Research Journal of Environmental and Earth Sciences 4(7): 688-696, 2012
ISSN: 2041 0492
© Maxwell Scientific Organization, 2012
Submitted: April 29, 2012
Accepted: June 08, 2012
Published: July 25, 2012
Characterization of Erodibility Using Soil Strength and Stress-Strain
Indices for Soils in Some Selected Sites in Imo State
C.C. Egwuonwu and N.A.A. Okereke
Department of Agricultural Engineering, Federal University of Technology, Owerri, Nigeria
Abstract: In this study, initial soil strength indices (qu) and stress-strain characteristics namely failure strain (εf);
area under the stress-strain curve up to failure (Is) and stress-strain modulus between no load and failure (Es) were
investigated as potential indicators for characterizing the erosion resistance of two compacted soils namely Sandy
Clay Loam (SCL) and Clay Loam (CL) in some selected sites in Imo State, Nigeria. The unconfined compressive
strength (used in obtaining strength indices) and stress-strain measurements were obtained as a function of moisture
content in percentage (mc %) and dry density (γd). Test were conducted over a range of 8 to 30% moisture content
and 1.0 to 2.0 g/cm3 dry density at applied loads of 20, 40, 80, 160 and 320 kPa. Based on the results, it was found
out that initial soil strength alone was not a good indicator of erosion resistance. For instance in the comparison of
exponents of mc % and γd for jet index or erosion resistance index (Ji) and the strength measurements, qu and Es
(Table 1) agree in signs for mc %, but are opposite in signs for γd. Therefore there is an inconsistency in exponents
making it difficult to develop a relationship between the strength parameters and Ji for this data set. In contrast, the
exponents of mc % and γd for Ji and εf and Is are opposite in signs (Table 1), there is potential for an inverse
relationship. The measured stress-strain characteristics however, appeared to have potential in providing useful
information on erosion resistance. The models developed for the prediction of the extent or the susceptibility of soils
to erosion and subjected to sensitivity test on some selected sites as shown in Table 2 achieved over 90% efficiency
in their functions.
Keywords: Characterization, erodibility, Imo state, indices, Nigeria, selected sites, soil strength, soils, stress-strain
and land management:. In many of these engineering
projects not only is the erodibility of the soil at the
surface of interest, but also the erodibility with depth
(Hanson, 1996). Earth spillways are an example in
which erosion exposes different materials with depth
and the erodibility of these materials is important in the
performance of the spillways under concentrated flow
conditions (Hanson, 1996). Measuring erodibility
directly is often difficult. Therefore development of
measurable soil parameters that indicate erodibility is
attractive (Elliot et al., 1990).
Soil strength indices have been a common soil
parameter investigated for characterization of soil
erodibility. Strength indices are commonly used
because they can be easily and rapidly obtained,
measured incrementally with depth and related to other
soil parameters that affect soil erodibility such as dry
density (γd) and water content (mc %). Soil strength
indices are also appealing because soil erosion is a
function of the forces applied by the flow and resistance
to erosion is offered by bonding forces between soil
particles and other materials in the soil matrix (Hanson,
1996). Since the state of bonding is manifested in the
soil strength, resistance to erosion should be
INTRODUCTION
Soil erosion is one of the most important physical
and
socio-economic
problems
affecting
our
development in this part of the world today. Apart from
the fact that it constitutes a menace to the environment
and despite its destruction of our infrastructure,
highways etc and soil erosion creates a major problem
on our agricultural land thereby interfering seriously
with mass food production hence the need for
predicting the susceptibility of soils to erosion.
An accurate estimate of soil erodibility (the
susceptibility or vulnerability of soil to erosion) is
important to engineers involved in the design of water
management projects. Defining soil erodibility,
however, is a difficult task. This is because soil
detachment is a complex function of both soil and
eroding fluid properties (Egwuonwu and Uzoije, 2009;
Akintola, 2001).
