A method for estimating soil water characteristic curve with limited experimental data

Ren, Xingwei; Kang, Jianyu; Ren, Junjie; Chen, Xiaojun; Zhang, Ming

doi:10.1016/j.geoderma.2019.114013

Cited by 30 publications

(10 citation statements)

References 42 publications

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“…e point S is the inflection point of SWCC (the point is largest absolute value of slope), from the perspective of pore size distribution; it corresponds to the point with the maximum value of frequency in the pore size distribution curve [57]. Because of the log-normal distribution of pore size of most soils, the maximum value of frequency in the pore size distribution curve can be considered as the mean pore size of the soil sample [37]. Besides this, Ren and Santamaina [58] and Ren et al [59] mentioned that the mean pore size can be expressed by void ratio and specific surface area.…”

Section: 3mentioning

confidence: 99%

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An Improved Prediction Method of Soil-Water Characteristic Curve by Geometrical Derivation and Empirical Equation

Zhou

Ren

2021

Mathematical Problems in Engineering

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Much attention has been paid on the soil-water characteristic curve (SWCC) during decades because it plays great roles in unsaturated soil mechanics. However, it is time-consuming and costly to obtain a series of entire saturation-suction data by experiments. The curves acquired by directly fitting empirical equations to limited experimental data are greatly different from the actual SWCC, and the relevant soil parameters obtained by inaccurate curve are also incorrect. Thus, an improved prediction method for more accurate entire SWCC was established. This novel method was based on the analysis of shape characteristics of SWCC with three critical points S , C 1 , and C 2 under the hypothesis of geometrical symmetric relation. The theoretical computation was specifically deduced under conventional Gardner, VG, and FX models, respectively, and then inferred on different soil types of 45 collected SWCC datasets. This geometrical symmetric relation exhibited well in all these three conventional empirical equations, especially in Gardner equation. Finally, a series of filer paper tests on sand, silt, and clay were also carried out to acquire entire SWCC curve for the verification and evaluation of the proposed geometrical method. Results show that this improved prediction method effectively decreases deviation resulting from directly fitting empirical equations to limited data of wide types of soils. The averaged improvement was larger under VG equation than under Gardner and FX equation. It proved that the accuracy of predicting greatly depends on the shape characteristic point of maximum curve curvature (point C 2 ), other than the number of points. This research provides a novel computation method to improve prediction accuracy even under relative less experimental data.

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Section: 3mentioning

confidence: 99%

“…Wang et al [36] combined statistical algorithms to predict entire SWCC from the Bayesian perspective, nevertheless, that approach is relatively complicated. Ren et al [37] proposed a method for estimating SWCC with limited data, but they did not quantitatively testify the feasibility of that method.…”

Section: Introductionmentioning

confidence: 99%

An Improved Prediction Method of Soil-Water Characteristic Curve by Geometrical Derivation and Empirical Equation

Zhou

Ren

2021

Mathematical Problems in Engineering

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“…The curve obtained was compared to those studied in the limited data model of Ren et al [17] that uses the Van Genuchten model and data compiled from 78 characteristic curves of different types of materials. The reference with which the experimentally measured suction data were most closely matched was Vanapalli et al [18].…”

Section: Soil Water Characteristic Curve (Swcc)mentioning

confidence: 99%

Ground heave movement evaluation in shallow foundations for expansive soils in Tunja, Colombia

2021

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A current challenge in unsaturated soil mechanics is the need to estimate ground heave and associated shallow foundation movements in expansive soils due to water content changes. Such estimation should be simple for geotechnical engineering practitioners and provide reliable foundation designs through quantifying the risk associated with the ground heave. The difficulties in generalizing a method are related to several variables influencing the expansive behavior, including the initial and final stress state condition, soil mineralogical composition, ground wetting depth, soil wetting degree, and geotechnical profile comprising soil strata thickness and groundwater condition. In this research, the evaluation of heave movements for the expansive soils located in the north-east of Tunja (Colombia) is performed through surrogate path (SPM), water content, and consolidation theory-based methods. Initial and final suction profiles were defined to quantify the wetting strains developed at each scenario of partial wetting. The sensitivity of the SPM to the estimated or measured value of constant volume swelling pressure was corroborated. The higher deformations that the soil profile would be able to develop when subjected to a progressive wetting were obtained along with the remaining heave capacity of the soil profile. Finally, concluding remarks and recommendations associated with the practicality and applicability of the methods are presented.

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“…Results always heavily depend on the accuracy of calculating or adapting the model’s parameter by utilizing pedotransfer functions ( Du, 2020 , Khlosi et al, 2008 ; Madi et al, 2018 ; Rawls et al, 1991 ; Wösten et al, 1999 ). Statistical models are also reliant on the soil pedotransfere functions as mostly generated from stepwise regression analysis for the available soil data, which consequently determine the accuracy and sensitivity of the final model ( Ghanbarian-Alavijeh and Liaghat, 2009 ; Mohawesh, 2013 ; Rawls and Brakensiek, 1982 ; Ren et al, 2020 ; Saxton and Rawls, 2006 ). The effect of soil physical properties on both types of models is obvious and prominent.…”

Section: Introductionmentioning

confidence: 99%

Characterizing physical and hydraulic properties of soils in Al-Ahsa, Kingdom of Saudi Arabia

Al-Saeedi

2022

Saudi Journal of Biological Sciences

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A method for estimating soil water characteristic curve with limited experimental data

Cited by 30 publications

References 42 publications

An Improved Prediction Method of Soil-Water Characteristic Curve by Geometrical Derivation and Empirical Equation

An Improved Prediction Method of Soil-Water Characteristic Curve by Geometrical Derivation and Empirical Equation

Ground heave movement evaluation in shallow foundations for expansive soils in Tunja, Colombia

Characterizing physical and hydraulic properties of soils in Al-Ahsa, Kingdom of Saudi Arabia

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