a multivariate framework for interpreting the effects of soil properties, soil management and...

Review

A multivariate framework for interpreting the effects of soilproperties, soil management and landuse on water repellency

R.J. Harpera,* , I. McKissockb, R.J. Gilkesb, D.J. Carterc, P.S. Blackwelld

aCALM Science Division, Department of Conservation and Land Management, Locked Mail Bag 104, Bentley Delivery Centre,Western Australia 6983, Australia

bSoil Science and Plant Nutrition, Faculty of Agriculture, The University of Western Australia, Nedlands, Western Australia 6907, AustraliacAgriculture WA, 444 Albany Highway, Albany, Western Australia 6330, Australia

dAgriculture WA, 285 Marine Terrace, Geraldton, Western Australia 6530, Australia

Received 22 February 1999; accepted 30 July 1999

Abstract

This paper reviews recent progress in relating the incidence of water repellency to other soil attributes, relating the severity ofwater repellency to different soil management and landuses and determining the value of soil survey in predicting the risk ofwater repellency. Data sets of soils from south-western Australia are used for this analysis.

The relationship between water repellency and other soil attributes such as clay and organic matter contents has been found tobe multivariate in nature, with a general form:

Water repellency< a Organic Matterb=Clayc

wherea, b andc are constants. Multiple regressions, which use a variety of attributes related to soil organic matter and soilsurface area (e.g. clay, silt, amorphous iron contents), can explain up to 63% of the variation in water repellency. Waterrepellency increases in severity with increasing organic carbon content or decreasing soil surface area and vice versa. Thisrelationship explains the poor or non-existent bivariate relationships between various soil attributes and water repellencyreported in several studies and allows the re-interpretation of studies into the effects of liming, zero-till and different rotationlengths on water repellency as each affect soil organic carbon (OC) content. It is also consistent with observations that waterrepellency is more prevalent on sandy soils and reported reductions in water repellency following applications of clay and fineinorganic materials. It similarly explains the occurrence of water repellency on soils with.5% clay; accumulation of sufficientamounts of OC can induce water repellency in any soil.

Soil management and landuse affect water repellency. Water repellency is less severe in soils under crops compared topastures and this has been considered as being caused by differences in organic matter composition. This is re-interpreted asbeing due to differences in organic matter amount, as cultivation mineralises and dilutes soil organic matter in the topsoil. Waterrepellency is also a feature of soils under natural vegetation (Eucalyptus, Banksiaspp.) and may be more severe than that foragricultural soils. Increments of organic matter from natural vegetation can induce water repellency to a greater extent thanequivalent amounts of organic matter from agricultural species. Thus, water repellency can be considered as a natural feature ofsoils, rather than a form of land degradation due to farming. Comparisons between the water repellency associated withdifferent soil management or landuses are problematic due to differences in not only OC content and composition but alsoother soil properties such as surface area, due to the spatial separation of the areas compared.

Journal of Hydrology 231–232 (2000) 371–383

0022-1694/00/$ - see front matterq 2000 Elsevier Science B.V. All rights reserved.PII: S0022-1694(00)00209-2

www.elsevier.com/locate/jhydrol

* Corresponding author. Fax:161-8-9334-0327.E-mail address:[email protected] (R.J. Harper).

Given the underlying relationship between clay content and water repellency, field texture data from soil surveys can be usedto predict the risk of water repellency developing, this providing a basis for optimum management practice. The degree towhich this water repellency develops will be dependent on management practices and their effects on soil organic mattercontent. Quite costly, but profitable, ameliorative management (e.g. clay application) can thus be applied to sites whererequired, rather than to large areas on a non-specific basis.q 2000 Elsevier Science B.V. All rights reserved.

Keywords: Organic carbon; Land management

1. Introduction

Water repellency is widespread in the soils ofsouthern Australia (Oades, 1992; Blackwell, 1993).Accurate regional assessments of the area affectedby water repellency and its severity are not available,and estimates are often based on the assumption thatwater repellency is a feature of all sandy surfaced soils(Select Committee into Land Conservation, 1990).Estimates of the area affected across southern Austra-lia vary between two (Oades, 1992) and five millionhectares (Blackwell, 1993).

Although small areas of south-western Australiahave been developed for irrigated agriculture, viticul-ture and horticulture, much of the farming of this areais reliant on annual rainfall (Squires and Tow, 1991).These dryland farming systems involve rotations ofwheat (Triticum aestivum), barley (Hordeum vulgare)or grain-legume (Lupinus angustifolius) crops andannual subterranean clover (Trifolium subterraneum)blue-lupin (Lupinus consentinii) or perennial lucerne(Medicago sativa) based pastures. The soils in thisregion are often sandy textured with the clay miner-alogy being dominated by kaolin and iron and alumi-nium oxides (Robson and Gilkes, 1981).