Predicting the susceptibility of a soil to erosion
prior to a concentrated flow event is an important
problem in many engineering projects such as
irrigation, channels, levees, highways, railways,
spillways, construction sites, mining area reclamation
Corresponding Author: C.C. Egwuonwu, Department of Agricultural Engineering, Federal University of Technology, Owerri,
Nigeria
688
Res. J. Environ. Earth Sci., 4(7): 688-696, 2012
Soil testing: Test was conducted on the compacted
samples. Strength and stress-strain values were
measured with the unconfined compression test.
The unconfined compressive tests were conducted
in accordance with ASTM D2166. In addition to the
unconfined compressive strength (qu), stress-strain
characteristics namely failure strain (εf), area under the
stress-strain curve up to failure (Is) and stress-strain
modulus between no load and failure (Es) were
determined for the unconfined compressive test.
Unconfined compressive tests were continued until the
load values decreased with increasing strain or until
20% strain was reached.
The samples of soil (Sandy Clay Loam (SCL) and
Clay Loam (CL)) were tested for resistance to
erodibility using a submerged jet testing device. Water
was fed under a constant head of 0.91 m, through a
circular nozzle, 13 mm in diameter, at a set height of
0.22 m above a level bed of prepared soil. The rate of
scour was monitored with time. The erosion resistance
of the samples was based on a jet index (Ji). The lower
the Ji values the less erosion occurred and the more
resistant the material (Hanson, 1991).
characterized by the measurement of soil strength.
Although soil strength indices have been used to
characterize erodibility of soils, their success have been
limited (Elliot et al., 1990; Parker et al., 1995) hence
the need for the use of more quantifiable parameters of
soil such as strength and stress-strain characteristics.
Unconfined compressive strength, triaxial shear test,
vane shear strength, pocket penetrometer as well as
other tests have been used to characterize soil strength
(Nearing and West, 1988).
The objectives of the study are: To measure and
observe the relationship between soil strength indices,
stress-strain characteristics and changes in moisture
content and dry density for the selected sites and to
develop models for predicting the susceptibility or
extent of soils to erosion in the selected sites.
MATERIALS AND METHODS
Study area: Characterization of erodibility using soil
strength and stress-strain indices was studied for some
selected towns in Imo State Nigeria namely: Ideato,
Mbaise and Okigwe. These towns lie between latitude
5.3 to 6.5oN and longitude 6.8 to 8.1oE and are within
the tropical rainforest zone. The study was carried out
in February 2011.
Data analysis: A comparison of nonlinear power curve
regression fits or power equation or models for jet
index (Ji), failure strain (εf), area under the stress-strain
curve up to failure (Is), unconfined compressive
strength (qu) and stress-strain modulus between no load
and failure (Es) versus the variables mc % and γd was
developed. The non linear power curve function served
as potential for functional relationships.
Multiple Linear Regressions in conjunction with
Naïve-Gauss Elimination Method and Gauss-Jordan
Matrix Inverses were used to obtain the models.
The coefficient of determination (r2) was computed
for each developed model to ascertain the level of
accuracy or exactness of each model.
Soil materials: The soils used in this study were a
Sandy Clay Loam (SCL) and a Clay Loam (CL)
obtained from three (3) sites in Imo State, Nigeria
namely Imo:
•
•
•
Okigwe; Imo
Mbaise; Imo
Ideato
The influence of compaction (mc % and γd) on
resistance to erosion of these soils was reported in
Hanson and Robinson (1993) and Hanson (1992, 1993).
RESULTS
Soil preparation: Soil samples were prepared by static
load compaction. Thirty test samples of each soil were
compacted using a device similar to a fixed ring
consolidometer. Static pressure was applied to the soil
by pneumatic bellows. Loads of 20, 40, 80, 160 and 320
kPa were applied to the samples. The size of prepared
soil sample was 445 mm in diameter and the final
height varied from 100 to 200 mm depending on the
load applied and the mc %. Samples were compacted at
various mc % ranging from 8 to 30% for each load. The
soils were wet by spraying to various mc % mixed
thoroughly and stored in polyethylene bags for 24 h to
allow the water to permeate through the soil.
