the effect of soil compaction and soil physical properties on the mechanical resistance of south...
TRANSCRIPT
Ž .Geoderma 78 1997 93–111
The effect of soil compaction and soil physicalproperties on the mechanical resistance of South
African forestry soils
C.W. Smith a,), M.A. Johnston b, S Lorentz c
a Institute for Commercial Forestry Research, UniÕersity of Natal, P.O. Box 100281, ScottsÕille 3208, SouthAfrica
b Department of Agronomy, UniÕersity of Natal, PriÕate Bag X01, ScottsÕille 3209, South Africac Department of Agricultural Engineering, UniÕersity of Natal, PriÕate Bag X01, ScottsÕille 3209, South
Africa
Received 10 May 1996; accepted 12 February 1997
Abstract
High soil strengths frequently develop in compacted forestry soils thus limiting root develop-ment of commercial timber species. The effect of soil compaction on mechanical resistance was
Ž .assessed for 29 South African forestry soils ranging widely in texture 8 to 66% clay and organicŽ .carbon content 0.26 to 5.77% . Models are presented which show that clay content and organic
Ž .carbon strongly influence the relationship between penetrometer soil strength PSS , bulk densityand water content. Organic carbon levels were not high enough to have a large effect on the
Ž .PSS–compaction–water content relationship for finer-textured soils )30% clay . However,evidence is presented to suggest that organic matter becomes more important in influencing PSSfor a range of water contents and bulk densities as clay content decreases. For cohesive soilsŽ .generally those with more than approximately 20% silt plus clay increasing clay content reducesthe rate at which PSS increases with decreasing water content. Similar to clayey soils, non-cohe-
Ž .sive soils -20% silt plus clay displayed slow rates of decrease in PSS as the soil dried althoughthe magnitude of PSS was considerably less for similar matric potentials and relative bulk
Ž .densities than for finer-textured soils. Thus the PSS at wilting point y1500 kPa increased withincreasing clay content. At a matric potential of y10 kPa PSS was most strongly related toloss-on-ignition indicating that organic carbon and clay mineralogy rather than soil texture aloneaffect soil strength in wet soils.
Keywords: soil strength; penetrometer; mechanical resistance; forestry soils; soil compaction
) Ž . Ž .Corresponding author. Tel.: q27 331 62314; Fax: q27 331 68905; E-mail: [email protected]
0016-7061r97r$17.00 q 1997 Elsevier Science B.V. All rights reserved.Ž .PII S0016-7061 97 00029-3
( )C.W. Smith et al.rGeoderma 78 1997 93–11194
1. Introduction
Measurements of soil strength to estimate mechanical resistance experienced by rootsystems have been widely used in commercial timber plantations to characterise the
Žcompacted state of forestry soils Sands et al., 1979; Jakobsen and Greacen, 1985; Grey.and Jacobs, 1987 . Reductions in rooting depth for various tree species grown in
Žcompacted soils have been attributed to increases in mechanical resistance Sands and.Bowen, 1978; Zisa et al., 1980; Tuttle et al., 1988 . A commonly accepted technique is
to measure mechanical impedance with a penetrometer. Although the measurement ofŽmechanical impedance in this way differs from that experienced by a root Barley and
.Greacen, 1967 , penetrometers have been used widely as comparative measures of soilŽstrength and as rapid appraisals of soil compaction in the field Campbell and O’Sulli-
. Ž .van, 1993 . Bengough 1993 has stated that the best indirect method of estimating soilresistance to root growth is by measuring soil resistance to a probe or penetrometer.
A factor limiting the use and interpretation of penetrometers in the field or as anindex of excessive compaction is that there is usually an insufficient data base for
Žpenetrometer resistance as a function of soil water content and bulk density Gupta and.Allmaras, 1987; Bennie and Burger, 1988 . A widely accepted norm has been to
measure penetrometer resistance at field capacity, which is essentially a reference point.However, it is very difficult to infer strength characteristics throughout the wholeavailable water range from a single measurement.
As soil strength is strongly related to water content it may vary considerablyŽ .throughout the year with wetting and drying cycles Spain et al., 1990 . The relationship
between strength and water content for a particular soil is strongly influenced by theŽ .degree of compaction Mirreh and Ketcheson, 1972 and this may affect forestry
management practices, such as the timing of tillage and site preparation practices. Whileit is clear that mechanical resistance is related to water content and bulk density theliterature is conflicting on the role of soil physical and chemical properties on thedevelopment of soil strength. Soil strength has been shown to be influenced by soil
Ž . Ž .texture Gerard, 1965; Byrd and Cassel, 1980 . Gerard 1965 , for example, showed thatthe strength of remoulded briquets, at a range soil water contents, increased with
Ž .increasing silt and clay contents. Similarly, Bennie and Burger 1988 illustrated therelationship between penetration resistance and silt plus clay content for a number of
Ž .predominantly sandy-textured soils clay plus silt -20% . Penetration resistance for thesame water content and bulk density increased with increasing amounts of silt plus clay.Increasing amounts of clay may also be responsible for increases in soil strength and
Ž .retardation of root growth Gerard et al., 1982 . Utilising reconstituted soil corescontaining between 66 and 83% sand, all with a similar bulk density, Byrd and CasselŽ .1980 reported a direct correlation between soil texture and mechanical resistance.
