Spatial Variability of Soil Water Retention Functions in a Silt Loam Soil

Shouse, P. J.; Russell, W. B.; Burden, David S.; Selim, H. M.; Sisson, J. B.; Genuchten, M. Th. van

doi:10.1097/00010694-199501000-00001

Cited by 45 publications

(25 citation statements)

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“…Spatial variability of hydraulic properties has been documented in many articles (e.g. Nielsen et al, 1973;Simmons et al, 1979, Russo andBouton, 1992;Istok et al, 1994;Jarvis and Messing, 1995;Mohanty et al, 1994;Shouse et al, 1995;Russo et al, 1997;Shouse and Mohanty, 1998). Water contents in the field are mostly found to be normally distributed with medium variation (coefficient of variation, 0.15 < cv < 0.5; Jury et al, 1991;Warrick, 1998), with increasing variability when the soils dry out (Shouse et al, 1995).…”

Section: Spatial and Temporal Variabilitymentioning

confidence: 97%

“…Nielsen et al, 1973;Simmons et al, 1979, Russo andBouton, 1992;Istok et al, 1994;Jarvis and Messing, 1995;Mohanty et al, 1994;Shouse et al, 1995;Russo et al, 1997;Shouse and Mohanty, 1998). Water contents in the field are mostly found to be normally distributed with medium variation (coefficient of variation, 0.15 < cv < 0.5; Jury et al, 1991;Warrick, 1998), with increasing variability when the soils dry out (Shouse et al, 1995). Field investigations of hydraulic conductivities yield in most cases lognormal distributions, with variances of log(K) in the order of 1 (Dagan, 1984;Butters et al, 1989;Heuvelman and McInnes, 1997;Holt et al, 2002).…”

Section: Spatial and Temporal Variabilitymentioning

confidence: 99%

“…Horizontal correlation scales for hydraulic properties were reported to be in the order of 6 m to 20-30 m (Ciollaro and Romano, 1995;Shouse et al, 1995), whereas vertical correlation scales are in the order of 0.1 to 0.3 m (Robin et al, 1991;Wierenga et al, 1991). Heuvelman and McInnes (1997) investigated spatial variability of water fluxes on a scale of centimeters and found water flux densities to be normally distributed in a sandy topsoil, becoming lognormally distributed in a loamy subsoil.…”

Section: Geostatistical Characterization Of Random Variabilitymentioning

confidence: 99%

“…Heuvelman and McInnes (1997) investigated spatial variability of water fluxes on a scale of centimeters and found water flux densities to be normally distributed in a sandy topsoil, becoming lognormally distributed in a loamy subsoil. Jury (1985) and Shouse et al (1995) noted that the range of spatial influence may be related to the scale of the sampled area, and that the commonly observed high nugget variance of soil hydraulic properties may be more closely related to measurement error than to high frequency, small-scale variations.…”

Section: Geostatistical Characterization Of Random Variabilitymentioning

confidence: 99%

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Soil Hydraulic Properties

Durner

Flühler²

2005

Encyclopedia of Hydrological Sciences

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The accurate knowledge of hydraulic properties for unsaturated soils is critical in addressing problems in a variety of disciplines such as hydrology, ecology, environmental sciences, soil science, and agriculture. The purpose of this paper is to review the characterization of unsaturated soil hydraulic properties for their applicability in models simulating unsaturated water transport. In a theoretical section, we present the fundamentals for the definitions of the hydraulic properties in the framework of the continuum theory as well as provide the common parameterizations of the hydraulic functions. The characterization and parameterization of hysteresis and the phenomenon of dynamic effects in hydraulic properties are addressed in subsequent sections. Finally we discuss issues related to the handling of spatial and temporal variability, including geostatistical characterization, upscaling, and scale dependency of effective properties. The review closes with a summary on limits and opportunities for modeling water transport with Richards' equation.

