Soil Survey Interpretations from Water Retention Data: I. Development and Validationof a Water Retention Model1

R. A. McBRIDE AND E. E. MACKINTOSH2

ABSTRACTThe prediction of spatial and temporal variations in the soil water

regime provides the basis for a proposed soil survey interpretivesystem. A water retention model estimates the boundary desorptioncurve from saturation to pF 4.2 for mineral soils in situ using limitedsoil physical data (standard error of estimate <2.2% g g"1). Thetotal porosity (structural parameter) and clay content (adsorptiveparameter) define the position of the moisture characteristic in log-arithmic coordinates and the silt content its configuration. Organicmatter affects the structural parameter by reducing both the dry bulkand particle densities but only significantly influences the adsorptiveparameter at organic matter contents of 5% or greater. Model val-idation shows that the state and quantity of water retained by fieldsoils near equilibrium is dependent on the position of the phreaticsurface. Under field conditions, the t(0) relationship establishes aneffective equilibrium midway between the predicted wetting and dryingcurves of the hysteresis loop.

Additional Index Words: land evaluation, soil moisture charac-teristic, phreatic surface.

McBride, R.A., and E.E. Mackintosh. 1984. Soil survey interpret-ations from water retention data: I. Development and validation ofa water retention model. Soil Sci. Soc. Am. J. 48:1338-1343.

THE FORMULATION of rural land use policies inCanada is becoming increasingly more complex

and, hence, more dependent on systematic informa-tion synthesizing and evaluation techniques (2, 28).However, the development of soil survey interpretiveprocedures based on a systems approach has not keptpace with the rapid evolution of land evaluationmethodologies and the expansion of their land qual-ity/performance data requirements. The soil water re-gime is a major determinant and integrator of soilsuitability, both as a medium for plant growth and asan engineering material. Thus, soil water retentionproperties offer a common conceptual ground for suchsystematic agronomic and engineering interpretations.The objective of this study was to develop and vali-date an empirical water retention model which is ap-plicable to Ontario soils and requires only limited in-put data.

MATERIALS AND METHODSGeneral Form of the Model

The estimation of soil moisture characteristics from othersoil physical properties has been frequently proposed as analternative to their routine measurement in soil testing lab-oratories or to compiling desorption data from existing soilinformation files (5, 31). This has led to the emergence ofthree divergent modelling approaches:

1) Fitting various types of functions to the moisture char-acteristics of soils. Parabolic and sigmoidal functions(26, 32), semilogarithmic line segments (16), and ex-

1 Contribution from Dep. of Land Resource Science, Univ. ofGuelph, Guelph, Ontario, NIG 2W1. Received 6 July 1983. Ap-proved 10 May 1984.2 Graduate Research Assistant and Associate Professor, respec-tively.

ponential or power functions (3, 7) have been used.Many attempts have been made to refine the coeffi-cients of the latter power function with data on par-ticle-size distribution (4, 8, 21), measured volumetricmoisture contents at air-entry and at pF 4.18 (24), andsoil organic matter content or sampling depth (21).

2) Development of the relationship between pore-size dis-tribution of a porous medium and its water retentioncharacteristics (6, 19, 33).

3) The statistical regression approach for estimation ofthe soil moisture content at predetermined pressurepotentials from textural composition and other soilproperties (11, 12). Most effort has been directed at theestimation of the upper and lower limits of plant-avail-able soil moisture from basic physical properties (5,20, 21, 22).

The present soil water retention model emphasizes thefirst of these modelling approaches and is fashioned afterthe power functions of Brooks and Corey (3) and Gardneret al. (7). In its simplest form, this model constructs a linearmoisture characteristic in logarithmic coordinates. For therange —fa's* — 1//> — 1.5 MPa, this can be expressed math-ematically as:

i - (« + (a [1]where

— t/'j = pressure potential at the primary inflection(kPa)

— ̂ = pressure potential for which 6m is to be pre-dicted (kPa)

0mi = gravimetric moisture content at the primaryinflection (% g g"1)

0mi s = gravimetric moisture content at a pressurepotential of -1.5 MPa (% g g~')

0m = predicted gravimetric moisture content at apressure potential of — ̂ (% g g"1)

a = slope = (Iog100mi.5 ~ Iog100mi)/(3.176 -Icgio^i)

The only conditions on these input variables are that 0^,0ml.5, and vt-i > 0 and 0^ > 0ml.5.