Ž .However, Stitt et al. 1982 studied the relationship between physical, chemical andmineralogical properties of a group of Atlantic coastal plain soils in the U.S.A. andfound no direct correlation between mechanical impedance and soil texture nor anyevidence that cementing agents were affecting cone index values.
Identification of factors affecting strength development is important for evaluating theeffects of compaction on soil properties and tree growth, soil trafficability and timing of
( )C.W. Smith et al.rGeoderma 78 1997 93–111 95
tillage operations. The objective of this study was to characterise the effect of soilŽ .compaction as reflected by bulk density on the relationship between penetrometer soil
strength and water content for a range of South African forestry soils, and to examinewhether these relationships could be related to commonly measured soil properties.
2. Materials and methods
2.1. Soils studied
Twenty-nine soils representing a wide range of soil textures and organic carboncontents from the main timber-growing regions in South Africa were used in thisinvestigation. The soils were selected from the main timber-growing areas in the easternseaboard of South Africa. This region is a predominantly summer rainfall region varyingin altitude from 0 to 1800 m. Rainfall is in the order of 700–1400 mm per annum andthe mean annual temperature ranges from 138 to 188C. Soil samples were taken fromfreshly cut faces in open pits. At the same time the soil profiles were described and
Žclassified according to the systems of South Africa Soil Classification Working Group,. Ž .1991 and the United States Soil Survey Staff, 1990 .
2.2. Sample preparation
Two sets of soil samples were prepared:Ž .1 ‘Repacked’ soil cores prepared for uniaxial compression tests in a separate study
Ž .Smith et al., 1997 for all the forestry soils. In this way it was possible to measurepenetrometer soil strength on a wide range of bulk densities and water contents for eachsoil. Field samples of soil were air-dried and passed through a 2 mm sieve. Each soilwas wet up to a range of water contents between saturation and wilting point. For eachsample approximately 2 kg of the air-dry soil was poured into a plastic tray and broughtto the desired water content by wetting with an atomizer followed by thorough mixing.The tray was then placed in a plastic bag and the sample was allowed to equilibrate for48 h. After equilibration, soil samples at each water content were placed in aluminiumcylinders, 77 mm in diameter and 50 mm long. As the cylinders had no attached base,they were placed on a perforated 5 mm metal base before the soil was added. Thecylinders were gently tapped to allow settling of the soil particles. Soil samples in thecylinder were then subject to a range of applied pressures by hydraulic press consisting
Ž .of a hydraulic ram connected to a piston Koolen, 1974 . The pressure was maintainedfor a few seconds and then released. The samples were allowed to ‘rebound’ before finalheights were measured for bulk density calculation.
Ž .2 ‘Repacked’ soil cores utilised during the determination of the water retentionŽ .characteristics of forestry soils Smith, 1995 . PSS was determined on all the soils
following equilibration at either y10 kPa or y1500 kPa after drying from saturation.The samples were prepared for the determination of full water retentivity curves from
( )C.W. Smith et al.rGeoderma 78 1997 93–11196
saturation to y1500 kPa, following similar procedures to those of Hill and SumnerŽ . Ž . Ž .1967 and Mirreh and Ketcheson 1972 . Air-dry sieved soil -2 mm soil was used toprepare the soil cores. The mass of soil required to obtain the desired bulk density when
Ž .compressed into an aluminium cylinder 53.0 mm in diameter and 29.5 mm long wasmeasured out. The samples were then equilibrated in a plastic bag for two days at water
Žcontents approximating the critical water content for maximum compressibility Smith et.al., 1997 . These were then compressed into the cylinder using an Instron Universal
Ž . 1Testing Machine IUTM . For the higher bulk densities, the sample was compressed intwo increments. The first half was compressed into the cylinder and then the second halfwas compressed on top of that. Triplicate cylinders at three or four levels of compactionwere established for each soil. All the soil cores were saturated with water for severaldays to ensure as complete a saturation of the soil as possible. As the original weight ofair-dry soil was known, together with the dimensions of the core and the air-dry watercontent, it was possible to ascertain when the soil was close to saturation by weighing.For equilibration at y10 kPa soils were equilibrated on a tension table apparatus
Ž .consisting of diatomaceous earth over coarse sand Smith and Thomasson, 1974 . Soilwater contents were recorded at matric potentials of y1.0, y2.5, y5.0, y7.5 andy10.0 kPa, allowing a minimum of 48 h for equilibration at each matric potential. Thesoil cores were equilibrated at y1500 kPa, corresponding to ‘wilting point’, using a 15bar ceramic plate in a pressure chamber.
