International Journal of Geosciences, 2012, 3, 111-116
http://dx.doi.org/10.4236/ijg.2012.31013 Published Online February 2012 (http://www.SciRP.org/journal/ijg)
Tropical Clayey Sand Soil’s Behaviour Analysis and Its
Empirical Correlations via Geophysics Electrical
Resistivity Method and Engineering Soil Characterizations
Andy Anderson Bery, Rosli Saad
Geophysics Section, School of Physics, Universiti Sains Malaysia, Penang, Malaysia
Email: andersonbery@yahoo.com.my
Received July 12, 2011; revised September 9, 2011; accepted November 3, 2011
ABSTRACT
Soil is a heterogeneous medium which consist of liquid, solid, and gaseous phases. The solid and liquid phases play an
essential role in soil spontaneous electrical phenomena and in behaviour of electrical fields, artificially created in soil.
Soil electrical properties are the parameters of natural and artificially created electrical fields in soils and influenced by
distribution of mobile electrical charges, mostly inorganic ions, in soils. Geophysical method of electrical resistivity
was used for measuring soil electrical properties and tested in different soil studies. Laboratory tests were performed for
the numbers of clayey sandy soil samples taken from Batu Uban area. The empirical correlations between electrical
parameter, percentage of liquid limit, plastic limit, plasticity index, moisture content and effective soil cohesion were
obtained via curvilinear models. The ranges of the soil samples are changed between 229 m to 927 m for resistivity
(ρ), 6.01 kN/m2 to 14.27 kN/m2 for effective soil cohesion (C'), 35.08 kN/m2 to 51.47 kN/m2 for internal fiction angle
'), 38% to 88% for moisture content (W), 33% to 78% for liquid limit (WL), 21% to 43% for plastic limit (Wp) and
11% to 35% for plasticity index (PI). These empirical correlations model developed in this study provides a very useful
tool to relate electrical resistivity with effective cohesion, internal friction angle (strength), void ratio, porosity, degree
of saturation, moisture content, liquid limit, plastic limit and plasticity index in context of medium-grained of clayey
sandy soil that is, its fluid behaviours.
Keywords: Empirical Correlations; Regression Coefficient; Resistivity; Moisture Content; Fluid Behaviours
1. Introduction
Natural geomaterials whose skeletons form the primary
structure to supports loadings consists of various solid
mineral particles with diverse size, shape and arrange-
ment, while multiple phases of pore fluids fill in their
voids, such as air, water and solutions [1]. Many kinds of
electrical fields and potentials are often simultaneously
observed in natural soil; thus, it is difficult to know what
mechanism is responsible for their formation. Electrical
conductivity and resistivity of soils have been investiga-
ted in a large number of studies, which can be divided in-
to three groups. The first group includes laboratory stud-
ies of electrical conductivity and dielectric constant of
different dispersed media (including soils) with electro-
magnetic waves [1,2]. These studies help to develop re-
lationship between electrical parameters, quantitative and
qualitative compositions of electrolytic solutions [2]. The
relationships were enhanced by the studies of soil elec-
trical parameters with constant electrical field. For some
diluted soil solutions and groundwater, the methods are
developed to calculate electrical conductivity from the
solution compositions. Electrical conductivity of the ex-
tracted soil solutions have been studied vigorously [3].
The second group of studies is devoted to laboratory mea-
surements of surface electrical conductivity. The surface
electrical conductivity is a major parameter describing
structure of electrical double layer and its ion composi-
tion. There is only limited special research with experi-
mental measurements of surface electrical conductivity
in soils [4]. The third group of studies includes measure-
ments of electrical conductivity of soils, rocks, and sedi-
ments in situ with various geophysical methods [4,5].
In the general engineering sense, soils defined as the
uncemented aggregate of mineral grains and decayed or-
ganic matter (solid particles) along with the liquid and gas
that occupy the empty space between the solid particles.
Soil is used as a construction material in various engi-
neering projects, and it supports structural foundations
[6]. Thus civil engineers must study the properties of soil
such as its origin, grain-size distribution, ability to drain
water, shear strength, compressibility and so on. The in-
situ behaviour of soils is complex because it is heavily
C
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A. A. BERY ET AL.
112
dependent upon numerous factors. To acquire appropri-
ate understanding, it is necessary to analyze them not
only through geophysics and geotechnical engineering
skills but also through other associated disciplines like
geology, geomorphology, climatology and other earth and
atmosphere related sciences [7]. It is understood that geo-
technical problems with socio-economic impacts like land-
slides can be addressed within a framework that accounts
for behavioural features in natural soils [7]. Research is
actively taking place in many countries, each focusing on
natural deposits of local importance, and a unified frame-
work that can account for all important effects is still
being developed [6,7]. Although the development of this
unified framework requires a huge and joint effort from
as many sources as possible, by means of the best of their
academic and technical skills and using best possible
equipments.
In this study, the clayey sand behaviour was estimated
through the analysis of their engineering characteriza-
tions. The objective of this study intents the empirical
correlations between soil’s electrical resistivity (ρ), effec-
tive soil cohesion (C' ), moisture content (W), void ratio
(e), porosity (n), degree of saturation (S), liquid limit
(WL), plastic limit (WP) and plasticity index (PI) in con-
text of medium-grained clayey sandy soils. Prior of that,
the analysis was conducted to develop practically appli-
cable of empirical correlations to study the role of water
in geosciences perspective.
2. Geography and Geology of Penang Island
Penang is the second smallest and one of the 13 states of
Peninsular Malaysia. It is situated in the northern region
and constituted by two geographically different entities—
an island (area: 293 km²) called Penang Island and a por-
tion of mainland called Seberang Perai (area 738 km²)
connected, besides a regular ferry service, through a
13.5 km long Bridge. The island is located between
latitudes 5˚8'N and 5˚35'N and longitudes 100˚8'E and
100˚32'E.
The climate is tropical with the average mean daily
temperature about 27˚C and mean daily maximum and
minimum temperature ranging between 31.4˚C and 23.5˚C
respectively. However, the individual extremes are 35.7˚C
and 23.5˚C respectively. The mean daily humidity varies
between 60.9% and 96.8%. The average annual rainfall is
about 267 cm and can be as high as 325 cm. The two rai-
ny seasons are south-west monsoons from April to Octo-
ber and north-east monsoons from October to February.
The terrain consists of coastal plains, hills and mountains.
There are large forest cover and the population concen-
tration on the eastern half of the Penang Island. There are
three main geological formations in Penang and their dis-
tribution is as given in Figure 1.
The major portion of Penang Island is underlain by ig-
neous rocks. All igneous rocks are granites in terms of
Streckeisen classification [8]. These granites can be clas-
sified on the basis of proportions of alkali feldspar to to-
tal feldspars. On this basis granites of Penang Island are
further divided into two main groups: the North Penang
Pluton approximately north of latitude 5˚23' and the Sou-
th Penang Pluton. In the northern part of the island, the
alkali feldspars that generally do not exhibit distinct cro-
ss-hatched twining are orthoclase to intermediate micro-
cline in composition. In the southern region, they gener-
ally exhibit well-developed cross-hatched twining and
are believed to be microcline. The North Penang Pluton
has been divided into Feringgi Granite, Tanjung Bungah
Granite and Muka Head micro granite. The South Penang
Pluton has been divided into Batu Maung Granite and
Sungai Ara Granite.
3. Data Acquisition and Methods
In geophysics, electrical resistivity of any material is
defined as the electrical resistance of a soil sample with a
cross section of unit area and with unit length as shown in
Equation (1). In most earth materials, porosity and che-
mical content of water filling the pore spaces are more
important in governing resistivity than is the conductivity
of mineral grains of which the material itself is composed
[9,10]. In this study, the electrical resistivity is measured
by using soil box for 32 numbers of clayey sandy soil
samples by using SCIP tester model TDLV equipment.
Mathematically;
L
R
A
(1)
where:
ρ = Resistivity of the conductor material (m)
L = Length of the conductor (m)
A = Cross-sectional area (m²)
On the other hand, in geotechnical engineering, water
content (Equation (2)) determination is a routine laboratory
test to determine the amount of water present in a quantity
of soil in terms of its dry mass [10]. As a definition,
100%
water
solid
M
WM