The strength test and stress-strain results as well as
the jet index result for SCL and CL soils are shown in
Table 3-8 for the sites selected in Imo State. The
comparison of nonlinear power curve regression fits for
Ji, εf, Is, qu and Es versus the variables mc % and γd is
shown in Table 1. The prediction of the extent or the
susceptibility of soils to erosion on some selected sites
using the Ji models developed is illustrated in Table 2.
The predicted Ji versus qu and Ji versus εf for SCL
and CL soils (Imo) in Fig. 1 to 4 and Fig. 5 to 8,
respectively.
689
Res. J. Environ. Earth Sci., 4(7): 688-696, 2012
SCL SOIL IMO (1)
0.20
0.18
0.16
Predicted Ji
0.14
0.12
0.10
0.08
0.06
0.04
0.02
0
0
0.02 0.04 0.06 0.08 0.10 0.12 0.14 0.16 0.18 0.20
εf
Fig. 1: Predicted Ji Vs εF for scl soil, Imo (1)
CL SOIL IMO (2)
0.14
0.12
Predicted Ji
0.10
0.08
0.06
0.04
0.02
0
0.02
0
0.04
0.06
0.08
0.10
0.12
εf
Fig. 2: Predicted Ji VS εF for cl soil, Imo (2)
SCL SOIL IMO (3)
0.25
Predicted Ji
0.20
0.15
0.10
0.05
0
0
0.01
0.02
0.03
εf
Fig. 3: Predicted Ji Vs εF for scl soil, Imo (3)
690
0.04
0.05
0.06
0.07
Res. J. Environ. Earth Sci., 4(7): 688-696, 2012
0.25
SCL SOIL IMO (1)
CL SOIL IMO (2)
SCL SOIL IMO (3)
Predicted Ji
0.20
0.15
0.10
0.05
0
0.02
0
0.04
0.06
εf
0.08
0.10
0.12
Fig. 4: Combined data for Scl and Cl soils for predicted Ji Vs εF, Imo state (3)
SCL SOIL IMO (1)
45
40
Predicted Ji
35
30
25
20
15
10
5
0
0
0.02 0.04 0.06 0.08 0.10 0.12 0.14 0.16 0.18 0.20
q u(KPa)
Fig. 5: Predicted Ji VS qu for scl soil, Imo (1)
CL SOIL IMO (2)
120
100
Predicted Ji
80
60
40
20
0
0
0.02
0.04
0.06
q u(KPa)
Fig. 6: Predicted Ji Vs Qu for cl soil, Imo (2)
691
0.08
0.10
0.12
Res. J. Environ. Earth Sci., 4(7): 688-696, 2012
CL SOIL IMO (3)
60
50
Predicted Ji
40
30
20
10
0
0
0.01
0.02
0.04
0.03
0.05
0.06
0.07
q u(KPa)
Fig. 7: Predicted Ji Vs Qu for scl soil, Imo (3)
120
SCL SOIL IMO (1)
CL SOIL IMO (2)
SCL SOIL IMO (3)
Predicted Ji
100
80
60
40
20
0
0
0.02
0.04
0.06
q u(KPa)
0.08
0.10
0.12
Fig. 8: Combined data for scl and cl soil for predicted Ji Vs Qu, Imo state
Table 1: Power curve functions of parameters Ji, qu, εf, Is and Es for
SCL and CL soils Imo state
Imo (1) SCL soil
Ji = 3.60* 103 (mc)-4.30 (γd)-3.07 r2 = 0.98
εf = 9.68* 10-6 (mc)2.67 (γd)3.10 r2 = 0.95
Is = 2.0 * 10-2 (mc)0.28 (γd)8.23 r2 = 0.93
qu = 27.18 (mc)-1.96 (γd)8.58 r2 = 0.94
Es = 1.26 * 105 (mc)-2.44 (γd)2.55 r2 = 0.88
Imo (2) CL soil
Ji = 39.24 (cm) -2.48 (γd)-4.11 r2 = 0.96
εf = 1.21 * 10-4 (mc)1.50 (γd)4.23 r2 = 0.95