South-western Australia has a Mediterranean envir-onment with a strongly seasonal rainfall distribution.Farming occurs in areas with.300 mm annual rain-fall. Most of this rainfall occurs in the cooler months(April to October), with little reliable rainfall in theremainder of the year (Rovira, 1992). The soil surfaceconsequently dries each summer, with the problemsassociated with water repellency occurring when rainfalls on dry soils. Although initial rainfall mostlyoccurs as a discrete “break of season”, at thecommencement of the relatively reliable winter rain-fall pattern, it can also occur with less frequentsummer rain storms. Intense falls of rain on waterrepellent soils can cause significant water erosion(McGhie and Posner, 1980; Blackwell, 1993).

Major problems associated with water repellencyinclude the poor or staggered germination of sowncrop seeds and regenerating pastures, with poor resul-tant production (Bond, 1972). Overcoming waterrepellency by adding clay has increased the yieldsof barley from 1.7 to 3.4 t/ha, and of lupins from 1to 2 t/ha, two years after application by improving thegermination and survival of seeds (Carter and Hether-ington, 1994). Other problems associated with waterrepellency include poor weed control due to unevengermination of weed seeds (Blackwell, 1993) and thedecreased availability of nutrients from dry soils(Moore and Blackwell, 1998).

Recent research on water repellency in southernAustralia has included the following themes:

• Characterising the organic fractions of soils(Ma’shum et al., 1988; Franco et al., 1995).

• Researching ameliorants including clay (Ward andOades, 1993; Richmond et al., 1996), lime (Wallisand Horne, 1992) and wetting agents (Summers,1987; Crabtree and Gilkes, 1999).

• Attempts to find biological solutions includingmicrobial consumption of waxes (Michelsen andFranco, 1996).

• Modified cultivation techniques such as furrowsowing (Blackwell, 1993; Blackwell et al., 1994b).

• Statistical approaches relating the incidence ofwater repellency to other soil attributes, differentlanduses and soil survey data (Harper and Gilkes,1994; McKissock et al., 1998).

These statistical approaches have been aimed atdeveloping predictive models for water repellency,so that treatments such as clay and wetting agentscan be applied where required rather than by routineprescription. This paper describes recent work insouth-western Australia which: (a) relates the inci-dence of water repellency to other soil attributes; (b)relates the severity of water repellency to soil

R.J. Harper et al. / Journal of Hydrology 231–232 (2000) 371–383372

management and landuse; and (c) determines thevalue of soil survey in predicting the risk of waterrepellency developing.

2. Multivariate nature of the relationship betweenwater repellency and other soil attributes

A major outcome of recent work in south-westernAustralia has been the elucidation of multivariate rela-tionships between water repellency and various soilattributes, and in particular clay and organic carbon(OC) contents. This multivariate approach has anumber of implications—both for modelling thelikely incidence of water repellency and for reinter-preting the conclusions of previous studies both fromthis region and elsewhere. It should be stressed at theoutset that relationships derived from regression arenot necessarily causal, but when used in an explora-tory manner this approach can suggest previouslyunrecognised relationships and provide hypothesesfor further experimental studies (Tukey, 1977).

Although the relationships between water repellency

and soil attributes such as soil texture and organicmatter content have been known in general termsfor some time (DeBano et al., 1976; DeBano, 1981),these relationships are qualitative rather than quanti-tative and do not provide numerical relationships thatcould be used in a predictive capacity.

Thus, although it is well accepted that organiccompounds cause water repellency, often onlypoor bivariate relationships have been reportedbetween measures of water repellency and OC.For example, it has been claimed that there isno relationship between the quantity of organicmatter in the soil and water repellency for bothsoils from south-western Australia (Nulsen andMcFarlane, 1988) and South Australia (Oades,1992). Similarly, Wallis and Horne (1992), intheir review of several water repellency studies,consider that the nature rather than quantity of soilorganic matter is the most important determinant ofthe severity of water repellency. Exceptions to thisabsence of predictive relationships include relativelysmall studies in isolated areas that will be consideredlater.

R.J. Harper et al. / Journal of Hydrology 231–232 (2000) 371–383 373

Fig. 1. Bivariate relationships between water repellency (log WDPT(s)) and soil organic carbon content (log OC (%)) for the topsoil (0–10 cm)from several studies from south-western Australia. (a) Cairlocup (Harper and Gilkes, 1994); (b) West-Midlands (McKissock et al., 1998); (c)South-West 2 (from data of Walker et al., 1997); and (d) Jarrah Forest (Harper and Wills, unpublished). Regression equations are summarized inTable 1.

