Xu et al. (2025) Construction and Application of Soil–Water Characteristic Curve Model Considering Water Mineralization Degree

Identification

• Journal: Agriculture
• Year: 2025
• Date: 2025-11-28
• Authors: Ding Xu, Qian Xu, Feilong Jie, Mingsheng Fan, Yanyan Ge, Sheng Li
• DOI: 10.3390/agriculture15232470

Research Groups

• School of Geology and Mining Engineering, Xinjiang University, Urumqi, China

Short Summary

This study developed and validated a modified Van Genuchten (VG) model for the soil–water characteristic curve (SWCC) that explicitly accounts for irrigation water salinity, demonstrating improved accuracy in predicting soil water dynamics in saline environments of southern Xinjiang.

Objective

• To investigate the effects of irrigation water salinity on the soil–water characteristic curve (SWCC) of loam soils in a typical irrigated area of Yingjisha County, southern Xinjiang.
• To develop and validate an optimized Van Genuchten (VG) model that incorporates the influence of water mineralization degree to enhance the accuracy of soil water dynamics simulation.

Study Configuration

• Spatial Scale: Loam soil samples collected from three sites (M1: Silty Soil, M2: Silt, M3: Sandy Loam) in Yingjisha County, southern Xinjiang, China. Laboratory experiments used cylindrical centrifuge test specimens (50 cm² base area, 2 cm height) and one-dimensional soil columns (0.6 m depth).
• Temporal Scale: Centrifuge tests maintained each rotational speed for 1 hour. One-dimensional constant-head soil column infiltration tests were monitored at 5-minute intervals until the wetting front reached the column base. No overall study duration was specified.

Methodology and Data

• Models used:
  • Soil–Water Characteristic Curve (SWCC) models: Van Genuchten (VG), Brooks–Corey (BC), Gardner (GW), and Fredlund–Xing (FX) models were evaluated.
  • Optimized Van Genuchten (VG) model: A modified VG model was developed to incorporate the influence of irrigation water salinity.
  • Numerical simulation: Richards equation, parameterized by the Van Genuchten scheme, was used in COMSOL Multiphysics.
  • Data analysis and fitting: MATLAB 2021a was used for nonlinear least squares fitting and correlation analysis.
• Data sources:
  • Soil samples: Undisturbed and disturbed soil samples from 0–20 cm depth in Yingjisha County, southern Xinjiang, China.
  • SWCC determination: Centrifuge method using a CR22N high-speed refrigerated centrifuge.
  • Test solutions: NaCl solutions with mineralization gradients of 1, 3, 5, 7, and 9 g L⁻¹, and ultrapure water as reference.
  • Infiltration tests: One-dimensional constant-head soil column infiltration experiments.
  • Soil moisture monitoring: TDR-6 soil moisture sensors installed at 0.15 m, 0.30 m, and 0.45 m depths in soil columns.
  • Soil physicochemical properties: Particle size distribution, inorganic salt content, and bulk density were measured.

Main Results

• Soil physical properties significantly influence water retention capacity, with grey correlation analysis ranking their influence on SWCC parameters as: soil dry bulk density (1st) > clay content (2nd) > inorganic salt content (3rd) > silt content (4th).
• Soils with higher clay and silt contents, along with greater bulk density (e.g., 1540 kg m⁻³ for M1, 1620 kg m⁻³ for M2, 1320 kg m⁻³ for M3), exhibited enhanced water retention capacity and a flatter SWCC.
• Irrigation water mineralization showed a non-linear, threshold-dependent effect on water retention: initially, increasing salinity enhanced water absorption, but beyond a mineralization degree of 1 g L⁻¹, the rate of enhancement slowed, and overall water retention performance began to decline.
• Among traditional models, the Van Genuchten (VG) model provided the best fit for loam soils in the study area, but with non-negligible deviations, indicating a need for refinement.
• A modified VG model, incorporating irrigation water mineralization as a key parameter, was developed. This model established quadratic polynomial relationships for parameter α(k) and power functions for n(k) and θs(k) with respect to mineralization level (k).
• Validation experiments confirmed that the modified VG model substantially improved predictive capabilities. In primary application scenarios (middle-layer soil of M1 and M3), it reduced the Root Mean Square Error (RMSE) by over 40% and increased the coefficient of determination (R²) by more than 13% compared to the traditional model.

Contributions

• Developed and validated a novel Soil–Water Characteristic Curve (SWCC) model based on the Van Genuchten framework that explicitly incorporates the influence of irrigation water mineralization degree.
• Established, for the first time, specific functional relationships (quadratic for α, power for n and θs) between key VG model parameters and water mineralization level, overcoming limitations of traditional empirical models.
• Provided a theoretical foundation for understanding soil water dynamics under brackish water irrigation, crucial for the prevention and amelioration of saline soils and efficient water resource utilization in arid regions like southern Xinjiang and Central Asia.

Funding

• Tianshan Talent Training Program (grant number 2023TSYCCX0091).

Citation

@article{Xu2025Construction,
  author = {Xu, Ding and Xu, Qian and Jie, Feilong and Fan, Mingsheng and Ge, Yanyan and Li, Sheng},
  title = {Construction and Application of Soil–Water Characteristic Curve Model Considering Water Mineralization Degree},
  journal = {Agriculture},
  year = {2025},
  doi = {10.3390/agriculture15232470},
  url = {https://doi.org/10.3390/agriculture15232470}
}