Predictive models for the residual saturation zone of the soil–water characteristic curve


Journal of Soils and Sediments, vol.23, no.11, pp.3974-3989, 2023 (SCI-Expanded) identifier

  • Publication Type: Article / Article
  • Volume: 23 Issue: 11
  • Publication Date: 2023
  • Doi Number: 10.1007/s11368-023-03646-0
  • Journal Name: Journal of Soils and Sediments
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Agricultural & Environmental Science Database, Aquatic Science & Fisheries Abstracts (ASFA), BIOSIS, CAB Abstracts, Environment Index, Geobase, Pollution Abstracts, Veterinary Science Database
  • Page Numbers: pp.3974-3989
  • Keywords: Multivariate linear stepwise regression, Residual saturation zone, SWCC, Total suction
  • Süleyman Demirel University Affiliated: Yes


Purpose: Soil–water characteristic curve (SWCC) models have generally been developed based on measurement results in the low suction range. However, different mechanisms govern the SWCC in the low suction range (desaturation zone) and high suction range (residual zone). Accurate estimation of the residual zone is critical for analysing the behaviour of soils in arid regions. This study aimed to develop prediction models for the residual zone based on selected properties of soils. Materials and methods: To achieve the abovementioned purpose, 162 total suction (in pF) and gravimetric water content (%) measurement pairs in the high suction range were made on 40 cohesive soil samples with known physical, chemical, and spectral properties. A semi-logarithmic linear model was used to define the residual saturation zone of the SWCC. The model parameters were the slope of the SWCC (sr) and total suction at zero water content (ψdry). Correlation and stepwise regression analyses were carried out between the model parameters and selected soil properties. The regression equations were validated using the four-fold cross-validation procedure. Water content (%) estimation models were developed using combinations of different regression equations for sr and ψdry , and their estimates were evaluated using performance metrics. Results and discussion: The sr values for the soils studied ranged from 1.589 to 13.035, with an average of 6.007. Although some studies have shown strong correlations between clay content and sr , no significant relationship was found between clay content and sr for the soils in this study. However, significant correlations were found between the consistency limits, some spectral parameters, and sr . The R 2 was 0.88 when the liquid limit (LL) and depth of the 1900 nm wavelength band (D1900) values were used as descriptive variables. The ψdry values for the soils studied ranged from 6.483 to 7.370 pF, with an average of 6.855 pF. The relationships between the selected soil properties and ψdry were weak, consistent with previous research. Conclusion: The spectral absorption characteristics of the soils in this study had a high potential for estimating the SWCC. Prediction models based on various sr and ψdry equation combinations could predict measured water content values with varying degrees of accuracy. The SWCC’s residual saturation zone was accurately estimated using soil properties such as liquid limit, electrical conductivity, and spectral characteristics that can be determined quickly and inexpensively.