( )2.3. Penetrometer soil strength PSS
The compressed soil cores with an attached metal base were placed on a top-panbalance. PSS was then measured on the compressed cores using a 608, 2 mm basaldiameter cone penetrometer, relieved to 1.5 mm behind the tip in order to reduce thesoil–steel friction component of cone resistance as much as possible. Also the use ofsuch a small cone in 75 mm laterally confined soil cores avoids problems due to edgeeffects. Core diameter may affect cone resistance if the core diameter is less than 20
Ž .times that of the probe Bengough, 1993 . The penetrometer was mounted on an InstronŽ .Universal Testing Machine IUTM and penetrated the cores at a rate of 10 mmrmin to
a depth of 40 mm. Two replicate penetrations were carried out for each soil core.Because of a malfunction in the recording chart mechanism of the IUTM the soil coreswere placed on a balance which was tared to zero. Balance readings were recorded at 5mm depth increments, producing seven readings altogether, from which an average wascalculated. The initial reading at 5 mm depth was disregarded as PSS increased withdepth up to a certain depth. This depth, beyond which PSS became relatively constant, is
Ž .known as the critical penetration depth Bradford, 1986 and was achieved for most soilsbetween 5 and 10 mm. The force required for the penetrometer to penetrate the soil was
Ž .calculated by converting the balance reading kg into cone resistance or penetrometer
1 The use of trade names does not imply endorsement.
( )C.W. Smith et al.rGeoderma 78 1997 93–111 97
Ž . Ž . Ž 2 .soil strength MPa by dividing the load kg by the cone basal area m andŽ .multiplying by the acceleration due to gravity Bradford, 1986 . Thus:
PSS MPa sMgrp r 2 1Ž . Ž .y2 Ž .where: gs9.807 m s ; Msmass kg ; and rsbasal radius of penetrometer cone
Ž 2 .m .For a cone with a basal diameter of 2 mm, a mass of 1 g recorded on the balance
corresponded to a cone resistance of 3.12166 kPa. On completion of the penetrationmeasurements the cores were oven-dried and bulk density and water content weredetermined.
2.4. Analytical methods
Ž .Soil texture was described in terms of the percentage of clay -0.002 mm , fine siltŽ . Ž . Ž .0.002–0.02 mm , coarse silt 0.02–0.05 mm , fine sand 0.05–0.25 mm , medium sandŽ . Ž .0.25–0.50 mm , and coarse sand 0.50–2.00 mm . Soil samples were pre-treated with
Ž .hydrogen peroxide 30%, vrv and the size fractions were determined by the pipetteŽ . Žmethod Day, 1965 after treatment with calgon sodium hexametaphosphate and sodium.carbonate and ultrasound. Organic carbon was determined by the Walkley–Black wet
Ž . Ž .oxidation method Walkley, 1947 . Loss-on-ignition LOI was determined by the lossŽ .in mass after ignition at 4508C and expressed as a percentage of oven-dry 1058C soil
mass. At this temperature, and for a similar range of South African forestry soils,Ž . ŽDonkin 1991 showed that LOI was strongly correlated with organic carbon Walkley–
.Black method and soil texture. Soil pH was determined in a suspension of 10 g soil inŽ .25 ml deionised H O, and in 1 M KCl. Effective cation exchange capacity ECEC was2
calculated as the sum of exchangeable basic and acidic cations and was expressed incmol kgy1 soil.c
3. Results and discussion
A feature of the soils was the wide range of textures and organic carbon levels. ClayŽ .contents ranged from 8 to 66% and organic carbon from 0.26 to 5.77% Table 1 . In
general, 2 : 1 clays were lacking as evidenced by the low ECEC values which rangedfrom 0.85 to 12.96 cmol kgy1. The highly weathered nature of the soils is reflected byc
some 85% of all soils having an ECEC of less than 6.00 cmol kgy1 soil and low tocŽ . Ž .very low pH KCl values Table 1 . The soils studied comprised mainly of Oxisols,
Ž .Ultisols, Alfisols and Entisols Soil Survey Staff, 1990 .
( )3.1. Effect of soil compaction on penetrometer soil strength PSS Õersus water contentrelationships for Õarious forestry soils
Ž .Penetrometer soil strength PSS versus water content relationships for a range ofbulk densities for selected forestry soils are illustrated in Fig. 1. The graphs on the
( )C.W. Smith et al.rGeoderma 78 1997 93–11198
Tab
le1
Soil
iden
tific
atio
nan
dsi
tech
arac
teri
stic
sof
the
soils
stud
ied
Part
icle
size
Soil
clas
sifi
catio
nSi
teL
oss-
on-
Org
anic
EC
EC
pHŽ
.di
stri
butio
n%
igni
tion
carb
onb
a,b
Soil
form
and
Soil
taxo
nom
yPa
rent
mat
eria
ly
1Ž
.Ž
.Ž
.Ž
.N
o.%
%cm
olkg
KC
la
ccl
aysi
ltsa
ndfa
mily
1AL
usik
i111
0T
ypic
Kan
hapl
usta
lfT
illite
2247
316.
