Estimating van Genuchten Parameters α and n for Clean Sands from Particle Size Distribution Data

Benson, Craig H.; Chiang, I-Ching; Chalermyanont, Tanit; Sawangsuriya, Auckpath

doi:10.1061/9780784413265.033

Cited by 52 publications

(60 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The table also shows the results predicted from the GP Model equations. Moreover, it shows the results predicted in Benson's (2014) [19] PTF for drying and wetting phases.Figures 5 and 6 show the evaluation of the results predicted from the GP Model equations versus the measured values in the two phases. The evaluation was conducted on the basis of the training and testing datasets.…”

mentioning

confidence: 93%

“…This study uses the Genetic Programming (GP) for the presentation of equations estimating the van Genuchten (vG) Model fitting parameters for unsaturated clean sand soils. Moreover, this study uses the data derived from the valid dataset of Benson et al (2014), including 95 measured SWCCs in both drying and wetting phases. The data on the particle size distributions includes the fine-grain percentage (Fines %), d60, d10, besides the residual and saturated volumetric water content (θ and θ ), as the GP model inputs of set of terminal.…”

Section: Introductionmentioning

confidence: 99%

“…To this end, the predicted results of the GP Model will be presented in Table 3 for the selected testing datasets. In addition to a and n values obtained from precise measurements, the datasets of the two phases include the predicted values of PTF (pedotransfer functions) equations developed by Benson (2014) [19]. Table 3 shows the results of the SWCC fitting parameters measured in the laboratory.…”

mentioning

confidence: 99%

“…In order to fit the abovementioned values of suction and its corresponding volumetric water content, Equation 1 was used [18]. In the dataset collected by Benson et al (2014) [18], some samples have just the drying data, some others have just the wetting data, and some others have the two types of data. For this reason, the present study divides Benson's initial dataset into two parts, that is, the drying phase and the wetting phase.…”

mentioning

confidence: 99%

“…Since the percentage of fine grains has a significant effect on the behavior of unsaturated soil, there will be an inappropriate prediction for the proposed equations with (PI=0) if one ignores the pass percentage of sieve #200. Based on the characteristics of particle size distribution of the clean sands, Benson et al (2014) [18] proposed separate equations for the estimations of the fitting parameters of van Genuchten SWCC model for both wetting and drying phases. These equations were just functions of the two parameters of d60 and Cu=d60/d10 of clean sand soils.…”

mentioning

confidence: 99%

See 4 more Smart Citations

The Estimation of van Genuchten SWCC Model for Unsaturated Sands by means of the Genetic Programming

2017

View full text Add to dashboard Cite

The van Genuchten Model (1980) is widely-used for the description of the Soil-Water Characteristic Curve (SWCC) of a variety of soils. This study uses the Genetic Programming (GP) for the presentation of equations estimating the van Genuchten (vG) Model fitting parameters for unsaturated clean sand soils. Moreover, this study uses the data derived from the valid dataset of Benson et al. (2014), including 95 measured SWCCs in both drying and wetting phases. The data on the particle size distributions includes the fine-grain percentage (Fines %), d60, d10, besides the residual and saturated volumetric water content (θ and θ ), as the GP model inputs of set of terminal. As for the model outputs of set of terminal, the fitting parameters for the vG model include a and n. The functions used in the GP training were 'plus', 'minus', 'times', taken from the MATLAB default functions, 'mydivide' proposed by Silva (2007), and some other new power functions included by this study. Accordingly, new equations were presented for the estimation of vG Model fitting parameters for both forms of wetting and drying. Finally, to evaluate the accuracy of the proposed estimation equations, the GP results were evaluated and verified in different procedures.Keywords: SWCC, van Genuchten Model, Unsaturated Soils, Genetic Programming, Fitting Parameters *Corresponding author. Tel: +98-912-568-3767 Fax: +98-6633243999 E-mail addresses: am.taban@gmail.com (A. Taban); msadeghi@ieht.ac.ir (M. Mirmohammad Sadeghi); mohamali@cc.iut.ac.ir (M.A. Rowshanzamir); Postal Address: Department of Civil Engineering Isfahan (Khorasgan) Branch, Islamic Azad University, Jey Street, Arqavanieh, University Blvd. PO Box: 158-81595, Isfahan, Iran 2 1.IntroductionSoil-Water Characteristic Curve (SWCC) is one of the widely-used concepts in the earth-related sciences, and particularly, in the mechanics of unsaturated soils. It describes the relationship between the amounts of water in the soil structure and the matric suction in the soil. Many analyses and numerical studies of unsaturated soils depend on the SWCC. Such expressions as the volumetric water content, the degree of saturation, and the normalized water content are used for the amount of water within the soil [1].There are various methods for the measurement of SWCC, many of which are costly and time-consuming. However, they are different from each other in terms of their capabilities of measuring different ranges of the suction. What follows is a list of measurement methods that directly measure the SWCC: The Hanging Column, the Pressure Plate Extractor (PPT), the Chilled Mirror Hygrometer, and the Centrifuge, which directly measure SWCC and the procedure has been explained in ASTM D6836 [2]. In contrast, there is another group of experiments which measure the values indirectly, for example: Filter Paper, Heat Dissipation, Thermal Conductivity Sensor Technique, Chilled-Mirror, Hygrometer Technique, and so forth [3]. These methods of suction measurement will measure different ranges of suct...