For most mineral soils, 8m3 can be estimated from the insitu dry bulk density (pb) in the relation (8):

= [(1 -W2.65))/pb].100 [2]where 0ms = gravimetric moisture content at saturation (%g-g~')> and ̂ = dry bulk density (g cm~3). Factors of 0.90for sands and loamy sands and 0.95 for all other texturalclasses are applied to 0ms to estimate 0,̂ , the moisture con-tent at the primary inflection (4, 24). Coarse-textured soilsare assigned lower factors to reflect their lower capillary po-rosity. For the range 0 ̂ — 4* ^ ~ &, #m is assumed todecrease linearly from 0ms to 8^ in linear coordinates whichimplies that the air-entry pressure potential is about —0.1kPa for fully saturated soils. White et al. (33) observed lin-earity in this "boundary effect zone" of the desaturationcurves of consolidated porous material cores. This effect wasattributed to the drainage of the larger boundary voids atthe exterior of the core even though the pressure potentialwas insufficient to force the air-water interface past any poreconstriction. This assumption should also hold for moststructured soils and unconsolidated materials in situ wherethe largest macropore(s) will undoubtedly have an effectiveradius of at least 1.5 mm, e.g., structural or bio-pores.

1338

MCBRIDE & MACKINTOSH: SOIL SURVEY INTERPRETATIONS FROM WATER RETENTION DATA: I. 1339

Calibration of the ModelAs part of a land productivity field program during 1978

in eastern and southwestern Ontario (18), 32 soil profilesrepresenting 10 different soil series were characterized fromsoil pits. Additional data were collected in 1980 for 63 soilprofiles across central and southeastern Ontario. Table 1outlines the taxonomic classification of these soil profiles atthe subgroup level (29). Particle-size distribution (pipette/dry sieve sand fractionation) and organic matter content(modified Walkley-Black wet oxidation method) were de-termined from bulk samples taken of each soil horizon. Apressure plate apparatus was used to measure the —1.5 MPamoisture percentage by weight (unreplicated) of each soilsample. The samples had been previously air-dried andpassed through a no. 10 mesh (2 mm) sieve.

To expedite the collection of undisturbed desorption cores,a portable, split-sleeve coring device was designed whichenabled intact columns (4.7 cm diam by 100 cm long) to betaken of entire soil profiles. A minimum of two and a max-imum of four soil cores (4.7 cm diam by 3.0 cm long) weretaken from each horizon thicker than 6 cm, with the finalnumber of replicates depending on the overall thickness ofthe horizon. Pressure plate desorptions were performed oneach of the undisturbed soil cores at pressure potentials of— 5, —10, and —33 kPa. The mean gravimetric moisturecontent of the replicates was calculated for each pressurepotential by horizon. The dry bulk density of each horizonat field capacity (—33 kPa) was determined by oven-dryingthe cores at 105°C for 48 h. The laboratory procedures fol-lowed are those outlined by McKeague (15).

The General Linear Models (GLM) procedure for multi-ple stepwise regression (27) was used for much of the dataanalysis.

Validation of the ModelField—In 1981, seven sites were established to study the

response of unsaturated moisture profiles of texturally dis-parate soils to fluctuations in the regional groundwater table.This was accomplished by installing at each site a ground-water table observation well and a neutron probe access tube,each up to 3 m deep and separated by a distance of ap-proximately 1 m. The sites were situated in fence rows undershort grass cover. Moisture contents were measured in 15-cm depth increments with a Troxler neutron thermalizationgauge (model 1257) with the uppermost measurement at 23cm below the soil surface, the depth of resolution (minimumaccurate depth) of this device. The groundwater table depthwas determined to the nearest centimeter from the obser-vation well. This procedure was repeated periodically(monthly) from April to November 1981/82, allowing aminimum of 4 d for internal drainage to take place aftersignificant rainfall events. The soils at each site were char-acterized in terms of dry bulk density at the field moisturecontent and particle-size distribution (15).

