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water retention curves

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Journal Article
Published: 01 August 2016
Vadose Zone Journal (2016) 15 (8): vzj2015.12.0165.
..., at which the saturation reached 0.98. At 1.5 MPa, the air bubbles were compressed to a non-detectable level so that the sands were fully saturated. A mathematical model was established based solely on Boyle’s law to define the water retention curve in a broad sense for the domain where the water pressure...
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Journal Article
Published: 01 November 2014
Vadose Zone Journal (2014) 13 (11): vzj2014.06.0062.
...Chong Chen; Kelin Hu; Emmanuel Arthur; Tusheng Ren Abstract Accurate information on the dry end (matric potential less than −1500 kPa) of soil water retention curves (SWRCs) is crucial for studying water vapor transport and evaporation in soils. The objectives of this study were to assess...
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Journal Article
Published: 01 September 2015
Vadose Zone Journal (2015) 14 (9): vzj2015.01.0006.
... in the literature regarding their validity and consistency. In this study, four purposely designed experiments were carried out to measure the water retention curves (WRCs) of a compacted silty sand at different densities using the ATT and OMT. The four WRCs obtained from this study, together with extensive...
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Journal Article
Published: 01 June 2015
Vadose Zone Journal (2015) 14 (6): vzj2014.10.0148.
...Dennis W. Hallema; Yann Périard; Jonathan A. Lafond; Silvio J. Gumiere; Jean Caron Abstract Water retention curves are essential for the parameterization of soil water models such as HYDRUS. Although hydraulic parameters are known for a large number of mineral and natural organic soils, our...
FIGURES
Journal Article
Published: 01 August 2005
Vadose Zone Journal (2005) 4 (3): 602–613.
... geometry control the unsaturated soil hydraulic properties such as the water retention curve, while conversely soil water and hydraulic stress often affects soil pore size. The experiments discussed in this paper focus on both of these two aspects and additionally consider how a previously applied...
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Journal Article
Published: 01 August 2002
Vadose Zone Journal (2002) 1 (1): 179–185.
...Lyle Prunty; F. X. M. Casey Abstract Water retention curves (WRC) play an essential role in characterizing soil hydraulic behavior. Numerous mathematical functions have been explicitly developed for modeling the WRC, a very recent example being a cubic spline approach using virtual data points...
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Journal Article
Published: 01 May 2014
Vadose Zone Journal (2014) 13 (5): vzj2013.05.0094.
... is planned to investigate the effect of confining stress on the air entry and air expulsion values, in the drying and wetting process, respectively. To evaluate the influence of stress state on these parameters, the soil water retention curve (SWRC) of the soil is determined under two different applied net...
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Journal Article
Published: 01 November 2004
Vadose Zone Journal (2004) 3 (4): 1443–1454.
... by assuming an empirical relationship between pore sizes and particle sizes. This pore-size distribution has been used to develop the soil water retention curve and/or the relative conductivity curve. In this study, we develop soil water retention models from particle-size distribution data based...
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Retention measurements, optimized soil water retention curves, and associated pore size distributions. VG = van Genuchten (1980), MVG = modified van Genuchten (Vogel and Cislerova 1988), and BVG = bimodal van Genuchten (Durner 1994). The circles in 25 and 45 cm of VG highlight the third small pore size maximum.
Published: 01 January 2006
Fig. 2. Retention measurements, optimized soil water retention curves, and associated pore size distributions. VG = van Genuchten (1980) , MVG = modified van Genuchten ( Vogel and Cislerova 1988 ), and BVG = bimodal van Genuchten ( Durner 1994 ). The circles in 25 and 45 cm of VG highlight
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Scaled water retention curves along with their reference retention curve for sand (S), sandy loam (SL), loam (L), silt loam (SiL), clay loam (CL), silty clay loam (SiCL), silty clay (SiC), and all soils combined together.
Published: 01 May 2005
Fig. 4. Scaled water retention curves along with their reference retention curve for sand (S), sandy loam (SL), loam (L), silt loam (SiL), clay loam (CL), silty clay loam (SiCL), silty clay (SiC), and all soils combined together.
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Main water retention curves and hydraulic conductivity curves used in the hydraulic simulations. The arrows indicate drying or wetting curves, respectively.
Published: 01 January 2014
Fig. 5. Main water retention curves and hydraulic conductivity curves used in the hydraulic simulations. The arrows indicate drying or wetting curves, respectively.
