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Estimation of the Soil–Water Retention Curve from the Grain Size Distribution and Relative Density of Coarse-Grained Soils

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posted on 2025-11-21, 02:31 authored by Xin Liu, Ruixuan Li, Xi SunXi Sun, Jie Li, Xiaonan Wang
<p dir="ltr">The soil–water retention curve (SWRC) is a fundamental property that governs the hydraulic and mechanical behavior of unsaturated soils. Laboratory SWRC determination remains time-consuming and costly, promoting indirect estimation methods. However, existing methods often oversimplify the pore structure and particle arrangement of soils and neglect the effect of capillary menisci, resulting in discrepancies from natural soil behavior. This study proposes a novel method to estimate the SWRC of coarse-grained soils based on grain size distribution (GSD) and relative density. In the proposed method, soil particles are idealized as spheres in a two-dimensional (2D) plane, and the packing structure is modeled using representative quadrilaterals composed of four poly-disperse particles. The GSD is employed to calculate the probability of different particle sizes occupying the corners of the quadrilateral elements, while the relative density defines their geometric configuration. The water retention behavior is then evaluated using the geometric relationships between the air–water interface and particle radii. The predicted SWRCs are in good agreement with experimental data, indicating that the method can effectively capture the water retention characteristics of coarse-grained soils governed by capillary effects. The method’s applicability is limited to coarse-grained soils and excludes clayey soils where adsorbed water dominates retention mechanisms.</p>

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    DOI - Is published in DOI: 10.3390/app152212078
  3. 3.
    EISSN - Is published in 2076-3417 (Applied Sciences)

Journal

Applied Sciences

Volume

15

Number

12078

Issue

22

Total pages

17

Publisher

MDPI AG

Language

en

Copyright

© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

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