Soil Water Characteristic Estimates by Texture and Organic Matter for
Hydrologic Solutions
K. E. Saxton and W. J. Rawls
ABSTRACT
Hydrologic analyses often involve the evaluation of soil water in-
filtration, conductivity, storage, and plant-water relationships. To de-
fine the hydrologic soil water effects requires estimating soil water
characteristics for water potential and hydraulic conductivity using soil
variables such as texture, organic matter (OM), and structure. Field or
laboratory measurements are difficult, costly, and often impractical for
many hydrologic analyses. Statistical correlations between soil texture,
soil water potential, and hydraulic conductivity can provide estimates
sufficiently accurate for many analyses and decisions. This study de-
veloped new soil water characteristic equations from the currently
available USDA soil database using only the readily available vari-
ables of soil texture and OM. These equations are similar to those
previously reported by Saxton et al. but include more variables and
application range. They were combined with previously reported rela-
tionships for tensions and conductivities and the effects of density,
gravel, and salinity to form a comprehensive predictive system of soil
water characteristics for agricultural water management and hydro-
logic analyses. Verification was performed using independent data
sets for a wide range of soil textures. The predictive system was pro-
grammed for a graphical computerized model to provide easy appli-
cation and rapid solutions and is available at http://hydrolab.arsusda.
gov/soilwater/Index.htm.
H
YDROLOGIC ANALYSES are commonly achieved by
computer simulation of individual processes, then
combined into more comprehensive results and ana-
lyzed by statistics or time series. This contrasts with
earlier methodology, which relied heavily on statistical
analyses of measured hydrologic data. While modern
methods do not ignore available data, simulation of the
individual processes and recombination into landscape
and watershed responses often reveals additional details
beyond that previously available, particularly where
data are limited or not available.
A significant percentage of most precipitation infil-
trates to become stored soil water, which is either re-
turned to the atmosphere by plant transpiration and
evaporation or is conducted to lower levels and ground
water. As a result, modern simulation and analyses of
hydrologic processes relies heavily on appropriate de-
scriptions of the soil water holding and transmission char-
acteristics of the soil profile.
Soil science research has developed an extensive un-
derstanding of soil water and its variability with soil
characteristics (Van Genuchten and Leij, 1992). Appli-
cation of this knowledge is imperative for hydro-
logic simulation within natural landscapes. However,
hydrologists often do not have the capability or time to
perform field or laboratory determinations. Estimated
values can be determined from local soil maps and
published water retention and saturated conductivity
estimates, but these methods often do not provide
sufficient range or accuracy for computerized hydro-
logic analyses.
The texture based method reported by Saxton et al.
(1986), largely based on the data set and analyses of
Rawls et al. (1982), has been successfully applied to a
wide variety of analyses, particularly those of agricul-
tural hydrology and water management, for example,
SPAW model (Saxton and Willey, 1999, 2004, 2006).
Other methods have provided similar results but with
limited versatility (Williams et al., 1992; Rawls et al.,
1992; Stolte et al., 1994). Recent results of pedotrans-
fer functions (Pachepsky and Rawls, 2005) are an exam-
ple of modern equations that cannot be readily applied
because the input requirements are beyond that cus-
tomarily available for hydrologic analyses. Currently
available estimating methods have proven difficult to
assemble and apply over a broad range of soil types and
moisture regimes. Therefore, the objectives of this study
were to (1) update the Saxton et al. (1986) soil water ten-
sion equations with new equations derived from a large
USDA soils database using only commonly available
variables of soil texture and OM, (2) incorporate the
improved conductivity equation of Rawls et al. (1998),
and (3) combine these with the effects of bulk density,
gravel, and salinity to provide a broadly applicable pre-
dictive system.
LITERATURE REVIEW
Estimating soil water hydraulic characteristics from
readily available physical parameters has been a long-
term goal of soil physicists and engineers. Several equa-
tions commonly applied to hydrologic analyses were
summarized by Rawls et al. (1992; Table 5.1.1) and Hillel
(1998). These included those developed by Campbell
(1974), Brooks and Corey (1964), Van Genuchten (1980)
and others. Many early trials were sufficiently success-
ful with limited data sets to suggest that there were sig-
nificant underlying relationships between soil water
characteristics and parameters such as soil textur e
(Gupta and Larson, 1979; Arya and Paris, 1981; Williams
et al., 1983; Ahuja et al., 1985, 1999; Rawls et al., 1998;
Gijsman et al., 2002). More recent studies have eval-
uated additional variables and relationships (Vereecken
et al., 1989; Van Genuchten and Leij, 1992; Pachepsky
and Rawls, 2005).
K.E. Saxton, Saxton Engineering and Associates, 1250 SW Campus
View, Pullman WA 99163; W.J. Rawls, USDA-ARS Hydrology and
Remote Sensing Lab, Bldg. 007, Rm. 104, BARC-W, Beltsville, MD
20705. Received 8 Apr. 2005. *Corresponding author (wrawls@
hydrolab.arsusda.gov).
Published in Soil Sci. Soc. Am. J. 70:1569–1578 (2006).
Soil & Water Management & Conservation, Soil Physics
doi:10.2136/sssaj2005.0117
ª Soil Science Society of America
677 S. Segoe Rd., Madison, WI 53711 USA
Reproduced from Soil Science Society of America Journal. Published by Soil Science Society of America. All copyrights reserved.
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