The underlying frequency distributions of soil attri-butes are often log-normally distributed or negativelyskewed (Webster and Oliver, 1990); the values ofwater repellency, OC and clay contents of soils inthese studies are no exception. Fig. 1 presents bivari-ate relationships between water repellency, measuredusing the water drop penetration test (King, 1981)(log WDPT), and log OC content for several WesternAustralian studies, with regressions explainingbetween 0 and 31% of the variation (Table 1).These are representative of the generally poor rela-tionships reported by many workers. This tableincludes previously published studies (Harper andGilkes, 1994; McKissock et al., 1998), a re-analysisof data from a survey of farmed soils (Walker et al.,1997) and from soils from the native Jarrah (Eucalyp-tus marginata) forest of south western Australia(Harper and Wills, unpublished). The data of McKis-sock et al. (1998) have been re-analysed to removesoil samples taken from beneath isolated trees withinpaddocks.

Analytical methods are provided in more detail inHarper and Gilkes (1994) and McKissock et al.

(1998). In each case topsoil samples were dried at40–608C, passed through a 2 mm sieve and waterrepellency measured with the water drop penetrationtest (King 1981). The Cairlocup, West Midlands andJarrah Forest samples were taken in autumn and werefield-dry; the South-west 1 and 2 samples were ofvariable moisture content at sampling.

There has also been a general recognition that waterrepellency is more likely to occur on sandy soils withclay contents of,5–6% (Roberts, 1966; Bond, 1969;Harper and Gilkes, 1994). For sandy soils additions ofclay (Ma’shum et al., 1989; Ward and Oades, 1993)and fine material (Roberts, 1966) have reduced waterrepellency. The assumption that water repellencymainly occurs on sandy surfaced soils has formedthe basis for regional assessments of the areas ofland susceptible to water repellency (Select Commit-tee into Land Conservation, 1990). However, reportsof water repellency associated with soils with.20%clay in southern Australia (McGhie and Posner, 1980;Chan, 1992) and elsewhere (Giovannini et al., 1983;Dekker and Ritsema, 1995; Dekker and Ritsema,1996) indicate that the problem is not restricted to


Fig. 2. Bivariate relationships between water repellency (log WDPT (s)) and soil clay (log clay (%)) content for the topsoil (0–10 cm) fromseveral studies from south-western Australia. (a) Cairlocup (Harper and Gilkes, 1994); (b) West-Midlands (McKissock et al., 1998); (c) South-West 2 (from data of Walker et al., 1997); and (d) Jarrah Forest (Harper and Wills, unpublished). Regression equations are summarized in Table1.

sand textured materials. Bivariate relationships fromseveral studies between water repellency (log WDPT)and log clay content are presented in Fig. 2. Theserelationships are generally poor, with regressionsexplaining between 0 and 26% of the variation inwater repellency (Table 1).

The amount of variation in water repellency that isexplained is substantially improved when the log-transformed soil data are combined into multivariateequations with water repellency (log WDPT) as thedependent variable. For example, for the Cairlocuparea bivariate relationships using log OC (%) andlog clay (%) contents explain 0 and 26% variation,respectively, in log WDPT (s) (Table 1). Whencombined in a multivariate equation they explain47% of the variation (Harper and Gilkes, 1994).These multivariate relationships have the form:

log WDPT� a 1 b log OC2 c log clay �1�with the values of the intercept,a, and the coefficientsb andc shown in Table 1, and with the capacity of thisequation to describe water repellency being consistentacross several data sets withR2 values ranging from30 to 47%. These results are also consistent with otherunpublished studies. For example, water repellencywas determined for 45 soils from farmland along a300 km transect between Wellstead and Esperancein south-western Australia (Carter unpublished).There was a relatively strong relationship�R2 �0:52� between water repellency as measured withthe Molarity of Ethanol Test (King, 1981), andorganic carbon measured as loss on ignition (log LOI(%)) and fine material (log, 63mm (%)) contents.

Addition of other soil attributes, using step-wiseregression (Tabachnick and Fidell, 1983), to themultivariate equations in Table 1 increases theamount of variation in water repellency expected tolie between 42 and 63% (Table 2). Table 3 outlinessummary statistics for soil variables, such as WDPT,clay, silt and OC contents in these studies. Apart fromthese analyses, the different data sets contained differ-ent additional soil analyses such as detailed sand sizedeterminations or exchangeable cation contents.Whereas soil OC is a consistent contributor to theseregressions (Table 2), the particle size fractions thatare included in the equation differ, with silt contentbeing a more important predictive variable than clay,in some cases. Similarly, other attributes related to

particle size such as skewness of the sand fraction,or mineralogy of the colloid fraction (Oxalate Fe)are also significant contributors to the regressionequations. We suggest that each of these attributescould be related to soil surface area.

