@article{WANG2026, 
author = {Song-he WANG and Xu-wei ZHAO and Shuai NIU and Jia-ding WANG},
title = {Modeling of water retention behavior of compacted loess to account for soil texture variability},
year = {2026},
journal = {Rock and Soil Mechanics},
volume = {47},
number = {10},
pages = {3493-3508},
keywords = {water retention curve, compacted loess, fines content, plasticity index, void ratio},
url = {https://www.sciopen.com/article/10.26599/RSM.2025.94300386},
doi = {10.26599/RSM.2025.94300386},
abstract = {This study aims to establish a generalized water-retention model by correlating model parameters with fundamental physical indexes of loess. Water retention test data from 35 sources of loess soils in northwest China were optimally fitted to yield parameters for the generalized water retention model (the Zhou-Lu model). These loess soils, classified as lean clay, encompass a broad range of particle size distribution (8.60%–37.85% in clay content), plasticity index (7.20–17.00), and dry density (1.23–1.83 g/cm3). Spearman correlation analysis between model parameters and both single and synthetic physical indexes indicates significant correlations of maximum adsorbed water content wamax with fines content Pfine, air-entry value 1/α with wIPe (the product of weighted plasticity index wIP and void ratio e), and capillary pore size distribution n with plasticity index IP, which were respectively described as simple empirical functions. The other three parameters (maximum matric suction ψmax, adsorption strength parameter m, mean cavitation suction ψc) are highly indeterminate and lack experimental evidence; therefore, the means were taken from their statistical distributions. The above parameters were incorporated into the Zhou-Lu model. Deviations of model predictions from the dataset mostly fall within ±30%. Further verification, based on water retention test data of compacted loess from three sampling sites (Baishui, Jingyang, and Hengshan), confirmed the rationale of the model. This preliminarily indicates the robustness of the Zhou-Lu model for loess soils with diverse textures, and allows for further refinement given improved datasets.}
}