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Soil Science Society of America Journal 65:460-462 (2001)
© 2001 Soil Science Society of America

DIVISION S-6-SOIL & WATER MANAGEMENT & CONSERVATION

Comparison of soil water retention at field and laboratory scales

Yakov Pachepskya, Walter J. Rawlsb and Daniel Giménezc

a Bldg. 007 Rm. 104, BARC-WEST, Beltsville, MD 20705
b USDA-ARS Hydrology and Remote Sensing Lab., Beltsville, MD 20705
c Dep. of Environmental Sciences, Rutgers, The State Univ. of New Jersey, New Brunswick, NJ 08901

Corresponding author (ypachep{at}hydrolab.arsusda.gov)


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 Materials and Methods
 Results and Discussion
 REFERENCES
 
Water content and soil water matric potential are measured in different soil volumes and at different spatial scales in the laboratory and in the field. The objective of this work was to use a large database to compare field and laboratory water retention. The database consisted of 135 datasets for soil horizons of various textures. Coarse-textured soils had the average difference between field and laboratory water contents close to zero. On the contrary, fine-textured soils with the sand content <50% had field water contents substantially smaller than the laboratory water contents in the range of water contents from 0.45 to 0.60 cm3 cm-3. A quadratic regression explained 70% of variability in field water contents as computed from the laboratory data. A fractal scaling of the bulk density could contribute to the observed field–lab differences in volumetric water contents for the range of high water contents.


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
Materials and Methods
 Results and Discussion
 REFERENCES
 
SOIL WATER RETENTION DATA is used in simulations of water and chemical transport in soils, in estimations of soil water holding capacity for crop growth simulations and irrigation requirements, and assessment of water sorptivity to predict infiltration rates.

Soil water retention has been determined both in the laboratory and in the field. In the laboratory, values of both volumetric water content {theta}, and soil water matric potential h are measured in the same sample. In field studies, water content and soil water matric potential are measured in different soil volumes and at different spatial scales. Until recently, field determination of soil water retention most often involved measurement of soil water contents with neutron probes, and soil water matric potential with tensiometers. A tensiometer measures soil water potential in a thin soil layer around the ceramic cup, whereas a neutron probe measures soil water content in a spherical soil volume with a diameter of between 25 to 50 cm.

Discrepancies between results of soil water retention measured in the field and in the laboratory have been reported in the literature. The differences between the data from two sources were attributed to the poor depth resolution of the neutron probe (Parkes and Waters, 1980), to the inadequate representation of large pores in the laboratory (Field et al., 1985), to sample disturbance and spatial variability (Field et al., 1985; Shuh et al., 1988), to hysteresis and/or overburden pressure (Shuh et al., 1988), to the overestimation of the soil water matric potential in tensiometer readings (Shein et al., 1993), and to scale effects related to the sample size (Shuh et al., 1988; Bork and Diekrügger, 1990).

The differences in location and scale of water content and pressure potential measurements in the field can result in differences in water retention data obtained in the field and in the laboratory. Differences in location between water content and tensiometer measurements can reflect soil spatial variability, but this effect is expected to result in random differences with zero average value between soil water retention measured in the laboratory and in the field. Differences in scale of measurements may potentially result in a systematic deviation between soil water retention measured in the field and in the laboratory.

Recent applications of fractal geometry to the theory of soil structure show that the soil bulk density may decrease as the scale of measurements (volume of soil) increases (Rieu and Sposito, 1991a; Perfect and Kay, 1995). Data on changes of soil aggregate density with aggregate size support this supposition (Rieu and Sposito, 1991b). This means that, assuming the gravimetric water content is the same, volumetric water contents will decrease with increasing sample size.

The objective of this work was to compare field and laboratory water retention using a sufficiently large database.


   Materials and Methods
TOP
 ABSTRACT
 INTRODUCTION
 Materials and Methods
Results and Discussion
 REFERENCES
 
The Data Set
We used the UNSODA database (Leij et al., 1996) as the main source of data. Data for 113 soil horizons were extracted from the database that had both field and laboratory water retention data reported as "volumetric water content–soil water matric potential" pairs measured during the drying, or drainage, process. Measurements were made by various authors in Alabama, Mississippi, North Dakota, Virginia, Australia, Germany, the Netherlands, New Zealand, Russia, and Ukraine. The data from UNSODA were augmented with 22 published data sets from other sources (Field et al., 1985; Shuh et al., 1988; Bork and Diekrügger, 1990; Shein et al., 1993). The pressure plate method was used to measure water retention in the laboratory in most cases. Laboratory samples were all undisturbed and of different sizes. We used radii of equivalent spheres, RL, that had the same volume as the laboratory sample, to compare these samples. Of all of the samples, 11% had RL between 2.2 and 2.4 cm, 69% had RL between 2.4 and 2.6 cm, 10% had RL = 2.9 cm, and 10% had RL = 3.8 cm. The field water content measurements were made with the neutron probes in all data sets, although in some cases these measurements were augmented with gravimetric sampling. Soil water matric potential was measured with tensiometers in the field. Soil texture in the samples is shown in Fig. 1 . Comparisons of water contents were made in the range of soil water matric potentials where field and laboratory data overlapped. Maximum and minimum matric potentials in overlapping ranges of field and laboratory observations differed among data sets and ranged from -10.7 to 0 kPa and from -85.5 to -1 kPa, with the median values -1.5 and -11.3 kPa, respectively. To make the comparisons, laboratory water contents were interpolated to the levels of soil water matric potential observed in the field. The logarithmic scale was used for soil water matric potentials in the interpolation.