There is thus a consistent trend across several datasets, with a positive relationship between water repel-lency and OC and an inverse relationship betweenwater repellency and soil texture, most commonlyclay or silt content (Harper and Gilkes, 1994; McKis-sock et al., 1998). A general equation to describe theincidence of water repellency thus has the form:

Water repellency<a Org: Matterb

Clayc �2�

Is this model consistent with the literature? In manyinstances this is difficult to determine as many waterrepellency studies have the following limitations:

• They are based on small sample sets with limitedgeographic range and limited variation in soil attri-butes.

• Although water repellency and organic carboncontents are given, there are no or limited claydata (e.g. McGhie and Posner, 1981; Summers,1987; Wallis et al., 1993).

• Water repellency is treated as a categorical ratherthan continuous variable (e.g. King, 1981).

• Soil data are considered in terms of taxonomicclasses which are based on whole profile character-istics, rather than in terms of the specific propertiesof the water repellent horizons (e.g. Richardsonand Hole, 1978; Wallis et al., 1993).

• Studies that have examined the nature of theorganic compounds that are responsible for waterrepellency have not quantitatively related theamounts of these compounds to the degree of repel-lency (Ma’shum et al., 1988).

The relationship reported here (Eq. (2)) also explainsthe strong relationships that occur between waterrepellency and OC contents within single pedons ortrenches (Singer and Ugolini, 1976,R2 � 0:60�; orwithin small areas (Wallis et al., 1990,R2 � 0:79�:In these situations the clay content is more likely tobe constant, with differences in OC content beingdirectly reflected in the degree of water repellency.When soils are obtained from wider areas the clay


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Table 1Summary of regression models used to predict water repellency (WDPT (s)) from organic carbon (log OC) and clay (log clay (%)) contents in topsoil (0–10cm) from various studiesin south-western Australia

Study Authors Area of study No. samples Proportion of variation explained (%) by regression Coefficients of equation log WDPT�a 1 b log OC 2 c log clay

(km2) log WDPTvs log OC

log WDPTvs log clay

log WDPTvs log OC1log clay

a (intercept) b (OC) c (clay)

Cairlocup Harper and Gilkes (1994) 50 148 0 26 47 3.0 (^0.3) 3.1 (̂ 0.4) 3.4 (̂ 0.3)W. Midlands, all samples McKissock et al. (1998) 1000 156 28 0 37 2.51 (^0.13) 2.30 (̂ 0.24) 1.53 (̂ 0.30)W. Midlands, bushland McKissock et al. (1998) 1000 39 26 10 38 2.50 (^0.40) 3.24 (̂ 0.78) 2.58 (̂ 0.89)W. Midlands, crop/pasture McKissock et al. (1998) 1000 117 36 0 43 2.45 (^0.10) 1.68 (̂ 0.18) 0.91 (̂ 0.23)South-west 1 McKissock et al. (1998) 250 000 80 14 32 1.13 (^0.23) 1.76 (̂ 0.32) 1.18 (̂ 0.27)South-west 2 Walker et al. (1997)a 250 000 165 30 3 35 2.94 (̂0.09) 2.31 (̂ 0.26) 1.04 (̂ 0.28)Jarrah Forest Harper and Wills

(unpublished)20 000 70 18 4 30 1.50 (̂0.32) 2.83 (̂ 0.54) 1.75 (̂ 0.49)

a Two outliers removed.

Table 2Best multiple regression models used to predict water repellency (log WDPT (s)) from various soil attributes in topsoil (0–10 cm) from various studies in south-western Australia.R2

proportion of variation explained

Study Authors No. samples Multiple regression equation (^s.e.)a R2 (%)