Is = 8.83 * 10-3 (mc)0.55 (γd)9.27 r2 = 0.91
qu = 5.66* 102 (mc) -1.94 (γd) 7.63 r2 = 0.92
Es = 4.06 * 105 (mc) -2.76 (γd)-4.99 r2 = 0.85
Imo (3) SCL soil
Ji = 22.94 (mc) -2.57 (γd) -1.85 r2 = 0.93
εf = 5.36 * 10-6 (mc)2.95 (γd)2.95 r2 = 0.96
Is = 3.35 * 10-4 (mc)1.69 (γd)8.53 r2 = 0.93
qu = 13.26 (mc) -1.08 (γd) 7.87 r2 = 0.96
Es = 1.84 * 105 (mc) -2.80 (γd)3.65 r2 = 0.81
Table 2: Prediction of the extent or the susceptibility of soils to
erosion on some selected sites using the Ji model developed
for Imo state
Location
Average mc % Average (γd)
Ji model
Imo (1) – A
13.90
1.25
0.022
Imo (1) – B
15.30
1.87
0.004
Imo (2) – A
14.40
1.30
0.018
Imo (2) – B
18.40
1.73
0.003
Imo (3) – A
11.10
1.60
0.020
Imo (3) – B
14.50
1.51
0.011
DISCUSSION
The strength indices (qu) for the SCL and CL soils
for the sites selected followed similar trends (Table 3 to
5). Strength indices increased as the γd increased for a
given mc and as the mc decreased for a given γd (the
asterixed values * and ** in Table 3 to 5). It was
observed that qu, εf, Is and Es increased as γd increased.
692
Res. J. Environ. Earth Sci., 4(7): 688-696, 2012
The values of qu and Es decreased as mc % increased
for a constant γd, whereas εf and Is tended to increase
(the asterixed values * and ** in Table 3 to 5). . At low
mc %, the soil tended to fail by brittle fracture. At high
mc %, the soil failed plastically.
The relationship of εf, Is and Es to γd and mc % for
the same set of samples shown in the tables listed for
strength indices are shown in Table 3 to 5. The Es
values were observed to have similar relationship as the
strength indices (qu) had to γd (Table 3 to 5). Soil
strength indices decreased with increases in mc% (the
asterixed values * and ** in Table 3 to 5), whereas the
resistance to erosion increased with increases in mc %
within the same range ((the asterixed values ** and ***
in Table 6 to 8). The conclusion is that the soil strength
indices alone, although affected by mc % and γd, would
make poor erosion characterization indicators.
The stress-strain characteristics εf and Is, tended to
increase with increases in γd and mc % (Table 3 to 5)
and these concur with that of the erosion resistance
index (Ji) (Table 6 to 8). Whereas Es tended to increase
with γd and decrease with mc %. Based on these test
results, Es has the same potential problems as strength
indices, qu. However, εf and Is have potential for
indicating erosion resistance of a soil.