624.
026.
773.
952A
Car
tref
2100
Typ
icH
apla
quep
tC
oars
e-gr
aine
dar
kosi
c13
1770
2.29
1.42
3.51
3.95
sand
ston
e2E
1115
740.
810.
321.
424.
253A
Lus
iki2
120
Aqu
icK
anha
plus
talf
Till
ite24
3441
5.86
2.37
4.04
3.85
4AM
agw
a12
00U
stic
Kan
hapl
ohum
ult
Arg
illac
eous
shal
e41
527
14.1
82.
106.
383.
955A
Inan
da12
00U
stic
Kan
dihu
mul
tM
icac
eous
sand
ston
e30
1555
6.73
2.15
3.94
n.d
6AK
rans
kop
1100
Hum
icH
aplu
stox
Dol
erite
5144
518
.49
5.77
4.82
4.45
6B46
2925
13.9
82.
642.
264.
756B
265
2312
11.2
71.
091.
645.
157A
Kra
nsko
p11
00H
umic
Hap
lust
oxD
oler
ite56
2133
11.3
04.
223.
564.
208A
Inan
da12
00T
ypic
Kan
hapl
ustu
ltA
rgill
aceo
ussh
ale
4044
168.
313.
589.
664.
558B
5037
134.
471.
0610
.27
4.59
9AN
oman
ci22
00Pa
chic
Hap
lum
brep
tG
neis
srsc
hist
2722
518.
383.
8312
.96
n.d.
10A
Car
tref
2200
Typ
icH
apla
quep
tT
illite
1634
502.
150.
953.
013.
8014
AH
utto
n21
00T
ypic
Kan
dius
tult
Coa
rse-
grai
ned
129
791.
370.
431.
163.
90sa
ndst
one
( )C.W. Smith et al.rGeoderma 78 1997 93–111 99
15A
Fern
woo
d21
10T
ypic
Ust
ipsa
mm
ent
Aeo
lian
sand
911
803.
131.
651.
894.
1016
AN
oman
ci12
00L
ithic
Ust
ochr
ept
Bio
tite
gran
ite24
1759
4.41
2.36
4.75
4.95
17A
Hut
ton
1200
Typ
icK
andi
ustu
ltB
iotit
egr
anite
2610
642.
751.
493.
254.
3017
B29
665
2.94
1.09
3.22
4.25
18A
Inan
da12
00T
ypic
Kan
hapl
ustu
ltL
euco
crat
icgr
anite
2816
564.
012.
422.
553.
7019
AK
rans
kop
1100
Hum
icX
anth
icD
iaba
se66
286
15.3
34.
133.
674.
10H
aplu
stox
20A
Clo
velly
1100
Lith
icH
aplu
stox
Med
ium
-gra
ined
3516
494.
031.
371.
763.
95sa
ndst
one
20B
3119
503.
580.
921.
434.
0521
AK
rans
kop
1100
Typ
icH
aplu
stox
Gra
nitic
gnei
ss44
1541
9.01
4.23
2.84
4.15
21B
4616
384.
931.
052.
324.
3522
AH
utto
n12
00R
hodi
cK
anha
plus
tult
Hor
nble
nde
biot
ite32
860
3.98
1.21
2.24
4.25
22B
528
404.
860.
342.
694.
3523
ASw
artla
nd12
11R
hodi
cK
anha
plus
talf
Dia
base
3420
465.
271.
575.
745.
2024
ASw
artla
nd21
11T
ypic
Kan
hapl
usta
lfH
ornb
lend
ebi
otite
3017
532.
871.
947.
885.
9024
B38
1844
2.80
1.46
2.25
4.30
25A
Inan
da12
00T
ypic
Kan
dihu
mul
tB
iotit
egr
anite
3411
556.
372.
851.
984.
0526
AM
agw
a11
00H
umic
Xan
thic
Hap
lust
oxB
iotit
egr
anite
3011
5910
.04
3.42
2.74
3.85
aŽ
.So
ilC
lass
ific
atio
nW
orki
ngG
roup
1991
.b
Ž.
Soil
Surv
eySt
aff
1990
.