Cairlocup Harper and Gilkes (1994) 148 log WDPT� 8.7(̂ 0.7)1 3.9(̂ 0.4)log OC2 2.0(̂ 0.3)log clay2 3.0(̂ 0.4)log Fe 63W. Midlands McKissock et al. (1998) 156 log WDPT� 3.19(̂ 0.18)1 2.68(̂ 0.23)log OC2 2.39(̂ 0.33)log (clay1 silt) 46South-West 1 McKissock et al. (1998) 80 log WDPT� 1.07(̂ 0.20)1 1.70(̂ 0.28)log OC2 1.41(̂ 0.30)log silt1 0.74(̂ 0.25) log skewness 42South-West 2 Walker et al. (1997)b 165 log WDPT� 3.59 (̂ 0.16)1 3.05 (̂ 0.29)log OC2 2.00(̂ 0.32)log (clay1 silt) 43Jarrah Forest Harper and Wills (unpublished) 70 log WDPT� 1.37 (̂ 0.30)1 5.22 (̂ 0.70)log OC2 2.74(̂ 0.49)log silt2 1.00(̂ 0.42)log Mg 46

a Fe: Tamm’s oxalate extractable Fe; skewness: skewness of sand size (45–2000mm) distribution; Mg: Exchangeable Mg.b Two outliers removed.

contents are likely to be more variable, and the bivari-ate relationships between OC and water repellency aresubsequently weakened (McKissock et al., 1998). Incontrast, a study of water repellency in trenches inHolland (Dekker and Ritsema, 1994) showed a non-linear relationship between organic matter contentand alcohol concentration, but no relationshipbetween OM content and WDPT.

The data sets examined were mainly sandy intexture (Table 3), however water repellency alsooccurred in soils with.5% clay, consistent with thestudies reported earlier. More OC was needed toinduce water repellency in the more clayey soilsthan in soils with,5% clay, a result consistent withEq. (2). For example, 7% of the West Midlands and6% of the soils in the South-West 2 studies with aWDPT .100s had clay contents of 5–10% (Table4). In both studies water repellent soils with 5–10%clay contained more OC than the similarly waterrepellent soils with,5% clay, with respective OCcontents in the West Midlands soils of3.48^ 0.32% vs 1.74̂ 0.08% and in the South-West 2 soils of 4.19̂ 1.20 vs 1.38̂ 0.09. Theabsence of water repellency in soils with.5% clayreported by Harper and Gilkes (1994) for soils fromthe Cairlocup area of Western Australia may berelated to the modest OC contents of those soils(0.8–3.3%) due partly to the relatively low annualrainfall (350 mm) of that study area. Soil OC gener-ally increases with mean rainfall in south-westernAustralia, consequently water repellency is expectedto occur at much higher clay contents in soils in higherrainfall areas.

This model may also explain the association ofsevere water repellency�WDPT� 9840 s� with soilswith 23% clay and 13% OC reported by Singer and

Ugolini (1976). Occurrence of water repellency insoils with high clay contents has also been explainedas being due to the concentration of hydrophobicmaterial on aggregate surfaces (McGhie and Posner,1980). This also suggests that standard laboratorypreparation procedures of crushing and sievingsamples, prior to measuring water repellency, mayresult in underestimates of the field expression ofwater repellency in such soils.

We can also use Eq. (2) to speculatively re-interpretthe results of Wallis et al. (1993) who described waterrepellency and organic carbon contents in a soilchronosequence in New Zealand. Water repellencywas associated with small OC contents in youngsoils but not with larger OC contents in older soils.These soils had respective clay contents of,1% and20%, thus we suggest that there was insufficient OC inthe more clayey soils to induce repellency.

The specific effects of the different fine mineralfractions in soils in combating water repellency arenot known. In some of the studies reported here claycontent is the most important factor, in others it is siltcontent or oxalate soluble Fe (a measure of amorphous


Table 4Comparison of the mean organic carbon content (%) of topsoils withclay contents,5% and 5–10% with severe water repellency�WDPT . 100 s�; in two studies from south-western Australia.(n) is number of cases

Clay content

, 5% 5–10%

OC (%) n OC (%) n

W. Midlands 1.74̂ 0.08 105 3.48̂ 0.32 8South-West 2 1.38̂ 0.09 117 4.19̂ 1.20 7

Table 3Summary statistics of key soil attributes for each of studies reported in this paper. (10, 50 and 90 percentile)

Study Authors No. samples WDPT (s) OC (%) Clay (%) Silt (%)

10 50 90 10 50 90 10 50 90 10 50 90

Cairlocup Harper and Gilkes (1994) 148 2 7 124 0.45 0.72 1.19 1.5 2.8 5.2 0.7 1.6 3.7W. Midlands McKissock et al. (1998) 156 14 184 902 0.72 1.34 2.95 1.6 2.7 4.2 0.2 1.2 2.0South-West 1 McKissock et al. (1998) 80 1 6 388 1.12 3.12 7.58 1.4 6.3 16.2 1.2 4.3 15.0South-West 2 Walker et al. (1997)a 165 27 552 9680 0.44 1.05 2.90 0.8 1.8 4.0 0.4 0.9 3.1Jarrah Forest Harper and Wills (unpublished) 70 1 26 1109 1.04 2.56 4.47 1.9 4.5 8.6 2.1 5.3 9.3

a Two outliers removed.

