An analytical model to predict water retention curves for granular materials using the grain-size distribution curve
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Dec 10, 2022
About this article
Article Category: Original Study
Published Online: Dec 10, 2022
Page range: 354 - 369
Received: Jan 01, 2022
Accepted: Sep 27, 2022
DOI: https://doi.org/10.2478/sgem-2022-0025
Keywords
© 2022 Linda Bouacida et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.
Figure 1
![Conceptual diagram showing the effect of (a) median particle size of uniform sand and (b) width of particle size distribution, on the shape of the soil-water characteristic curve (SWCC) of sand (Craig H. Benson et al. [14]).](https://sciendo-parsed.s3.eu-central-1.amazonaws.com/64737a0a4e662f30ba53f8b8/j_sgem-2022-0025_fig_001.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Credential=AKIA6AP2G7AKOUXAVR44%2F20250920%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-Date=20250920T135710Z&X-Amz-Expires=3600&X-Amz-Signature=de5ef92ba9288daafca29fddef89700cb2474e2fcc462a88acf5aede49fd4cdb&X-Amz-SignedHeaders=host&x-amz-checksum-mode=ENABLED&x-id=GetObject)
Figure 2
![Conceptual diagram presenting the effect of (a) the median particle size of uniform sand, and (b) the breadth of particle size distribution, on the parameters α and n (Craig H. Benson et al. [12]).](https://sciendo-parsed.s3.eu-central-1.amazonaws.com/64737a0a4e662f30ba53f8b8/j_sgem-2022-0025_fig_002.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Credential=AKIA6AP2G7AKOUXAVR44%2F20250920%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-Date=20250920T135710Z&X-Amz-Expires=3600&X-Amz-Signature=80e21c321fb9f7ddd2e3780e0a4c9fc3184e1895aaed77bfc69221a106340554&X-Amz-SignedHeaders=host&x-amz-checksum-mode=ENABLED&x-id=GetObject)
Figure 3
![Typical soil water retention curve (Toll [59]).](https://sciendo-parsed.s3.eu-central-1.amazonaws.com/64737a0a4e662f30ba53f8b8/j_sgem-2022-0025_fig_003.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Credential=AKIA6AP2G7AKOUXAVR44%2F20250920%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-Date=20250920T135710Z&X-Amz-Expires=3600&X-Amz-Signature=4d2f36163b8fa1b622b61c7fe6af7893a45084feaba473d9812b348bad41d8a7&X-Amz-SignedHeaders=host&x-amz-checksum-mode=ENABLED&x-id=GetObject)
Figure 4
![Explanatory diagram of the drying and wetting processes in the porous network that is composed of cylinders with radius r; rm is the meniscus radius at the air-water interface (Do. [19]).](https://sciendo-parsed.s3.eu-central-1.amazonaws.com/64737a0a4e662f30ba53f8b8/j_sgem-2022-0025_fig_004.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Credential=AKIA6AP2G7AKOUXAVR44%2F20250920%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-Date=20250920T135710Z&X-Amz-Expires=3600&X-Amz-Signature=00f68991ab58cb838fea178ce83f22209ed0bdcb22941f32fe5779ddff76c019&X-Amz-SignedHeaders=host&x-amz-checksum-mode=ENABLED&x-id=GetObject)
Figure 5
![Schematic representation of the tensiometric method for the measurement of suction (Feia et al. [25]).](https://sciendo-parsed.s3.eu-central-1.amazonaws.com/64737a0a4e662f30ba53f8b8/j_sgem-2022-0025_fig_005.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Credential=AKIA6AP2G7AKOUXAVR44%2F20250920%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-Date=20250920T135710Z&X-Amz-Expires=3600&X-Amz-Signature=501d0d1fb1ac9683120b4997e2016d3418079af7488ee56944c6274bc16e6ec7&X-Amz-SignedHeaders=host&x-amz-checksum-mode=ENABLED&x-id=GetObject)
Figure 6
![Experimental results used in this study (Feia et al. [25]).](https://sciendo-parsed.s3.eu-central-1.amazonaws.com/64737a0a4e662f30ba53f8b8/j_sgem-2022-0025_fig_006.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Credential=AKIA6AP2G7AKOUXAVR44%2F20250920%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-Date=20250920T135710Z&X-Amz-Expires=3600&X-Amz-Signature=8112d5ed2c7e7d2f8c9c30bad75243cf36d281628aec9db28672fd1a0d15d359&X-Amz-SignedHeaders=host&x-amz-checksum-mode=ENABLED&x-id=GetObject)
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Figure 18
![Comparison between the results obtained by the proposed model and those calculated by the law of Della and Feia [47].](https://sciendo-parsed.s3.eu-central-1.amazonaws.com/64737a0a4e662f30ba53f8b8/j_sgem-2022-0025_fig_018.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Credential=AKIA6AP2G7AKOUXAVR44%2F20250920%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-Date=20250920T135710Z&X-Amz-Expires=3600&X-Amz-Signature=2d56914e963f27cdf387584c3ef9de82f8b75bd9a1b8ce1ae80c3ac4349f421f&X-Amz-SignedHeaders=host&x-amz-checksum-mode=ENABLED&x-id=GetObject)
Values of the parameters of the proposed model for the three types of sand_
α | 4.5 | 3.4 | 3 |
8.5 | 7.3 | 6 |
Characteristics of the materials to be analyzed_
Type 1 | 0.18 | 1.5 | 0.51 | 0.79 | 2.65 |
Type 2 | 0.37 | 2.85 | 0.47 | 0.75 | 2.65 |
Type 3 | 0.42 | 2.47 | 0.47 | 0.76 | 2.65 |
Type 4 | 0.5 | 5 | 0.44 | 0.77 | 2.65 |
Characteristics of the used sands_
NE34 | 206 | 1.5 | 0.557 | 0.884 | 2.65 |
0.9 | 0.7 | 0.5 |