Comparison of the performance of 22 models describing soil water retention curves from saturation to oven dryness. Issue 1 (30th September 2020)

• Record Type: Journal Article
• Authors: Du, Chaoyang
• Is Part Of: Vadose zone journal. Volume 19:Issue 1(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-09-30
• Subjects: Soil science -- Periodicals; Zone of aeration -- Periodicals; Groundwater flow -- Periodicals; Groundwater flow; Zone of aeration; Periodicals; Electronic journals; 631.4
• DOI: 10.1002/vzj2.20072
• Languages: English
• ISSNs: 1539-1663

Abstract

Abstract: Soil water retention curve (SWRC) is key hydraulic property for vadose zone hydrology. Selected 22 SWRC models with different structures were divided into four types: traditional, single‐segment, two‐segment, and three‐segment models. According to the accuracy and model selection criterion, these models were compared and evaluated using water retention data from saturation to oven dryness of 94 soil samples covering almost all soil types. Among the models, the EG model (exponential model combined with the Groenevelt–Grant model) shows the best performance, but the BC (Brooks–Corey) and VG (van Genuchten) models performed the worst. The relationship between model performance and complexity showed that traditional models with residual water content performed worse than segmental models from saturation to oven dryness, and the segmental models performed worse with an increase in the segment number. In general, models with more parameters perform better, but when the parameter number is greater than five, the model performance gradually worsens due to the equifinality of different parameters. The correlation analysis between soil properties on model performance showed that soil texture has a more significant effect on model performance than bulk density and organic matter content, because the models are primarily affected by their mathematical forms rather than the physical significance of the parameters. Each model picks its limitations and may apply to only one or particular group(s) of soil(s). Therefore, the complementarities of different models may be a great choice to improve SWRC fitting and simulation in arid soil. Core Ideas: Traditional models (e.g., BC and VG models) perform worse than segmental models. Segmental models perform worse with a growth of the curve segments. Models with more parameters perform better, but five parameters perform best. The model performance is not affected by soil properties due to the mathematical forms.