ArticlePloS one2025
Estimation of bimodal soil-water characteristics curve under wetting process.
Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Integrating experimental data and machine learning to predict collapse potential of loessic and lacustrine-alluvial soils using suction and SWCC parameters.Scientific reports · 2026Article
- Effects of wet-dry cycles on the bimodal soil-water characteristic curve and unsaturated permeability of granite residual soil.PloS one · 2026Article
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Authors and funding
4 authors.
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Abstract
Soil-water characteristics curve (SWCC) is hysteretic. The hysteretic curves represent the soil conditions during drying and wetting processes. Almost all failure of geotechnical structures, particularly in soils with dual porosity (bimodal soils) occurs during soil wetting, making the wetting curve more relevant to geotechnical applications than the drying curve. Still, due to the high-cost implications, time require, and difficulties associated with measuring SWCC under wetting process, the wetting curve has been continuously neglected. This leads to analyses that do not reflect the actual soil condition, which may result in structural failure. Although bimodal soils are encountered in many areas across the globe, there is no mathematical model for estimating bimodal SWCC under wetting process. This work developed a new mathematical equation to estimate a bimodal SWCC under wetting process. The proposed model also has parameters with physical meaning in relation to the variables of the wetting SWCC, which is very important in practical applications and numerical analyses. Six soil types were used in the model validation. The overall model performance has been evaluated through statistical methods using the coefficient of determination (R2) and Root Mean Square Error (RMSE). The evaluation also indicates a good performance of the model, with an average RMSE of 0.0263 and an average R2 of 0.9945 for the six soil samples used in the validation. Given the significance of wetting-induced failures, the proposed model is highly relevant in engineering applications.
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