iron oxide) (Table 2). Each of these measures canbe regarded as a major contributor to soil surfacearea with a consistent decrease in water repellencywith increasing surface area. Ma’shum et al.(1989) describe a laboratory experiment in whichwater repellency was induced in sands of differentsizes with cetyl alcohol; with repellency inverselyrelated to sand size. Similarly, Roberts (1966)describes the amelioration of water repellency onaddition of 2.5% finely ground silica (75mm). Thesurface areas of fine sand (0.1 m2/g), silt (1.0 m2/g)and clay (5–800 m2/g, dependent on mineralogy)fractions are quite different in both extent and type(White, 1979).

The question thus arises as to whether it issurface areaper se that is important, or sand oraggregate size. The interaction of hydrophobiccompounds and the soil may be between aggre-gates of sand, silt and clay and organic particles(Franco et al., 1995) rather than with single crys-tals. For example, the surface area in 0.1 nm voidsbetween silicate layers in smectites and illites maynot participate in overcoming water repellency asmolecules of some hydrophobic compounds mayresist intercalation into interlayers. This may alsoexplain reported responses of water repellency toclay applications, where clay effectiveness is notincreased by smaller crystal size or larger clay surfacearea (McKissock et al., 2000).

The strength of the relationships in Table 2 suggeststhat it may be possible to produce a general predictivemodel for water repellency, however, this is not possi-ble at this stage. Apart from not being based on arepresentative sample of the soils from south-westernAustralia, the coefficients of the multivariate relation-ships in Table 2 will differ between studies due todifferences in other factors which are known to affectwater repellency. These include the moisture contentof the soils at the time of sampling (Summers, 1987),sample pre-treatment and laboratory conditions whenmeasuring water repellency (King, 1981). Althougheach of these factors may be consistent within eachdata set, they may differ between data-sets. Similarly,different suites of soil analysis have been performed inthe different studies. The development of a waterrepellency prediction model, for this region, willtherefore require a standard sampling and analysisprogram.

3. Variation in water repellency with soilmanagement and landuse

Water repellency is generally more severe in soilsunder legume-grass pastures, compared to cerealcrops, with the severity of repellency increasingwith the age of pasture (Bond, 1964; King, 1981;McGhie and Posner, 1981). Consequently, asdescribed earlier, it has been suggested that it is thenature rather than amount of OC contributed by plantsthat is most important in determining the severity ofwater repellency. It follows that it may be possible tomanage water repellency by manipulating the type oforganic matter in soil by management practicesincluding selection of species.

Eq. (2) allows us to re-interpret these seeminglyclear-cut conclusions. Differences in either OC orclay contents alone will change water repellency,and these differences can be caused by changes insoil management or landuse. Harper and Gilkes(1994) re-interpreted data of McGhie and Posner(1981)—which had suggested that differences inwater repellency under crops and pastures in a long-term field trial were induced by different plant speciesand rotations. When the water repellency and OCcontent were compared in a bivariate plot the slopewas not systematically different (Fig. 3a), indicatingthat there was no systematic difference in the capacityof organic matter to induce water repellency. Differ-ences in water repellency were suggested to be due todifferences in the organic carbon content, induced bydifferences in management (i.e. cultivation vs pastur-ing). This was subsequently confirmed by McKissocket al. (1998) for a comparison between cropped andpastured land (Fig. 3b). Re-presentation of the data ofSpadek et al. (1994) from a crop-pasture rotation trialnear Esperance, Western Australia, is also consistentwith this interpretation. Here different rotations ofcrops and pasture had been continued over 26 years.A bivariate relationship between water repellencymeasured by the Molarity of Ethanol Droplet Test(King, 1981; log MED) and log OC (measured byloss on ignition) explained 81% of the variation(Fig. 3d). As with the McGhie and Posner (1981)study the clay content for each sample had not beendetermined, however this is assumed to be constantacross the trial site.

Cultivation for crop establishment reduces soil OC


content by mixing and mineralisation, whereas OCcan accumulate under continuous pasture (Rasmussenand Collins, 1991). Thus, differences in water repel-lency between crops and pastures can be interpreted asbeing due to differences in OC content, induced bymanagement, rather than due to differences in thecomposition of OC due to different plant species.Increases in water repellency with increasing age ofpasture were most likely due to the accumulation ofOC, a result that also applies to the earlier observa-tions of Bond (1964); King (1981). We thus suggestthat any practice that increases soil OC content willincrease water repellency and vice versa. This is animportant consideration with the increasing use ofzero tillage cropping which can lead to the accumula-tion of organic matter near the soil surface.