Table 4: Strength and stress-strain indices for CL soil as a function of
mc % and γd for Imo state (2)
mc(%) γd (g/cm3)
qu (kPa)
εf
Is (kPa)
Es (kPa)
14.5
1.09
10
0.010
0.10
500
15.6
1.10
9
0.015
0.10
500
17.5** 1.14
10
0.018
0.20
600
20.0
1.26
12
0.038
0.40
500
20.9
1.28
10
0.040
0.60
400
21.6
1.30
7
0.041
0.40
300
10.8
1.10
10
0.006
0.08
500
13.5
1.18
15
0.008
0.18
750
15.4
1.20
15
0.010
0.20
700
17.6** 1.24
18
0.020
0.32
800
20.7
1.37
18
0.060
1.00
500
21.4
1.53
35
0.100
4.00
400
9.5
1.17
15
0.007
0.14
750
11.8
1.21
18
0.010
0.20
1000
14.2
1.26
20
0.012
0.28
1300
16.3
1.33
25
0.020
0.38
1300
17.5** 1.40
38
0.032
0.80
1500
20.0
1.55
45
0.080
4.00
800
21.9
1.60*
40
0.140
6.00
300
9.0
1.33
30
0.010
0.28
1900
10.8
1.35
40
0.018
0.32
2000
11.8
1.38
30
0.026
0.40
1800
16.5
1.50
70
0.034
1.20
2200
19.4
1.60*
70
0.080
4.00
1000
20.4
1.65
80
0.120
8.00
500
0.014
0.70
3000
11.8
1.47
70
0.038
3.00
3000
15.2
1.61*
100
0.060
4.00
2200
17.6** 1.64
100
0.080
6.00
2000
18.0
1.67
110
0.100
8.00
1800
18.5
1.72
120
Table 3: Strength and stress-strain indices for
of mc % and γd for Imo state (1)
γd (g/cm3)
qu (kPa) εf
mc (%)
8.0**
1.17
02
0.007
12.6
1.26
07
0.010
13.7
1.27
05
0.012
15.4
1.30
07
0.020
15.7
1.39
12
0.040
18.2
1.58*
18
0.120
19.2
1.67
25
0.200
9.1
1.29
08
0.008
11.7
1.31
10
0.100
14.9
1.49
18
0.040
15.3
1.58*
25
0.070
17.0
1.67
25
0.160
17.9
1.71
40
0.180
18.7
1.71
40
0.200
8.1**
1.31
10
0.010
11.6
1.42
20
0.015
13.8
1.60
38
0.050
15.0
1.69
40
0.100
15.6
1.78
60
0.100
17.0
1.82
70
0.120
8.1**
1.41
25
0.008
9.5
1.44
25
0.010
10.7
1.58*
55
0.010
12.3
1.62
48
0.020
14.2
1.83
80
0.080
8.1**
1.58*
60
0.013
10.0
1.64
70
0.018
11.2
1.71
80
0.025
12.2
1.81
100
0.040
13.7
1.88
100
0.080
Table 5: Strength and stress-strain indices for SCL soil as a function
of mc % and γd for Imo state (3)
mc(%) γd (g/cm3) qu (kPa) εf
Is (kPa)
Es (kPa)
9.0
1.15
0
0.010
0.01
100
12.0** 1.20
3
0.013
0.17
300
14.0
1.28
6
0.016
0.25
500
15.3
1.35
10
0.028
0.37
510
17.0
1.42
12
0.053
0.55
440
18.5
1.60*
20
0.150
2.80
250
20.0
1.65
22
0.180
4.50
100
8.0
1.30
12
0.010
0.20
800
12.0** 1.35
13
0.012
0.31
700
13.5
1.50
20
0.033
0.75
1100
15.6
1.60*
28
0.080
2.20
70-0
16.5
1.67
33
0.130
3.20
480
18.0
1.70
38
0.150
4.80
300
21.0
1.75
32
0.200
6.00
100
8.4
1.35
17
0.007
0.24
1000
10.0
1.42
20
0.010
0.34
1400
12.1** 1.60*
40
0.028
1.20
1800
14.2
1.70
48
0.076
2.96
1000
15.0
1.78
60
0.110
4.80
800
17.0
1.83
60
0.200
6.00
300
9.0
1.40
22
0.010
0.3
1400
10.0
1.45
28
0.010
0.39
1600
11.6
1.60*
45
0.020
1.00
1800
15.0
1.72
45
0.094
3.00
800
17.5
1.83
60
0.120
6.00
300
8.1
1.50
40