show abstract

mentioning

confidence: 93%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

See 3 more Smart Citations

The Estimation of van Genuchten SWCC Model for Unsaturated Sands by means of the Genetic Programming

2017

View full text Add to dashboard Cite

show abstract

Impact of coastal marsh eco-geomorphologic change on the prediction of saltwater intrusion under future sea level rise

Svyatsky

Rowland

et al. 2021

Preprint

View full text Add to dashboard Cite

Coastal saltwater intrusion (SWI) is one key factor affecting the hydrology, nutrient transport, and biogeochemistry of coastal marsh landscapes. Future climate change, especially intensified sea level rise (SLR), is expected to trigger SWI to encroach coastal freshwater aquifers more intensively. Numerous studies have investigated decadal/century scale SWI under SLR by assuming a static coastal landscape topography. However, coastal marshes are highly dynamic systems in response to SLR, and the impact of coastal marsh evolution on SWI has received very little attention. Thus, this study investigated how coastal marsh evolution affects future SWI with a physically-based coastal hydro-eco-geomorphologic model, ATS (Advanced Terrestrial Simulator). Our synthetic modeling experiments showed that it is very likely that the marsh elevation increases with future SLR, and a depression zone is formed due to the different marsh accretion rates between the ocean boundary and the inland. We found that, compared to the cases without marsh evolution, the marsh accretion may significantly reduce the surface saltwater inflow at the ocean boundary, and the evolved topographic depression zone may prolong the residence time of surface ponding saltwater, which causes distinct subsurface salinity distributions. We also found that the marshland may become more sensitive to the upland groundwater table that controls the freshwater flux to the marshes, compared with the cases without marsh evolution. This study demonstrates the importance of marsh evolution to the freshwater-saltwater interaction under sea level rise and can help improve our predictive understanding of the vulnerability of the coastal freshwater system to sea level rise. Hosted filesupporting-information_for_submission.docx available at https://authorea.com/users/524393/ articles/597484-impact-of-coastal-marsh-eco-geomorphologic-change-on-the-prediction-ofsaltwater-intrusion-under-future-sea-level-rise

show abstract

The impact of aquifer stratification on saltwater intrusion characteristics. Comprehensive laboratory and numerical study

Etsias

Hamill

Águila

et al. 2021

Hydrological Processes

View full text Add to dashboard Cite

Laboratory experiments and numerical simulations were utilized in this study to assess the impact of aquifer stratification on saltwater intrusion. Three homogeneous and six layered aquifers were investigated. Image processing algorithms facilitated the precise calculation of saltwater wedge toe length, width of the mixing zone, and angle of intrusion. It was concluded that the length of intrusion in stratified aquifers is predominantly a function of permeability contrast, total aquifer transmissivity and the number of heterogeneous layers, being positively correlated to all three. When a lower permeability layer overlays or underlays more permeable zones its mixing zone widens, while it becomes thinner for the higher permeability strata. The change in the width of the mixing zone (WMZ) is positively correlated to permeability contrast, while it applies to all strata irrespectively of their relative vertical position in the aquifer. Variations in the applied hydraulic head causes the transient widening of WMZ.These peak WMZ values are larger during saltwater retreat and are negatively correlated to the layer's permeability and distance from the aquifer's bottom. Moreover, steeper angles of intrusion are observed in cases where low permeability layers overlay more permeable strata, and milder ones in the inverse aquifer setups. The presence of a low permeability upper layer results in the confinement of the saltwater wedge in the lower part of the stratified aquifer. This occurs until a critical hydraulic head difference is applied to the system. This hydraulic gradient value was found to be a function of layer width and permeability contrast alike.

show abstract

Estimating van Genuchten Parameters α and n for Clean Sands from Particle Size Distribution Data

Cited by 52 publications

References 13 publications

The Estimation of van Genuchten SWCC Model for Unsaturated Sands by means of the Genetic Programming

The Estimation of van Genuchten SWCC Model for Unsaturated Sands by means of the Genetic Programming

Impact of coastal marsh eco-geomorphologic change on the prediction of saltwater intrusion under future sea level rise

The impact of aquifer stratification on saltwater intrusion characteristics. Comprehensive laboratory and numerical study

Contact Info

Product

Resources

About