Laboratory—By assembling the coring device with anacrylic tube rather than split sleeves, an intact, undisturbedcolumn of a complete soil profile up to 1 m long could beobtained. Profiles of three soil series were sampled in thismanner. The encased soil columns were allowed to saturatein a cylindrical tank filled with de-aired water and were thenmounted on a hanging water column apparatus. By adjust-ing the position of the burette (water reservoir) relative tothe base of the column, the soil could be subjected to dif-ferent negative pressure potentials. A sequence of four neg-ative pressure potentials was applied to the base of each soilcolumn in decrements of 5 kPa, from —5 to —20 kPa. Itwas assumed that static equilibrium was reached when therewas no measurable increase in the total volume of waterextracted for a period of at least 1 d. This period variedfrom 2 to 3 d for fine sands to 6 to 8 d for medium-textured

Table 1—Subgroup classification of sample sites, t

Subgroup

Aquic HapludalfsAquic Arenic HapludalfsArenic HapludalfsTypic HapludalfsTypic FluvaquentsMollic HaplaqueptsTypic DystrachreptsAquic EutrachreptsArenic EutrachreptsTypic Eutrachrepts

Number of soilprofiles sampled

162

11421

113225

Number of soilhorizons sampled

557

40168

23110116

17

t Soil Survey Staff, 1975.

soils. The volume of water extracted for each desorption wasrecorded. After the final desorption, the soil column wasremoved from the tube in 10-cm lengths and each segmentwas oven-dried at 105°C for 48 h. Dry bulk densities andgravimetric moisture contents were determined (15) and avolumetric soil moisture profile was constructed.

RESULTS AND DISCUSSIONModel Calibration

The relationship between the measured —1.5 MPamoisture percentages of 347 Ontario soil horizons andtheir total clay (<2 ^m) contents (Fig. 1) was used toestimate 0rol 5 in Eq. [1]. The difference in the config-uration of this curve from the linear (1), quadratic(22), and exponential (exponent > 1.0) (20) relation-ships reported elsewhere is attributed to the predom-inantly illite-chlorite mineralogy of the <2-/mi soilfraction. The deviation away from the expected linearrelationship is thought to be due to the influence ofvarious soil fabric assemblages on water adsorption atlow pressure potentials. Organic matter contents inexcess of about 5% by weight were found to increasethe measured 0ml.5 values substantially. Linear in-creases in the —1.5 MPa moisture percentage withorganic matter content have been reported by Peter-sen et al. (22) within individual textural classes andby Gupta et al. (10) for sandy soils. While inclusionof a cubed organic matter term in the stepwise regres-sion was significant at a = 0.05, there were generallytoo few Ap horizon samples with organic matter con-

0.

ffl 6

<D

em1.5 = 1.338* (%clay) ••'r = 0.971

standard error of estimate= 1.33% moisture

30 40

Clay (% by wt)

50 70

Fig. 1—Plot of the gravimetric moisture content at a pressure po-tential of —1.5 MPa vs. clay content of Ontario soils.

1340 SOIL SCI. SOC. AM. J., VOL. 48, 1984

1.50

S§M.OO

0.00

i = 0.065 • ((VoSilt)2*/') + (0.01//')-fi = pressure potential at the

primary inflection (kPa)-/" = pressure potential for which

6m is being predicted (MPa

0.00 1.00 2.00 3.00 4.00

Fig. 2— Plots of estimated moisture characteristics for sand, silt, and loam soils.

tents of this magnitude to conclusively isolate this ef-fect.