0.010
0.40
2300
10.0
1.65
70
0.015
1.00
2600
12.0** 1.70
70
0.035
2.20
2000
1450
13.5
1.80
78
0.070
4.00
800
15.0
1.88
90
0.120
6.00
SCL soil as a function
Is (kPa)
0.08
0.20
0.22
0.30
0.40
2.50
4.00
0.20
0.25
0.80
1.80
3.00
4.00
6.00
0.20
0.40
1.80
3.00
4.00
6.00
0.35
0.40
0.80
1.50
5.50
0.50
1.00
2.00
3.00
6.00
Es (kPa)
200
400
380
500
500
300
100
500
600
800
800
350
350
100
1000
1200
1200
800
1000
500
1800
1800
1700
1800
1000
2900
2600
2300
1800
1200
693
Res. J. Environ. Earth Sci., 4(7): 688-696, 2012
Table 6: Values of Ji for SCL soil as a function of mc % and γd for
Imo state (1)
Ji
mc (%)
γd (g/cm3)
13.0
1.29***
0.020
12.6**
1.40
0.020
12.1
1.48
0.020
11.1
1.69
0.020
10.0
1.88
0.020
13.3
1.36
0.018
10.9
1.86
0.017
14.1
1.29***
0.016
13.7
1.40
0.016
12.6**
1.61
0.016
10.9
1.84
0.016
12.5**
1.71
0.015
15.9
1.28***
0.012
15.3
1.40
0.012
13.9
1.60
0.012
12.6**
1.80
0.012
12.0
1.90
0.012
16.3
1.43
0.010
16.2
1.55
0.008
15.3
1.65
0.008
13.0
1.90
0.008
16.2
1.73
0.006
15.0
1.80
0.006
13.7
1.88
0.006
14.6
1.87
0.005
17.4
1.83
0.004
15.3
1.86
0.004
14.3
1.90
Table 8: Values for Ji for
Imo state (3)
mc (%)
12.4
11.6
10.8
12.8
11.5
10.7
13.8
12.5**
11.6
14.1
13.0
11.0
12.9
16.1
14.2
13.0
12.4**
14.7
17.5
15.8
12.4**
15.8
17.5
14.3
16.5
13.8
SCL soil as a function of mc % and γd for
γd (g/cm3)
1.38
1.56***
1.71
1.35
1.58
1.81
1.32
1.60
1.75
1.32
1.56***
1.88
1.40
1.33
1.56***
1.76
1.86
1.53
1.46
1.56***
1.94
1.72
1.68
1.85
1.84
1.94
Ji
0.021
0.021
0.021
0.020
0.020
0.020
0.017
0.017
0.017
0.016
0.016
0.016
0.014
0.012
0.012
0.012
0.012
0.011
0.009
0.009
0.007
0.006
0.006
0.004
0.004
A comparison of nonlinear power curve regression
fits for Ji, εf, Is, qu and Es versus the variables mc% and
γd are shown in Table 1. The nonlinear power curve
function served as potential for functional relationships
and was consistently a good fitting function in all cases
and allowed comparison between parameters.
The exponents of mc % and γd indicate their
functional relationship to Ji, εf, Is, qu and Es. Based on
the exponents Ji decreases as mc % increases holding γd
constant. This comparison indicates that even though
the exponents of mc % and γd for Ji and εf and Is are
opposite in signs, there is potential for an inverse
relationship. In contrast, the comparison of the
exponents for mc % and γd for Ji and the strength
measurements, qu and Es agree in signs for mc %, but
are opposite in signs for γd. Therefore, there is an
inconsistency in exponents making it difficult to
develop a relationship between the strength parameters
and Ji for this data set.