McKissock et al. (1998) compared soils underbushland and pasture in the West Midlands andfound that the OC fromBanksia woodland andheath induced water repellency to a greater extent

than OC from pasture (Fig. 3c). Agricultural develop-ment of adjacent farmland significantly reduced waterrepellency in the West Midlands, from 838̂331 s,in bushland soils, to 373̂ 43 s in agricultural soils.Adding “landuse” to the multiple regression for theWest Midlands data (Table 2), however, only margin-ally increased the proportion of variation explainedfrom 46 to 49%. McGhie and Posner (1980) alsoreport severe water repellency under natural standsof Eucalyptus astringens,or “brown mallet”. Thecontribution of residual organic compounds from theformer natural bushland to water repellency in farm-land is not known, with McGhie and Posner (1980)suggesting that this may be significant and help toexplain the variable distribution of water repellencyin farmland.

An implication of Eq. (2) is that for direct compar-isons to be made of the effects of soil management orlanduse on water repellency some standardisation ofother soil properties should occur. Differences in clay


Fig. 3. Bivariate relationships between water repellency and organic carbon content for different landuses from several studies. (a) Agriculturalrotations (McGhie and Posner, 1981,R2 � 0:38; 25 d.f.); (b) agricultural rotations (McKissock et al., 1998,R2 � 0:36; 116 d.f.); (c) bushland(McKissock et al., 1998,R2 � 0:26; 38 d.f.); (d) agricultural rotations (Spadek et al., 1994;R2 � 0:81; 12 d.f.). All regressionsP , 0.0001.Samples from land under wheat (X), pasture (W), in bushland (A), lupin (B), wheat/pasture (K) and wheat/lupin (O).

content alone, for example, with no difference in OCcontent, will affect apparent water repellency.Comparisons of landuse are often by necessity madebetween spatially separated parcels of land, and it isquite likely that an array of soil properties will differbetween such parcels. Similarly, given the consider-able spatial variation in soil properties it is importantthat comparisons are made following adequatesampling, to allow reasonable estimates of differencesbetween mean values (Webster and Oliver, 1990), andnot by comparing single paired samples (e.g. McFar-lane et al., 1992; Franco et al., 1995).

4. Implications of the multivariate relationship forsoil management

Eq. (2) also provides a basis for re-interpretingvarious studies of the effect of soil management onsoil water repellency; as water repellency can bereduced by management factors which reduce thetotal OC content or increase the amount of clay inthe topsoil.

Cultivation. Minimum tillage and zero till systemsare likely to cause an increase in water repellency dueto the accumulation of organic matter in the soilsurface horizon (White, 1990). Chan (1992), forexample, reported an increase in OC content from1.7% to 2.4% with a change in water repellency(WDPT) from 0 to ~39 s, associated with differenttillage systems. Likewise cultivation will decreasewater repellency by both mixing and mineralisationof organic matter. For texture contrast soils cultivationcan increase the clay content of the topsoil by mixingdeeper, more clayey materials thereby reducing waterrepellency.

Claying and marling. Increasing the soil claycontent by the addition of clayey materials, “claying”(Ward and Oades, 1993; McKissock et al., 2000) anddelving of the subsoil (Blackwell et al., 1994a) areboth known to reduce water repellency.

Liming. Liming may reduce water repellency byproviding additional fine material and also stimulatingthe mineralisation of organic matter. This reduction inorganic matter may explain the reduction in waterrepellency on liming (Wallis and Horne, 1992), parti-cularly where the lime is incorporated by cultivation,which further increases organic matter mineralisation.

Land degradation in Western Australia water repel-lency has been considered a form of “degradation” ofagricultural soils (Select Committee into LandConservation, 1990), however it is evident thatwater repellency is not just a feature of agriculturalsoils but also occurs in natural soils. Soils from theSouth-West 1, Jarrah Forest and some of the WestMidlands data sets are vegetated with a range ofnatural communities. Not only do these soils havewater repellency as severe as that which occurs inagricultural soils (Table 3), but they also have thesame form of predictive relationships between waterrepellency and soil properties as soils under agricul-ture. Indeed, as discussed earlier, agricultural devel-opment may reduce the severity of water repellency.The implications of water repellency in these season-ally dry natural ecosystems are not known, however, itmay comprise a strategy to (a) inhibit seed germina-tion and water use by potential competitors (Scott,1991), or (b) to conserve water, as evaporation canbe reduced under water repellent mulches (Hillel andBerliner, 1974).