With respect to the other definitive model variable,the pressure potential at the primary inflection (&), itwas determined that a unique value did not providethe best fit of the data for a given soil using Eq. [1].Rather, & varied with the pressure potential for whichthe estimate of 0m was to be made. In effect, this meansthat soil moisture characteristics are not best repre-sented by a linear plot in logarithmic coordinates. Thishas been corroborated by Russell and Mickle (25) whoobserved curvature between pF 2 and 4 in the mois-ture characteristics of sandy loams and silt loams plot-ted on a log-log scale. The regression equation arrivedupon for i//j has both silt content and pressure potentialas variables, thereby forcing the plot of the moisturecharacteristic to deviate from the linear projection (Fig.2). While it was thought that the relative proportionsof fine and coarse sand separates would also have somebearing on the configuration of the water retentioncurve in the high pressure potential range, regression

36

30

24

®•o 18

12

confidence interval about bc:-0.0260 <jB0 S0.7910(70% probability level)

confidence interval about b,:0.9945 <p, < 1.0388(70% probability level)

6 30 3612 18 24Estimated ©m (%)

Fig. 3 — Measured vs. estimated moisture contents at a pressure po-tential of -33 kPa.

analysis of this desorption data yielded no significantparametric relationship.

As an illustration, Fig. 2 shows the estimated waterretention curves for sand, silt, and loam soils, all witha dry bulk density of 1.4 g cm ~3 and a clay content of10%, i.e., predicted 0ml 5 is 6.7%. The significance ofsilt content in defining the configuration of the curvein the higher pressure potential range is not surprisingsince the silt fraction is the major determinant of theamount of plant-available soil water (1, 22). More de-tailed fractionation has shown that the 5-to 20-jumseparate has the greatest influence on both the —33kPa moisture percentage and the plant-available mois-ture-holding capacity of soils (23). The pressure po-tential at the intercept of the plotted moisture char-acteristic and the (0m/0mi) = 1 line is the estimatedvalue of — \!/i. In Fig. 2, the primary inflection occursat —3.1 kPa for the sand, —3.3 kPa for the loam, and—4.6 kPa for the silt. Between saturation and the pri-mary inflection, the sand releases 3.37% of its dryweight in moisture whereas the loam and silt releaseonly 1.68%.

Incorporating the two statistical expressions pre-sented in Fig. 1 and 2 into Eq. [1], the correspondencebetween the measured and estimated moisture con-tents at each of the three pressure potentials (—5, —10,— 3.3 kPa) was assessed, and the results for —3.3 kPaare presented in Fig. 3. In all cases, the coefficientvalues of /80 = 0 and #1 = 1.0 fall within the confi-dence limits calculated at a = 0.02. However, in mostinstances, these coefficient values are still within themuch narrower intervals calculated for lower proba-bilities, e.g., a = 0.30. This further increases the con-fidence that &Q and 0t do not differ from 0 and 1.0,respectively. Despite this apparent correspondencewith the 1:1 line, significant overpredictions are prev-alent in the sandy textural range, particularly at veryhigh pressure potentials. The standard errors of esti-mate ranged from 1.83% to 2.20% moisture by weightfor the three pressure potentials. This is well withinthe level of accuracy required for the intended appli-cations.

Model ValidationLaboratory—Validation of the water retention model

was achieved with the use of data from two indepen-

MCBRIDE & MACKINTOSH: SOIL SURVEY INTERPRETATIONS FROM WATER RETENTION DATA: I. 1341

Waterloofine sandy loam

Table 2—Results from the desorption of three soil columns.

Soil series

Hillsburgfine sand

Length(volume) ofsoil column

92cm(1596 cm')

Range of pressurepotential throughthe soil column

cm of water-50 to -142

-100 to -192-150 to -242-200 to -292

Volume of water retainedat equilibrium

Predicted

355.0293.5262.4242.8

Measured

300.9252.9243.9239.9

Difference between predicted andmeasured soil moisture profiles

Volume

+ 54.1+ 40.6+ 18.5+ 2.9

»v

+ 3.39+ 2.54+ 1.16+0.18

»m

+ 2.26+ 1.69+0.77+ 0.12

Mean92cm

(1596 cm')-50 to-142

-100 to-192-150 to-242-200 to-292

375.8309.3276.9256.9

445.4333.4296.4281.4

-69.6-24.1-19.5-24.5

Mean

+ 1.82-4.36-1.51-1.22-1.54-2.16

+ 1.21-2.93-1.01-0.82-1.03-1.45

Brantfordsilt loam

99cm(1718 cm'|

-50 to -149-100 to -199-150 to -249-200 to -299

553.1528.4516.2508.0

583.1576.1573.1572.1

-30.0-47.7-56.9-64.0

Mean

-1.75-2.78-3.31-3.73-2.89

-1.12-1.78-2.12-2.39-1.85

dent sources. First, it was determined if the model,which was based on desorption data from 3 cm longcores, could be used to approximate the ^(6) relation-ship from complete soil profiles. This was accom-plished by saturating and draining intact soil columnsup to 1 m long via a hanging water column.