The jet index (Ji) test results and the strength (qu)
and stress-strain (εf) test results are independent data
sets, a prediction of Ji can be made for the strength and
stress-stain data using the functional relationships in
Table 1 for the SCL and CL soil. As an example of the
potential relationships for Ji versus εf and qu a
comparison of the predicted Ji versus εf and predicted Ji
versus qu for Imo State is shown in Fig. 1 to 4 and Fig.
5 to 8, respectively for SCL and CL soil.
These plots show that there does appear to be a
general trend as qu increases Ji decreases (Fig. 5 to 7),
Table 7: Values for Ji for CL soil as a function of mc % and γd for Imo
state (2)
mc (%)
γd (g/cm3)
Ji
17.3
1.21
0.0120
15.0
1.3
0.0120
13.6
1.42
0.0120
13.0
1.51***
0.0120
12.4
1.63
0.0120
10.6
1.75
0.0120
17.0**
1.26
0.0100
15.9
1.32
0.0100
13.6
1.40
0.0100
13.1
1.50***
0.0100
12.4
1.64
0.0100
11.0
1.74
0.0100
19.1
1.34
0.0080
15.5
1.42
0.0080
15.0
1.50***
0.0080
14.3
1.60
0.0080
12.6
1.71
0.0080
20.5
1.42
0.0070
17.1**
1.47
0.0070
19.6
1.50***
0.0060
16.6
1.60
0.0060
13.8
1.73
0.0060
20.5
1.58
0.0055
18.3
1.60
0.0058
16.9
1.60
0.0058
15.0
1.68
0.0050
18.4
1.64
0.0050
19.8
1.70
0.0040
18.7
1.74
0.0040
17.0**
1.71
0.0040
14.5
1.74
694
Res. J. Environ. Earth Sci., 4(7): 688-696, 2012
but there is quite a bit of scatter. For a parameter to be
effective in predicting erodibility, it must also be
consistent between soils. Combing the data in Fig. 1 to
3 for predicted Ji versus εf brings the data for SCL and
CL soils together (Fig. 4). However, combining the data
in Fig. 5 to 7 for qu versus Ji does not bring the data
together (Fig. 8).
Using the erosion prediction model Ji obtained for
the three sites in Imo State, two locations in each of the
sites were each tested for the mc % and γd. The two
sites included one that had visibly undergone erosion
(A) and one that had not visibly undergone or partially
undergone erosion (B). The parameters mc % and γd
were obtained at random locations (20) on the site. The
average values of the parameter were imputed in the Ji
model to ascertain the extent of or the susceptibility of
soils to erosion and to also verify the efficacy or
exactness of the model obtained. This is shown in Table
2.
Based on the jet index (Ji), a highly erodible soil
will have a Ji of approximately 0.020 whilst an erosion
resistant soil will have a Ji of approximately 0.002.
From Table 2; Imo 1A, Imo 2A and Imo 3A had Ji
values close to 0.020 or slightly above it. This explains
the adverse extent of erosion on these soil to the extent
it was glaringly visible. Imo 1B and Imo 2B had Ji
values close to 0.002 with no visible signs of erosion.
These soils are still erosion resistant. However, with a Ji
value of 0.011 for Imo 3B, is an indication of the
susceptibility of the soil to erosion even though it is not
yet prominent. However, if nothing is done to curb the
erosive tendencies at this stage of Imo 3B will subject
the soil to severe erosion.
Furthermore, the predicted Ji versus qu for SCL and
CL (Fig. 5 to 7) soils does not indicate potential for a
relationship between soils. For a parameter to be
effective in predicting erodibility it must also be
consistent between soils. However, the combined data
in Fig. 5 to 7, for Ji and qu does not bring the data
together (Fig. 8). This does not discard soil strength as a
potential indicator, but it does indicate that it should not
be solely relied upon for prediction of soil erodibility.
The results from compacted samples of SCL and
CL soils indicate that stress-strain characteristics
namely failure strain (εf) and area under the stress strain
curve up to failure (Is) are helpful in predicting
erodibility. The stress-strain indices (εf and Is) increased
with increases in both γd and mc% (Table 3 to 5). The
resistance to erosion (Ji) of the SCL and CL soil also
increased with increase in both γd and mc % within the
same range (Table 6 to 8).