(2)
where:
Mwater = water mass present in soil mass (g)
Msolid = mass of soil solids (g).
In the early 1900s, a Swedish scientist named Batten-
berg developed a method to describe the consistency of
fine grained soils with varying moisture contents. Accord-
ing to [11,12], at very low moisture content, soil behaves
more like a solid. When the moisture content is very high,
the soil and water may flow like a liquid. Hence, on an
arbitrary basic, depending on the moisture content, the
Copyright © 2012 SciRes. IJG
A. A. BERY ET AL.
Copyries. IJG
113
Figure 1. Geological map of Penang Island.
behaviour of soil can be divided into four basic states—
solid, semisolid, plastic and liquid. The moisture content
at the point of transition from semisolid to plastic state is
the plastic limit and from plastic to liquid state is the liq-
uid limit. These parameters are known as atterberg limits.
ght © 2012 SciR
Equation (3) show the relationship of another property
which is derived from the liquid limit and the plastic
limit which is very useful. The property is called plastic-
ity index and is designated as PI and computed as
L
P
PI WW (3)
where:
WL = Liquid limit of soil (%)
Wp = Plastic limit of soil (%)
Another property can be determined from these pa-
rameters is liquidity index and is designated as LI (Equa-
tion (4)) and computed as
P
WW
LI PI
(4)
where:
Wp = Plastic limit of soil (%)
W = Moisture content of soil (%)
PI = Plasticity index of soil (%)
The residual soils are generally found in unsaturated
condition. The shear strength of unsaturated soils can be
represented by the so called extended Mohr-Coulomb
criterion.