Results were obtained for three soil series belongingto the Typic Hapludalfs subgroup (Table 2). For therange of pressure potentials from —50 to —299 cm ofwater, the mean errors of estimation varied from only1.21% to 1.85% moisture by weight for the soil col-umns. With the exception of the Brantford silt loam,there was a clear tendency toward better predictionsat lower pressure potentials. Since the silt loam col-umn released only 11 cm3 of water at pressure poten-tials between — 50 and —299 cm of water over a 28-d period, the point at which the column reached evena "quasi-equilibrium" state could not be identified.The presence of 1 to 2 cm thick silty clay varves inthe subsoil would certainly have contributed to theslow drainage rate. The column length was also a lim-iting factor, for Topp and Zebchuk (30) showed thatequilibrium was reached in smaller sand and clay cores(7.6 cm diam by 7.6 cm long) only after 200 h forpressure potentials ranging to — 50 kPa. Therefore, itis believed that a large part of the underprediction of6m in the silt loam column was due to the nonattain-ment of static equilibrium. The overprediction of 0mfor sands in this pressure potential range appears tobe an innate weakness of this model and was, there-fore, anticipated for the Hillsburg fine sand.

Field Conditions—With the apparent successachieved in applying the model to complete soil pro-files in the laboratory, the validation was extended tofield conditions. Volumetric soil moisture above aphreatic surface was monitored at seven site locationsthroughout the 1981/82 field seasons. Results for twosites from 1982 are presented graphically in Fig. 4.Each composite figure displays the estimated bound-ary curves of the hysteresis loop and the measuredsoil moisture profile to the depth of the groundwatertable. The wetting curve is estimated from the dryingcurve using the universal hysteresis expression for-mulated by Mualem (19).

(cm)-0

-50

-100-

-150

(cm)

-100

-200

-300

APRIL 16 AUGUST 20

A - Predicted Absorption CurveD - Predicted Desorption CurveM - Measured Soil Moisture Profile

200v (

APRIL 16

A - Predicted Absorption CurveD - Predicted Desorption CurveM - Measured Soil Moisture Profile

20ev (%)

40 0 40

Fig. 4—Measured and predicted soil moisture profiles for 1982:(a) site 2 (b) site 4.

All of the sites showed remarkably little change intheir moisture profiles from April through October,with most variation occurring in the surface 30 to 40cm where the processes of evapotranspiration andpostinfiltration redistribution of precipitation (inter-nal drainage) occur most actively. This would suggestthat the vadose water below this surface zone is in aneffective state of equilibrium with the phreatic surfacemuch of the time. Groenevelt and Bolt (9) have ar-

1342 SOIL SCI. SOC. AM. J., VOL. 48, 1984

gued that this "static" equilibrium curve probably liesbetween the two "metastable" boundary curves. Forthis reason, the measured moisture profile has beenplotted alongside both the estimated wetting and dryingcurves. The predicted moisture profiles have been gen-erated in 1-cm depth increments whereas the neutrongauge point measurements represent the mean mois-ture content within a sphere of influence of about 18to 40 cm in diameter, depending on the soil wetness.

Site 2 was situated within a slightly depressionalarea of a gently undulating, deltaic sand plain. Thesoil profile was a homogeneous fine sand with littleevidence of profile development as a result of aeolianreworking. In Fig. 4a, the measured soil moisture pro-files show a reasonably close correspondence with thepredicted drying curves above the 40-cm and belowthe 100-cm depths, with the exception of the 20 Au-gust profile where the surface soil was desiccated byevapotranspirational moisture loss. This observationwas attributed to the surface 30 to 40 cm of soil reach-ing a near-saturated condition during the spring runoffperiod and the groundwater table reaching a 2-yr peakof 117 cm on 16 April 1982. The intermediate zone(40 to 100-cm depth) was never fully recharged at anytime during the year and, therefore, equilibrated nearerthe moisture contents found on the boundary wettingcurve.