( )C.W. Smith et al.rGeoderma 78 1997 93–111100
Ž .Fig. 1. a–f The effect of compaction on the penetrometer soil strength–water content relationship for selectedŽ .forestry soils. The symbol WP is the water content corresponding to wilting point y1500 kPa . FCL and
Ž .FCH are the water contents corresponding to field capacity y10 kPa at low and high levels of compaction,Ž y1 . Ž y3 .respectively. u sgravimetric water content kg kg , r sbulk density Mg m .m b
( )C.W. Smith et al.rGeoderma 78 1997 93–111 101
Ž .Fig. 1. continued .
( )C.W. Smith et al.rGeoderma 78 1997 93–111102
left-hand side have been transposed from the original data on the right-hand side forŽ .clarity Smith, 1995 . All the graphs in Fig. 1 have been drawn at the same scale to
Ž .enable a visual comparison. Water retention data from Smith 1995 has been superim-posed on the x-axis so that an initial interpretation of the PSS values with respect toavailable water capacity criteria can be made. As the matric potential at a given water
Ž .content depends upon the compaction level Larson and Gupta, 1980 , three values ofŽ .matric potential, those corresponding to wilting point y1500 kPa and field capacity
Ž .y10 kPa , are given in the graphs corresponding to the lowest and highest bulkŽ .densities WP and FCL and FCH, respectively . Only one water content is presented for
WP since the changes in water content at WP for different levels of compaction weretoo small to be represented on the graphs. It should also be pointed out that the PSSreadings were not carried out on soils dried under tension during the determination ofthe water retention characteristic. Gravimetric water content has been used becausevolumetric water content or matric potential may change during penetration due to
Žparticle rearrangement whereas gravimetric water content remains constant Koolen and.Kuipers, 1983 .
For all soils PSS increases with increasing bulk density and decreasing water content,except at lower levels of compaction when there is usually a decline in PSS as the soilbecomes very dry. A feature of all the graphs is that, for a range of bulk densities, onlysmall differences in PSS occur at water contents approaching field capacity and wetter.As the soils dry the lines diverge, illustrating that differences in soil strength fordifferent bulk densities are greater at lower rather than high water contents.
Ž . Ž .For the loamy sand 15A Fig. 1a only small differences in strength developmentwere noted across a wide range of water contents. In contrast to the other soils in Fig. 1,PSS for the loamy sand does not undergo an abrupt change at any bulk density as watercontent changes. This can be primarily related to the contribution of frictional ratherthan cohesion forces to PSS. Surface tension forces may contribute to resistance atintermediate water contents, termed annular bridges by Panayiotopolous and MullinsŽ .1985 , which bind soil particles together forming bonds of sufficient strength to providea degree of resistance. These forces will be negligible when the sandy soil becomes verywet or very dry.
South African forestry soils with between 12 and 20% clay and derived from eithersandstone sediments or glacial tillite are known to pose a number of establishmentproblems for forestry management due to their poor consistence. Two such soils, the
Ž . Ž . Ž .sandy loam 14A and the loam 10A Fig. 1b and c, respectively illustrate thesensitivity of PSS to water content especially at high bulk densities. Pronounced
Ž .increases in PSS from 1 to 5 MPa for the sandy loam occurred over a range of waterŽ .contents, from a range of as little as 4% by mass . Similar results have been reported by
Ž .Mullins et al. 1989 for hardsetting soils. The proximity of the iso-stress lines for theŽ .sandy loam 14A, Fig. 1b compared to the more widely spaced iso-stress lines for the
Ž .loam 10A, Fig. 1c is probably related to the slightly greater cohesion and availableŽ .water capacity which reflects a more even pore size distribution of the loam due to its
Ž .higher clay plus silt content 50% as opposed to 21% for the sandy loam . Alsoobservations in the field and the laboratory show that both soils slump readily when theyare wet up rapidly. As the soil approaches field capacity, the bulk densities for
( )C.W. Smith et al.rGeoderma 78 1997 93–111 103
uncompacted soil increases. This is due to the smaller pores filling with water thusseriously reducing the effectiveness of the high-tension water bridges binding the
Ž .particles together Akram and Kemper, 1979 . Consequently, particles succumb togravitational forces and, in the case of the more sandy-textured soils, slumping is oftenobserved.
Ž .The PSS of the sandy clay loam soil 22A developed from granite displays a strongŽ .dependence on water content and compaction level Fig. 1d . The PSS levels at high
water contents are very low but increase rapidly as the soils dry at moderate levels ofcompaction. With higher clay contents changes in PSS take place across a wider range
Ž . Ž . Žof water contents for the clay 19A and silty clay 4A 66% and 41% clay,.respectively, Fig. 1e and f . As these soils approach wilting point the PSS values
increase less rapidly at higher levels of compaction than the less clayey soils. These soilsalso differ from the soils with a lower clay content in that PSS at field capacity is higherat all levels of compaction.