εf and Is had similar functional relationships to Ji
(Table 1). Even though, the exponents of mc % and γd
for Ji and εf and Is are opposite in signs, there is
potential for an inverse relationship. The predicted Ji
versus εf for SCL and CL soils (Fig. 1 to 3) indicate
potential for a relationship between stress-strain and
erodibility for a soil and between soils. The combined
data in Fig. 1 to 3 for predicted Ji versus εf brings the
data for SCL and CL soils together (Fig. 4). These
results indicate that stress-strain characteristics should
be included alongside strength indices in studies when
developing relationships between soil erodibility and
other soil parameters.
The models developed for the prediction of the
extent or the susceptibility of soils to erosion and
subjected to sensitivity test on some selected sites as
shown in Table 2 achieved over 90% efficiency in their
functions.
From the discoveries made in this project, it is
appropriate to recommend the following:
CONCLUSION AND RECOMMENDATIONS
The soil strength indices (qu) for SCL and CL soil
in the sites increased with increases in dry density (γd)
(Table 3 to 5). The resistance to erosion (Ji) of the SCL
and CL soils in the region also increased with increases
in γd (Table 6 to 8). qu decreased with increases in
moisture content (mc %) (Table 3 to 5), whereas Ji
increased with increases in mc % within the same range
(Table 6 to 8).
Soil strength (qu) and erodibility (Ji) are both
affected by mc % and γd, but not necessarily in the
same functional manner (Table 1). The comparison of
the exponents for mc % and γd for Ji and the strength
measurements; qu and Es agree in signs for mc %, but
are opposite in signs for γd. Therefore, there is an
inconsistency in exponents making it difficult to
develop a relationship between the strength parameters
and Ji for the data set.
•
•
695
Similar studies should be extended to other areas in
the country that are prone to erosion in order to
develop models that will ascertain the
susceptibility or extent of soils to erosion. Since the
control of erosion is capital intensive, early
detection will minimize cost and ultimately save
the environment from its menace.
Studies in soil erosion are usually intensive and
expensive in terms of finance. Government through
institutions, agencies and parastatals should make
available adequate funds to sustain such studies.
With proper funding results of such studies will go
a long way in totally annihilating the menace of
soil erosion in our environment if sincerely
implemented?
Res. J. Environ. Earth Sci., 4(7): 688-696, 2012
•
Hanson, G.J., 1991. Development of a jet index to
characterize erosion resistance of soils in earthen
spillways. Trans. ASAE, 34(5): 2015-2020.
Hanson, G.J., 1992. Erosion resistance of compacted
soils. TRB Transport Res., 1369: 26-30.
Hanson, G.J., 1993. Effects of Consolidation on Soil
Erodibility. ASAE Paper No St. Joseph, Mich., pp:
93-2091.
Hanson, G.J., 1996. Investigating soil strength and
stress-strain indices to characterize erodibility.
Trans. ASAE, 39(3): 883-890.
Hanson, G.J. and K.R. Robinson, 1993. The influence
of soil moisture and compaction on spillway
erosion. Trans. ASAE, 36(5): 1349-1352.
Nearing, M.A. and L.T. West, 1988. Soil strength
indices as indicators of consolidation. Trans.
ASAE, 31(2): 471-475.
Parker, D.B., T.G. Michel and J.L. Smith, 1995.
Compaction and water velocity effects on soil
erosion in shallow flow. J. Irrigat. Drainage Engrg.
ASCE, 121(2): 170-178.
Soil strength should not be solely relied upon for
measuring erodibility of soils. However, other
parameters i.e., stress-strain characteristics etc
should be included alongside strength indices when
developing relationships between soil erodibility
and other soil parameters.
REFERENCES
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