The soil profile at site 4 was characterized by a sharpdiscontinuity in texture between the predominantlyfine sandy loam solum and the fine sand subsoil atthe 120-cm depth (Fig. 4b). This, in conjunction withthe deep and relatively stable level of the phreatic sur-face, provided the conditions necessary to examinethe effect of underlying coarser-textured strata on soilwater retention. Miller and Bunger (17) did so on ar-tificially-constructed, stratified soils and found that asandy loam soil overlying a clean gravel or sand bedretained much more moisture than a uniform sandyloam soil. Furthermore, the soil moisture content in-creased with proximity to the textural interface. Usingthe moisture profile measured on 7 June 1982 (Fig.4b) as an example, the moisture content measured im-mediately above the textural interface was 27.7% byvolume. This corresponds to a pressure potential of— 7.2 kPa on the predicted drying curve and — 3.9 kPaon the predicted wetting curve, even though this pointis 125 cm above the phreatic surface. Therefore, thefine sandy loam above the interface must reach a pres-sure potential of between —3.9 and —7.2 kPa beforethere is appreciable water migration into the muchlarger pores of the underlying fine sand. These valuescompare favorably to the —3.6 kPa pressure potentialmeasured by Miller and Bunger (17) in a sandy loamsoil at the interface of a sand lens located 122 cmbelow the surface. Despite the low water transmissi-bility rates across the textural interface, the upper soilmoisture profile had effectively equilibrated with thedescending groundwater table by 20 Aug. 1982.

Below the 120-cm level (Fig. 4b), the measuredmoisture profiles follow the predicted wetting curvesclosely to about the 230-cm depth. In those instanceswhere the recorded groundwater table lies below the245-cm level (2-yr peak), the drying curve is under-standably a better predictor of the moisture content

below this depth. Taking into account the sizeable zoneof influence of the neutron probe, the gradual shiftfrom the wetting to the drying curve between 230 and250 cm would be anticipated.

Data from the remaining five sites over the 2 yr ofobservation indicate that there is a good correspond-ence between the predicted and measured moistureprofiles, particularly below the zone of most activemoisture loss and redistribution at the surface.

SUMMARY AND CONCLUSIONSFrom the results presented here, it can be concluded

that the segment of the main desorption curve fromsaturation to a pressure potential of —1.5 MPa can beadequately predicted (standard error of estimate<2.2% g g~') for most mineral soils found in situ inOntario using limited soil physical data. The total soilporosity (structural parameter) and clay content (ad-sorptive parameter) define the position of the mois-ture characteristic in logarithmic coordinates and thesilt content its configuration. In conjunction with theuniversal hysteresis expression formulated by Mu-alem (19), the complete boundary hysteresis loop canbe estimated. If the water history of a field soil is notknown, i.e., maximum and minimum annual ground-water table depths, it can be assumed for soil interpre-tive purposes that the i/<0) function lies midway be-tween the predicted wetting and drying curves at staticequilibrium.

Additional input data which may improve the waterretention estimates are the organic matter content andeither the total soil porosity or the specific gravity(particle density) of the soil. Organic matter affects thestructural parameter by reducing both the dry bulkand particle densities but only significantly influencesthe adsorptive parameter at organic matter contentsof 5% or greater.

Development of a water retention model based onlimited data inputs provides an effective tool for ex-tending the use and interpretation of soil inventoriesin land evaluation. The current model has been ap-plied to establishing class limits and crop performanceindices for soil capability classes, with application tothe soil erosion-soil productivity relationship (14), andthe prediction of soil engineering properties (13).

ACKNOWLEDGMENTSWe would like to thank Drs. P.M. Groenevelt and M.H.

Miller, Dep. of Land Resource Science, for their commentsand suggestions throughout the course of this work and fortheir review of the manuscript. We are indebted to Dr. L. J.Evans, Dep. of Land Resource Science, for classifying oursites according to the Soil Taxonomy.

MCBRIDE & MACKINTOSH: SOIL SURVEY INTERPRETATIONS FROM WATER RETENTION DATA: II. 1343

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