5. Using soil survey to determine water repellencyrisk

Although McGhie and Posner (1980) described thespecific association of severe water repellency with“mallet hill” land types in Western Australia, thespatial distribution of water repellency, at a fieldscale, has not been studied systematically. Knowledgeof the distribution of water repellent soils on farmswill allow the strategic, rather than blanket, applica-tion of ameliorative treatments such as furrow sowing,clay, or wetting agents. Although individual soil attri-butes, such as water repellency, can be mappedfollowing field observations or laboratory analysesof field samples by techniques such as kriging(Webster and Oliver, 1990), this is unlikely to bepractical in Australia’s dryland farming systems.Not only are many farms between 1000–8000 ha insize but farmers are also confronted by an array ofother soil management problems such as acidity, sali-nity, wind erosion and multiple nutrient deficiencies(Select Committee into Land Conservation, 1990).Any soil mapping will need to provide informationto assist management of these multiple problems.


An implication of the multivariate model for waterrepellency (Eq. (2)) is that for any particular soiltexture, the severity of water repellency is stronglydetermined by the soil’s organic matter content.Thus, Harper and Gilkes (1994) introduced the ideaof separately clarifying thepotentialandactualwaterrepellency of soils. Potential water repellency, whichindicates the risk of water repellency, is determinedby stable soil properties such as soil texture and parti-cularly clay content. The actual water repellency is thedegree to which water repellency is expressed andparticularly depends on soil management factors thataffect soil organic matter content, as alreadydescribed. Measurements of water repellency under-taken during routine soil survey, or soil testing proce-dures, will only indicate where it is currently aproblem and not where it will develop in the future.Similarly, the values may vary with the season ofmeasurement as water repellency shows majortemporal variations in severity (Summers, 1987).

Soil survey procedures using the hand texturingprocedure (Schoeneberger et al., 1998), or possiblyremote sensing techniques (Wong and Harper,1999), may rapidly and adequately define the distribu-tion of soil clay contents and can thus be used toindicate where water repellency will develop. Thus,Eq. (2) can be used as a pedo-transfer function topredict where water repellency will occur under a

particular management scenario. It is expected thatthe prediction of water repellency will be greatlyrefined by incorporating additional pedological dataand local experience into the predictive model so as togenerate an expert system.

Soil mapping often produces Soil Series that arebased on a classification of the whole profile usingpedological criteria. A defined member of a SoilSeries often exhibits a wide range in surface soil prop-erties, consequently water repellency may varyconsiderably within this member. Harper and Gilkes(1994) describe using soil textural classes to providegreater objectivity in defining members of mappingunits. The five successive classes (I–V) had respectivemedian clay contents of 1.5, 2.5, 4, 8 and 22% andwater repellency decreased in incidence with increas-ing class, being absent for the more clayey Class IV orV soils. Water repellency was most severe for theClassI soils with 66% of the samples having WaterDrop Penetration Time (WDPT) values.10 s,whereas corresponding values for Classes II and IIIwere 37 and 20% (Fig. 4). Similarly, each of Classes Ito III had 39, 6 and 3% of soils with severe waterrepellency �WDPT . 100 s� (Fig. 4). Hendrickx etal. (1988) have used a similar approach to utilisequalitative soil survey information to predict theoccurrence of unstable wetting fronts caused bywater repellency.


Fig. 4. Comparison between the proportion of samples affected by moderate�WDPT . 10 s� and severe�WDPT . 100 s� water repellency ineach of five classes with increasing topsoil (0–10 cm) field texture derived from a soil survey. Number of cases in each class in brackets.

6. Conclusions

This view of research on water repellent soils insouthern and southwestern Australia has clearlydemonstrated that the water repellence is directlyrelated to the organic matter content and inverselyrelated to the clay content. This multivariate depen-dence provides a simple basis for explaining thedependence of water repellency on soil type, landmanagement practices and ameliorative practicesand thus a basis for the development of predictivemodels. Moreover, it may provide indications of thenature of the interactions between soil fine materialand organic matter in inducing water repellency.

Acknowledgements

We would like to thank the Australian Departmentof Industry Science and Tourism for funding to attendthe International Workshop “Soil water repellency:origins, assessment, occurrence, consequences,modeling and amelioration”, SC-DLO Winand Star-ing Centre, Wageningen, Holland. Irene McKissock isfunded by Grains Research and DevelopmentCorporation. Allan Wills, Evonne Walker, ShelleyMcArthur and Lin Wong are thanked for their techni-cal assistance. All landholders are thanked for accessto their land.

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