Soil-Water Characteristic Curve Model Based on Particle Size Distribution and Pellicular Water

doi:10.11988/ckyyb.20240089

Abstract

Abstract:

Traditional models for predicting soil-water characteristic curve (SWCC) based on particle size distribution curve require segmentation of the curve when calculating water content and often neglect the pellicular water (also known as film water) content on the surface of soil particles. This significantly limits the prediction accuracy. To address these issues, this study assumes point-to-point contact between particles, employs the Weibull function to characterize the particle size distribution curve, determines the capillary water content using the Young - Laplace equation, and accounts for the influence of film water content. On this basis, a new SWCC model considering particle size distribution and film water is developed. Twenty-six soil samples from the Unsaturated Soil Database (UNSODA) are selected for validation and comparison with the AP and MV models. The results indicate that the proposed model based on particle size distribution and film water can predict the SWCC more accurately and significantly reduces the prediction error of water content in the high-matrix-suction section.

Key words: soil-water characteristic curve, particle size distribution curve, capillary water, film water, water content prediction

CLC Number:

TU43土力学

ZHU Shi-wang, LI Shuang-yang, JIANG Qi, ZHAO Jian-yuan, ZHOU Shang-qi, LIU Hui-ying. Soil-Water Characteristic Curve Model Based on Particle Size Distribution and Pellicular Water[J]. Journal of Changjiang River Scientific Research Institute, 2025, 42(5): 200-207.

Figures/Tables 12

Fig.1 Schematic diagram of particle point-to-point contact

Table 1 Soil types and numbering

土壤类型	UNSODA中土壤编号
砂土	1460,1462,1464,1466,3340,4060
砂质壤土	1010,1015,4580
壤土	1211,1260,1261,2530,2 531,3302,4790
黏质壤土	1123,2743,3031,3033
黏土	1400,2340,2681,4120,4680,4681

Fig.2 Comparison of predicted and measured data for different soil types using three models

Fig.3 Comparison chart with the same scale between measured and predicted water content

Table 2 RMSE statistics for predicting SWCC with three models

土壤类型	均方根误差
土壤类型	AP模型	MV模型	新模型
砂土	0.068 6	0.033 9	0.012 8
砂质壤土	0.068 2	0.052 6	0.024 9
壤土	0.141 9	0.083 0	0.016 5
黏质壤土	0.048 9	0.048 0	0.026 2
黏土	0.082 8	0.048 8	0.010 2

Fig.4 Comparison of RMSE among three models

Fig.5 Comparison of MV model and Hamamoto model with the proposed model

Table 3 RMSE statistics for three models

土壤样品编号	RMSE
土壤样品编号	MV模型	Hamamoto模型	新模型
砂土3340	0.042 1	0.029 5	0.012 5
黏土4680	0.055 8	0.033 4	0.009 9

Fig.6 Particle size distribution curve and SWCC at different a(b=2)

Fig.7 Particle size distribution curve and SWCC at different b(a=1×10-4)

Fig.8 Comparison of the predictive performance of the proposed model using Weibull function and segmentation method

Fig.9 Contributions of adsorbed water and capillary water in sandy soil

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