing material. The testing comprised of performing Atterberg limits, Uncon􀅮ined Compression, Direct Shear, Sieve Analysis, Moisture Dry Density, and Permeability. The Bricks waste passing no. 40 sieve is mixed with 􀅮ill soil and testing on different proportions i.e. 0, 5, 10, 15 and 20 percent was carried out. The summary was prepared showed improvement in soil regarding the shear strength and toughness as the Plasticity Index of the soil was improved. The uncon􀅮ined compression test results show a pattern in which the peak stress is increased as we move to higher percentages. Also, the moisture content is increased for this test because the brick debris absorbed water. Direct shear test on percentages up to 15% showed that the peak shear stress increased, which indicates that on higher percentages the sample took more load as compared to small percentages. Moisture Dry Density relationship provides a clear indication of an increase in density of soil as moved to higher percentages and decrease in Optimum Moisture Content which suggests that, clay absorbs more water content as compared to brick debris.

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“…Soil PSD is often used to estimate the water retention curve (Chang, Cheng, & Qiao, 2019; Costabel & Yaramanci, 2013; Fredlund & Xing, 1994) and soil freezing characteristic curve (Watanabe & Mizoguchi, 2002). Both curves are essential to investigate the movement of water and salt in soil pores in agriculture, forestry, and geotechnical engineering (Bayer, Jaeger, & Schaumann, 2010; Jaeger, Bowe, Vanas, & Schaumann, 2009; Wang, Lai, & Zhang, 2017).…”

Section: Introductionmentioning

confidence: 99%

Characterizing the pore size distribution of a chloride silt soil during freeze–thaw processes via nuclear magnetic resonance relaxometry

Liu

Yang

et al. 2020

Soil Science Soc of Amer J

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Soil pore size distribution (PSD) is typically used to predict the soil freezing characteristic curve and estimate the hydrological and mechanical properties during freeze-thaw cycles. However, direct measurements of frozen soil PSD remain a great challenge. This study proposed a method to determine the PSD of frozen soils based on nuclear magnetic resonance (NMR) relaxometry. Tests were performed on a saturated chloride silt soil at different salt contents (0.3, 1.0, 2.0, and 3.0%) and temperatures (between-30 and 0 • C) during a freeze-thaw cycle. The NMR-detected PSD (only accounting for pores occupied by unfrozen water) varied with soil temperature, salt content, and freeze-thaw cycle. The sequence of the water-ice phase change and hysteresis were also identified in a freeze-thaw cycle. A regression analysis was performed on the cumulative NMR-detected PSD via a variant van Genuchten model. The critical freezing pore radius and the thickness of unfrozen water film were computed and used to transform NMRdetected PSD into the actual PSD of frozen soils on the basis of a pore radius transformation equation established in this paper. Notably, the actual PSD accounted for pores occupied by ice and unfrozen water. The actual PSD indicated that the water-ice phase change was more pronounced in macro-and mesopores, especially at lower temperatures and salt content. A comparison between the calculated average pore size and those presented in other studies showed that the proposed technique is a valuable alternative for the prediction of actual frozen soil PSD. Abbreviations: κ, uniformity of the cumulative nuclear magnetic resonance-detected pore size distribution curve; BCC, bundle of cylindrical capillary model; MPVC, maximum pore volumetric content; NMR, nuclear magnetic resonance; PSD, pore size distribution; PSDC, pore size distribution curve; PVC, pore volumetric content; r, pore radius; r c , critical pore radius; r MPVC , radius of the maximum pore volumetric; SEM, scanning electron microscopy; T 2 , transverse relaxation time; T mf , water-ice phase change temperature; T s , supercooling temperature; VG, van Genuchten.

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Improving estimation of pore size distribution to predict the soil water retention curve from its particle size distribution

Cited by 27 publications

References 25 publications

A Simple Water Retention Model Based on Grain Size Distribution

A Simple Water Retention Model Based on Grain Size Distribution

Utilizing Alumina-Silica Enriched Bricks Debris Determining End Product of ML-CL Fill Soil: Advanced Stabilization Practices with Innovating Discarded Material

Characterizing the pore size distribution of a chloride silt soil during freeze–thaw processes via nuclear magnetic resonance relaxometry

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