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Section: Spatial and Temporal Variabilitymentioning

confidence: 97%

Section: Spatial and Temporal Variabilitymentioning

confidence: 99%

Section: Geostatistical Characterization Of Random Variabilitymentioning

confidence: 99%

Section: Geostatistical Characterization Of Random Variabilitymentioning

confidence: 99%

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Soil Hydraulic Properties

Durner

Flühler²

2005

Encyclopedia of Hydrological Sciences

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“…In Oliveira et al (2006), stochastic fields of "parameters" were generated using conditioning parameters to simulate variably-saturated water flow in soils. In some studies, the number of parameters is even reduced to one or two by using the scaling method (e.g., Shouse et al, 1995;Oliveira et al, 2006). The question then arises whether or not we can consider these derived (i.e., averaged or randomly generated) parameters to be equivalent to experimentally measured soil physical properties, such as volumetric water contents.…”

Section: Introductionmentioning

confidence: 99%

An alternative deterministic method for the spatial interpolation of water retention parameters

Saito

Seki

Šimůnek

2009

Hydrol. Earth Syst. Sci.

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Abstract. There are two approaches available for mapping water retention parameters over the study area using a spatial interpolation method. (1) Retention models can be first fitted to retention curves available at sampling locations prior to interpolating model parameters over the study area (the FI approach). (2) Retention data points can first be interpolated over the study area before retention model parameters are fitted (the IF approach). The current study compares the performance of these two approaches in representing the spatial distribution of water retention curves. Standard geostatistical interpolation methods, i.e., ordinary kriging and indicator kriging, were used. The data used in this study were obtained from the Las Cruces trench site database, which contains water retention data for 448 soil samples. Three standard water retention models, i.e., Brooks and Corey (BC), van Genuchten (VG), and Kosugi (KSG), were considered. For each model, standard validation procedures, i.e., leave-oneout cross-validation and split-sample methods were used to estimate the uncertainty of the parameters at each sampling location, allowing for the computation of prediction errors (mean absolute error and mean error). The results show that the IF approach significantly lowered mean absolute errors for the VG model, while also reducing them moderately for the KSG and BC models. In addition, the IF approach resulted in less bias than the FI approach, except when the BC model was used in the split-sample approach. Overall, IF outperforms FI for all three retention models in describing the spatial distribution of retention parameters.

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Determining hydraulic properties of a loam soil by alternative infiltrometer techniques

et al. 2015

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Testing infiltrometer techniques to determine soil hydraulic properties is necessary for specific soils. For a loam soil, the water retention and hydraulic conductivity predicted by the BEST (Beerkan Estimation of Soil Transfer parameters) procedure of soil hydraulic characterization was compared with data collected by more standard laboratory and field techniques. Six infiltrometer techniques were also compared in terms of saturated soil hydraulic conductivity, Ks. BEST yielded water retention values statistically similar to those obtained in the laboratory and Ks values practically coinciding with those determined in the field with the pressure infiltrometer (PI). The unsaturated soil hydraulic conductivity measured with the tension infiltrometer (TI) was reproduced satisfactorily by BEST only close to saturation. BEST, the PI, one-potential experiments with both the TI and the mini disk infiltrometer (MDI), the simplified falling head (SFH) technique and the bottomless bucket (BB) method yielded statistically similar estimates of Ks, differing at the most by a factor of three. Smaller values were obtained with longer and more soil-disturbing infiltration runs. Any of the tested infiltration techniques appears usable to obtain the order of magnitude of Ks at the field site, but the BEST, BB and PI data appear more appropriate to characterize the soil at some stage during a rainfall event. Additional investigations on both similar and different soils would allow development of more general procedures to apply infiltrometer techniques for soil hydraulic characterization

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Spatial Variability of Soil Water Retention Functions in a Silt Loam Soil

Cited by 45 publications

References 20 publications

Soil Hydraulic Properties

Soil Hydraulic Properties

An alternative deterministic method for the spatial interpolation of water retention parameters

Determining hydraulic properties of a loam soil by alternative infiltrometer techniques

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