A feature of all the graphs presented here is the slight convexity of the PSS–watercontent relationship at low bulk densities. The PSS commonly decreases as the soil driesbeyond wilting point. This slight drop in PSS as the soils become dry at relatively low
Ž .bulk densities has also been recorded by Mirreh and Ketcheson 1972 and Akram andŽ . Ž .Kemper 1979 . Mirreh and Ketcheson 1972 developed relationships between pen-
etrometer resistance, bulk density and matric potential for a clay loam soil and noted thatat low bulk densities mechanical resistance of the soil passed through a maximum asmatric potential decreased from y100 to y800 kPa. It was suggested that the convexityof the soil resistance surface along the matric potential axis at low bulk densities, similarto the water content–PSS relationships in Fig. 1, was caused by inter-particle moisturebonds increasing in strength as water is drained from larger pores. Further drainageresults in a larger number of broken bonds and a net decline in resistance results.
A number of authors have placed great emphasis on the role of effective stress in theŽgeneration of high levels of soil strength, particularly in hardsetting soils Mullins and
. Ž .Panayiotopolous, 1984; Mullins et al., 1989; Ley et al., 1993 . Mullins et al. 1989emphasised that since hardsetting is usually accompanied by slumping, which itself is aprocess of compaction, it is difficult to separate the effects of compaction from those ofeffective stress in the development of high levels of soil strength. Although no direct
Ž .evidence was presented in this study effective stresses were not calculated , the natureof the relationships in Fig. 1, and in particular those for the two hardsetting soils in the
Ž .study, the sandy loam and the loam Fig. 1b and c suggests that compaction rather thaneffective stress, is primarily responsible for the magnitude of PSS. This was borne out
Ž .by Vepraskas 1984 who reported a close correlation between cone index and effectivestress but the contribution of effective stress to the overall soil strength was very smalland depended more on factors such as bulk density and soil type. The nature of therelationships presented in Fig. 1 show that effective stress influences the rate at whichPSS increases but only as the soil dries at higher compaction levels for all the soils. Thisphenomenon is particularly noticeable for soils with low organic matter contents andclay contents of between about 12 and 30%, i.e., those categorised by Mullins et al.Ž .1989 as being susceptible to hardsetting.
( )C.W. Smith et al.rGeoderma 78 1997 93–111104
( ) ( )3.2. Penetrometer soil strength PSS at wilting point y1500 kPa and field capacity( )y10 kPa
As the normal range of bulk densities and water contents varies depending upon soiltexture, establishing the actual effect of clay content on PSS at a constant bulk densityand water content would have limited value. It was decided, therefore, to compare PSSvalues at wilting point and field capacity for a range of selected soils at two levels of
Ž .compaction: high, corresponding to a relative bulk density RBD of 0.9; and moderate,Ž .corresponding to a RBD of 0.8 Figs. 2 and 3 . RBD is simply the actual bulk density
divided by maximum bulk density, the latter being measured by the Proctor Impact testŽ .American Society for Testing and Materials, 1985 . A simple linear and multipleregression was carried out for each compaction level to test the significance of therelationship between PSS and soil physical properties.
A significant relationship exists between PSS and clay content for both levels ofŽ .compaction when soils are at a matric potential of y1500 kPa Fig. 2 . A power
function showed a better fit of the data than a simple linear regression. This demon-strated that at both moderate and high levels of compaction, PSS at wilting pointincreases with increasing clay content up to a point after which PSS declines. These
Ž .results tend to support the results of Ball and O’Sullivan 1982 who showed thatpenetrometer resistance increased with a higher proportion of small particle sizes atconstant water content and bulk density. Similarly, for soils with less than 20% silt plus
Ž .clay, Bennie and Burger 1988 reported an increase in PSS with increasing clay contentfor soils at a water content of 0.1% by volume. However, as both of these studies had alimited range of soil textures, it was not clear whether PSS would continue to riseindefinitely with increasing clay content.
Ž .At field capacity y10 kPa a significant correlation was found between clay contentand PSS for both compaction levels but the correlation was poor, being significant atP-0.05. Interestingly, the correlation improved substantially when loss-on-ignitionŽ . Ž .LOI replaced clay as the independent variable Fig. 3 . The significant relationship
Fig. 2. Relationship between penetrometer soil strength and clay content at a matric potential of y1500 kPafor a range of selected forestry soils at two levels of compaction corresponding to 0.8 and 0.9 of relative bulkdensity.
( )C.W. Smith et al.rGeoderma 78 1997 93–111 105
Ž .Fig. 3. Relationship between penetrometer soil strength and loss-on-ignition LOI at a matric potential ofy10 kPa for a range of selected forestry soils at two levels of compaction corresponding to 0.8 and 0.9 ofrelative bulk density.
between LOI and PSS at wilting point for two levels of compaction was also recordedbut these correlations were not as strong as the correlations between PSS and claycontent at wilting point. This suggests that soil texture and organic carbon content which
Ž .are reflected by LOI Donkin, 1991 are more important in strength development athigher water contents than at lower water contents where the effect of clay content alone
Ž .is dominant. Causarano 1993 found that organic matter increases the strength of wetsoil and decreases the strength of dry soils.