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(a) Water retention curves, (b) water permeability functions, and (c) air permeability functions for silt, sand, clay, and gravel.
Published: 01 August 2015
Fig. 3. (a) Water retention curves, (b) water permeability functions, and (c) air permeability functions for silt, sand, clay, and gravel.
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Measured and simulated water retention curves and air–water interfacial area: (a) F-75 Ottawa sand; (b) river sand; (c) concrete sand; and (d) Texas sand.
Published: 01 May 2014
Fig. 5. Measured and simulated water retention curves and air–water interfacial area: (a) F-75 Ottawa sand; (b) river sand; (c) concrete sand; and (d) Texas sand.
Image
Water retention curves (effective water saturation [Se] as a function of water pressure head [h]) and saturated hydraulic conductivity (Ks) as a function of depth for Locations X and I and Plot 2. The data were acquired by the Tempe cell technique (a–e). Measured data (points) and the van Genuchten (1980) model (V.G. model, solid line) are shown, with retention curve parameters α and n given in the legend.
Published: 01 August 2008
F ig . 8. Water retention curves (effective water saturation [ S e ] as a function of water pressure head [ h ]) and saturated hydraulic conductivity ( K s ) as a function of depth for Locations X and I and Plot 2. The data were acquired by the Tempe cell technique (a–e). Measured data (points
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Sample soil water retention curves: ψ is the pressure head and θ the water content; NN-Pred are the neural network predicted values. Values at each point are averaged across 10 clustering levels. Error bars show deviation in θ(ψ) values across the clustering levels.
Published: 01 November 2007
F ig . 5. Sample soil water retention curves: ψ is the pressure head and θ the water content; NN-Pred are the neural network predicted values. Values at each point are averaged across 10 clustering levels. Error bars show deviation in θ(ψ) values across the clustering levels.
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Two representative water retention curves for clayey soils in the Shale Hills catchment (SH) and for sandy soils in the Garner Run catchment (GR) in the Susquehanna Shale Hills Critical Zone Observatory (SSHCZO). Dashed lines demonstrate the effects of increasing n from 1.6 (GR value) to 2.0, and decreasing α from 5.0 to 3.0 m−1. The range of water content (θs − θr) is a measure of potentially mobile water storage capacity per unit soil depth (paper in review).
Published: 01 September 2019
Figure 3. Two representative water retention curves for clayey soils in the Shale Hills catchment (SH) and for sandy soils in the Garner Run catchment (GR) in the Susquehanna Shale Hills Critical Zone Observatory (SSHCZO). Dashed lines demonstrate the effects of increasing n from 1.6 (GR value
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Comparison between in situ and reference water retention curves (WRCs) for the MPS-2, polymer tensiometer (POT), and pF-meter sensors. The whiskers show the standard deviation of the water content measured in five intact cores. The pF-meter measurement interval was 15 min.
Published: 01 April 2017
Fig. 5. Comparison between in situ and reference water retention curves (WRCs) for the MPS-2, polymer tensiometer (POT), and pF-meter sensors. The whiskers show the standard deviation of the water content measured in five intact cores. The pF-meter measurement interval was 15 min.
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Water retention curves of substrates (a) S1, (b) S2, (c) S3, (d) S4, and (e) S5. Black diamonds are observations and solid lines are the modeled values.
Published: 01 April 2017
Fig. 3. Water retention curves of substrates (a) S1, (b) S2, (c) S3, (d) S4, and (e) S5. Black diamonds are observations and solid lines are the modeled values.
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Water retention curves in the conventional and extended domains. In the extended domain, contributions from three mechanisms (mobilization of mobile bubbles, compression and dissolution of immobile bubbles) are shown schematically.
Published: 01 August 2016
Fig. 1. Water retention curves in the conventional and extended domains. In the extended domain, contributions from three mechanisms (mobilization of mobile bubbles, compression and dissolution of immobile bubbles) are shown schematically.
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Effect of compaction on the water retention curves of sands (a) S2 and (b) S5 and (c) of mixing different proportions of S2 and S5 on the soil water retention curve for a porosity ϕ of 0.40.
Published: 01 August 2016
Fig. 9. Effect of compaction on the water retention curves of sands (a) S2 and (b) S5 and (c) of mixing different proportions of S2 and S5 on the soil water retention curve for a porosity ϕ of 0.40.