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  		Fig. 1. Texture of soils in this study

 

   Results and Discussion
TOP
 ABSTRACT
 INTRODUCTION
 Materials and Methods
 Results and Discussion
REFERENCES
 
Field and laboratory volumetric water contents are compared in Fig. 2 . Both random and deterministic component can be seen in the differences between field and laboratory water contents. Coarse-textured soils (mostly sands, loamy sands) have appreciable random differences, but they do not show a deterministic bias in the differences. The average difference between field and laboratory water contents is only 0.006 m3 m-3, and the standard error of the difference is 0.0022 m3 m-3. The fine-textured soils with sand content <50% have a random component in the differences between field water and laboratory water contents that is similar to the one in coarse-textured soils. These soils also have definite bias, and field water contents are substantially smaller than the laboratory water contents in the range of water contents from 0.45 to 60 cm3 cm-3. Soils with the intermediate textures with sand content between 50 and 80% have laboratory and field water retention close in the intermediate range of water contents below 0.45 cm3 cm-3, but field water contents become smaller than the laboratory values as the water contents increases.



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  		Fig. 2. Relationship between field and laboratory water contents at the same soil water matric potential: (a) samples with sand content more than 50%, (b) samples with the sand content less than 50%, (c) all samples

 
The graph of the quadratic regression fitted to data is also shown in Fig. 2. The equation of this regression is

(1)

Here 0.05 < {theta}L < 0.065. When used to compute the field water contents from the laboratory data, this equation explains 69.5% of variability.

A fractal scaling of the bulk density may explain the deterministic component of the observed field–lab differences in volumetric water contents in the range of high water contents. Filgueira et al. (1999) used the model of Rieu and Sposito (1991a) and showed that the mass fractal dimension found from the water retention data was applicable to the scaling of the aggregate bulk densities. In the fractal model of soil, the bulk density depends on scale R as (Rieu and Sposito, 1991a)

(2)
where Dm is the mass fractal dimension, 2 < Dm < 3. Therefore, the ratio of bulk densities at field and laboratory scales depends on the ratio of sample radii as

(3)

If the gravimetric water contents are the same for a given soil water matric potential, then the ratio of the volumetric water contents {theta}L/{theta}F is the same as the ratio of bulk densities. Values of Dm found from the laboratory water retention data vary mostly between 2.85 and 2.95 in soils (Rieu and Perrier, 1994; Giménez et al., 1998). The equivalent radii of laboratory samples RL are mostly in the range between 2.2 and 2.9 cm, and the average radius of the field soil neutron probe volume is RF = 15 cm at high water contents. Therefore, we find that the ratio of bulk densities in field and laboratory samples {rho}L/{rho}F may vary mostly between (15/2.9)0.05 and (15/2.2)0.15, that is, between 1.09 and 1.33. This is the range that can be seen in Fig. 2 in ratios {theta}L/{theta}F for the fine-textured soils.

The scaling given in Eq. [3] and the values of Dm used above are derived from the soil water retention data in capillary range and aggregate bulk density data. If this scaling is valid at scales well above the pore and aggregate size, then the scaling is applicable in the range of scales between the laboratory sample size and the neutron probe sensitivity range. That may not necessarily be true, as fractal scaling in soils tends to be valid within a range of scales not exceeding 1 to 1.5 orders of magnitude (Giménez et al., 1998). In coarse-textured soils, water retention curves change their slopes abruptly in the air entry point. Therefore, the scaling with fractal dimension of 2.85 to 2.95 found from water retention curves apparently ceases at larger scales. This may be a reason for a relatively small average difference between field and laboratory water retention in these soils. In fine-textured soils, the air entry point is difficult to define. The abrupt change of the slope of the water retention curve does not occur, and the scaling found in the capillary range may extend to the range of scales that includes the size of the field neutron probe sensitivity volume.

The bulk density scaling as a hypothetical explanation of the differences between field and laboratory retention data does not dispute the importance of other field factors contributing to these differences, such as spatial variability, overburden pressure, hysteresis, or possible nonequilibrium. These factors have probably manifested themselves, to various extents, in each of the studies that provided data for this work. The regression equation (Eq. [1]) simulates the average lab–field deviations that may be expected as a result of coupled field and laboratory measurements, rather than an outcome of a specific experiment.

The observed differences in field and laboratory water retention may have important consequences for estimating soil hydraulic properties from readily available soil data. Pedotransfer functions are built from the laboratory water retention data. Estimates of the available water capacity in soil horizons obtained from such pedotransfer functions may be too high. A correction needs to be applied to these estimates. Equation [1] gives the first approximation for such correction. Similarly, the water content at field capacity estimated from the laboratory data may be too high. This will result in too low effective porosity values defined as differences between the total porosity and water content at 0.03 MPa soil water matric potential, and therefore, will result in low saturated conductivity values computed from the effective porosity (Rawls et al., 1992). Data in Fig. 2 suggest that field water retention curves of fine-textured soils are, in general, steeper than the laboratory water retention curves. Therefore, the differential water capacity defined as d{theta}/dh is higher from field data than from laboratory data in the range of low soil water matric potentials. This should result in slower infiltration predictions based on the sorptivity from the laboratory data. These and similar observations indicate the need to pay more attention to the effects of scale on soil hydraulic properties and the need to include such and effects in pedotransfer functions.


   ACKNOWLEDGMENTS
 
We wish to dedicate this note to the memory of late Michel Rieu whose pioneering research of scaling in soil structure paved the way for the work of many scientists who followed his path. Support from the NASA Land Surface Hydrology program is appreciated.

Received for publication April 6, 2000.


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 Materials and Methods
 Results and Discussion
 REFERENCES
 




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This Article
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