3.3. A quantitatiÕe description of penetrometer soil strength
The graphs presented in the previous section showed that PSS is strongly related tobulk density and water content. An appropriate multiple regression equation was soughtwhich could explain the variation in PSS by using bulk density, mass water content and
Žsoil physical properties as independent variables. Stepwise multiple regression back-. Ž .ward option was employed Draper and Smith, 1981 and various combinations of the
variables were tested based on the nature of the relationships presented in Fig. 1. Asmentioned in the introduction, previous studies have either concentrated on developing
Žthese types of relationships for one soil only Mirreh and Ketcheson, 1972; Cassel et al.,. Ž1978 or a limited range of textures Byrd and Cassel, 1980; Bennie and Burger, 1988;
.Henderson et al., 1988 .Two soils, selected at random, were left out of the regression for model validation
purposes later. The final model selected illustrates that the relationship between PSS andbulk density and water content is strongly influenced by clay content and organic carbonŽ Ž ..Eq. 2 . The regression coefficients, standard errors and multiple correlation coefficientŽ . Ž .R are presented in Table 2. The model in Eq. 2 explains almost 82% of thevariability in PSS which is a considerable achievement considering the large number ofsoils in the study. The standard error of estimate was 0.2436 with a total of 1102 degrees
Ž .of freedom Table 2 .
PSSsyau ybr qc log r qd CLAYye ORG C 2Ž .m b b
( )C.W. Smith et al.rGeoderma 78 1997 93–111106
Table 2Ž . Ž .Regression coefficients and standard errors of the terms in Eqs. 2 – 4
Equation Regression coefficients R
a b c d e
2 y5.0483 y3.6162 32.1616 0.1051 0.2273 0.908))
Ž . Ž . Ž . Ž . Ž .0.6652 0.1985 1.2017 0.0041 0.03823 y17.5797 y4.7966 39.2046 0.1535 0.6207 0.914))
Ž . Ž . Ž . Ž . Ž .1.4174 0.2648 1.7024 0.0078 0.06814 y1.3329 6.9498 0.1549 y7.7943 0.926))
Ž . Ž . Ž . Ž .0.7925 0.2854 0.0109 0.4633
Note that all values of R are significant at P -0.01. Standard errors are shown in brackets.
The model has confirmed the features of the relationships presented so far in that soiltexture and organic carbon appear to have a considerable influence on the nature of thePSS–water content relationship for different compaction levels. The exclusion of otherparticle sizes, including clay plus silt, from the model has shown that clay content is theparticular textural component influencing the relationship. The results support those of
Ž .McCormack and Wilding 1981 who related penetrometer soil strength to bulk density,gravimetric water content and clay content and developed a multiple regression equationrelating these properties to PSS which explained 78% of the variation in soil strength.
Ž .Similarly, Gerard et al. 1982 reported that soil strength, measured by a small conepenetrometer, was significantly correlated with bulk density, void ratio and clay content.The exclusion of clay plus silt from the final model was at variance with a number of
Ž .authors Gerard, 1965; Byrd and Cassel, 1980 who found a significant relationshipbetween clay plus silt and PSS values in combination with compaction level and watercontent.
Ž .The inclusion of organic carbon in Eq. 2 is of interest since previous inspection ofthe PSS–water contentrbulk density relationships of the type presented in Fig. 1showed that organic carbon appeared to have a greater effect on these relationships formore coarsely textured soils. Therefore the stepwise regression procedure was carriedout separately on data sets for soils having above and below 30% clay. The final modelsselected are given below and the regression coefficients, standard errors and multiple
Ž .correlation coefficients R are presented in Table 2.For soils with less than 30% clay:
PSSsyau ybr qc log r qd CLAYqe ORG C 3Ž .m b b
For soils with more than 30% clay:
PSSsyau qbr qc CLAYyd log CLAY 4Ž .m b
The inclusion of organic carbon as an independent variable in the model for soilsŽ Ž ..with less than 30% clay Eq. 3 and its exclusion from the model for soils with more
Ž Ž ..than 30% clay Eq. 4 demonstrates the importance of organic carbon in affecting thePSS of the more coarsely textured soils. For more finely textured soils, organic carbonlevels may need to be much higher to have any effect on PSS. For example, Ohu et al.Ž .1986 reported that organic matter contents of between 10 and 17% decreased the
( )C.W. Smith et al.rGeoderma 78 1997 93–111 107
strength of three soils of varying clay content at any water content at various levels ofsoil compaction. Such high levels of organic matter are well in excess of the organicmatter levels reported in this study. Clay content alone, rather than in combination withorganic carbon, becomes increasingly important in affecting the PSS of the more finely
Ž Ž ..textured soils Eq. 4 . The fact that slightly more of the variation in PSS can beŽ .explained by splitting soils into categories based on clay content suggests that Eqs. 3
Ž .and 4 are most useful for the prediction of PSS from soil physical properties.
Ž .Fig. 4. Predicted relationships solid lines versus measured values of the relationship between penetrometerŽ . Ž . Ž .soil strength PSS and water content at a range of compaction levels for: a sandy clay loam, and b loam.
The broken lines correspond to the best fit line through the data points predicted by the models for theŽ . Ž .individual soils in Eqs. 3 and 4 , and Table 2.
( )C.W. Smith et al.rGeoderma 78 1997 93–111108
The effect of organic matter on PSS values could be due to organic particlesdisrupting the surface tension forces which contribute to soil strength as the soils dryŽ . Ž .Mullins et al., 1989; Causarano, 1993 . Gupta et al. 1989 suggested that organicresidue particles are more effective in separating single-grain particles in sandy soilsthan in finer-textured soils due to the lower surface area of the former. Since the veryhigh organic matter levels in this study were usually associated with higher clay contentsorganic matter is therefore unlikely to have any mechanical effect on the more finely
Ž .textured soils due to the high surface area of the clays Gupta et al., 1989 . It isŽsuggested that the dominant effect on strength properties for fine-textured soils loam
.and finer is soil texture rather than organic matter.
3.4. Model Õalidation
The effect of compaction on the PSS–water content relationship is shown in Fig. 4Ž .for the two soils which were left out of the original stepwise regression, a loam 10A
Ž . Ž .and a sandy clay loam 23A . This was compared to the predicted values solid linesŽ . Ž . Ž . Ž . Žusing the model given in Eq. 3 loam, 10A and Eq. 4 clay loam, 23A Fig. 4a and
.b, respectively . The broken lines indicate the best fit through the data points from theŽ . Ž .individual model for each soil evaluated from Eqs. 3 and 4 and Table 2. In both cases
the model slightly underpredicts PSS at very low water contents and overpredicts PSS athigh water contents. However, the agreement between predicted and measured isremarkably good. It is clear that clay content and organic carbon can be effectivelyutilised to predict the effect of compaction and water content on PSS.
4. Conclusions
The relationships developed have provided an insight into the effect of soil com-Ž .paction and water content on penetrometer soil strength PSS . This study has shown
that PSS is principally related to bulk density, water content, clay content and organiccarbon. For all the soils in this study, PSS increases with increasing bulk density anddecreasing water content, except at lower levels of compaction when there is usually adecline in PSS as the soil becomes very dry. Only small differences in PSS occur atwater contents approaching field capacity and wetter for a range of bulk densities.Differences in PSS at various bulk densities are greatest when soils are dry rather thanwhen they are wet.
For cohesive soils, increasing clay content reduces the rate at which PSS increases asthe soil dries to wilting point and beyond. For non-cohesive soils in the studyŽ .approximately -20% clay plus silt , the rate of increase in PSS as the soils dry issimilar to that for soils with a high clay content, despite changes taking place at verydifferent water contents. At wilting point, higher PSS values are obtained with increas-ing clay content up to about 45 to 50% clay, after which PSS declines. With increasing
Ž .loss-on-ignition LOI contents, PSS values are higher at field capacity, especially athigher bulk densities.
The regression models showed that the relationship between PSS and bulk densityand water content was affected by clay content and organic carbon for soils with less
( )C.W. Smith et al.rGeoderma 78 1997 93–111 109
than 30% clay and by clay content alone for soils with greater than 30% clay. Organiccarbon levels, though ranging from 0.16 to 5.77%, were probably not high enough tohave an influence on PSS for the more clayey soils. A clay content of 30% is suggestedas a threshold value below which moderate changes in organic carbon content can havean appreciable effect on PSS. Although the results in this study relate to disturbedsamples it is believed that the results will reflect the behaviour of field soils since theclay fraction of the majority of South African forestry soils is dominated by kaoliniticclays and hydrous oxides resulting in a lack of macro-structure and the tendency todevelop strong micro-aggregation.
The models can be used to predict the likely effects of soil compaction on themechanical impedance of soils to root penetration and, as a result, to assist in a morerefined assessment of the compaction susceptibility of forestry soils. Coupled withinformation on critical root penetration criteria, the models could serve as an invaluabletool in soil waterrsoil fertility studies. In addition, the correlation between PSS and
Ž .trafficability Knight and Frietag, 1962 will enable a more meaningful appraisal of soiltype in forestry terrain classifications.
Acknowledgements
The authors are indebted to Mrs. Mary Galbraith and Mr. Innocent Mchunu for theirtechnical assistance throughout this project. Mrs. Galbraith is also acknowledged for herhelp in the preparation of the figures.
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