'tan''tan
fa awb
Cu uu
f
 
  (5)
f
f
= shear stress on the failure plane at failure; C
=
effective cohesion; σ = normal stress; = pore-air pres-
sure;
a
u
u
''
a = net normal stress;
= effective an-
gle of shear resistance; = pore-water pressure;
w
u
A. A. BERY ET AL.
114

uu
aw
= matrix suction; and b
= angle indicating
the rate of increase in shear strength relative to matrix
suction. As the soil approaches saturation, the pore pres-
sure, w, approaches the pore pressure, and Equa-
tion (5) becomes:
ua
u
tan
w
Cu
'
ff


tan '
b
uu
 (6)
that is the Mohr-Coulomb strength criterion for saturated
soils. In applying Equation (5) to unsaturated soils, the
shear strength component due to matrix suction.
aw


'tanu
, is masked as the cohesion intercept,
aw b
CCu
 

0.01
1409.0 W
e
. Therefore, the cohesion inter-
cept, C, in residual soils appear to vary widely [12].
These useful indicators are important in determine their
changes in fixed study period in purpose to obtained de-
tails reliable data. All the engineering index properties
obtained are useful to indicate the clayey sand’s behave-
iour and their empirical correlations in 5 months of fixed
period.
4. Soil’s Behaviour Results
Laboratory tests were performed to determine 32 clayey
sand soils’s engineering characterization during five mon-
ths period. The percentages of liquid limit, plastic limit
and plasticity index of the samples taken from the site are
plotted against resistivity and moisture content. Note that,
the resistivity of the soil samples increase with the de-
creasing of the moisture content percentage. Figure 2
shows the correlation of the resistivity and the moisture
content of the clayey sandy soil is
and regression coefficient, R² was approximately 0.504.
For the empirical correlation between resistivity and
internal friction angle,

378.0e
for undisturbed clayey sand
soils is 0.03
1
C
and the regression coefficient,
R2 was approximately 0.647 as shown in Figure 3. It
shows that internal friction angle is inversely propor-
tional to the resistivity of samples.
In Figure 4, the empirical correlation between resis-
tivity, ρ and undisturbed soil’s effective cohesion,
for
Figure 2. Empirical correlation of resistivity, (ρ) and mois-
ture content, (W) of 32 clayey sand soil samples.
Figure 3. The empirical correlation between resistivity, (ρ)
and internal friction angle,
of undisturbed clayey sand
soil samples.
Figure 4. The empirical correlation between resistivity, (ρ)
and effective cohesion, C' of undisturbed clayey sand soil
samples.

0.101
167.0 C
e
clayey sand soils is found as:
0.047 103.0e
and re-
gression coefficient, R2 was approximately 0.664.
Meanwhile, Figure 5 shows the empirical correlations
of void ratio, porosity and degree of saturation with re-
sistivity of clayey sand soil samples. The empirical cor-
relation between resistivity, ρ and void ratio, e is,

0.014 51.20n
and its regression coefficient, R²
was approximately 0.345. The empirical correlation be-
tween resistivity with porosity, n is,

0.048 102.7S
and its regression coefficient, R2 was approximately 0.220.
However, the empirical correlation between resistivity, ρ
and saturation degree, S is,
 
0.845 36.63eW
and its
regression coefficient, R2 was approximately 0.529.
Figure 6 shows the empirical correlations between
moisture content with void ratio, porosity and degree of
saturation of clayey sand. The empirical correlation be-
tween moisture content, W and void ratio, e is,
0.317 28.41nW
0.629 46.30SW
and its regression coefficient, R² was
approximately 0.692. The empirical correlation between
moisture content, W with porosity, n is,
and its regression coefficient, R2 was approximately 0.724.
However, the empirical correlation between moisture con-
tent, W and saturation degree, S is,
and its regression coefficient, R2 was approximately 0.570.
Figure 7 shows the empirical correlation between liq-
uid limit, WL and resistivity, ρ is found as:
Copyright © 2012 SciRes. IJG
A. A. BERY ET AL. 115
Figure 5. The empirical correlation of void ratio, (e), poros-
ity, (n) and degree of saturation (S) with resistivity, (ρ) of
clayey sand soil samples.
Figure 6. The empirical correlation of moisture content (W)
with void ratio, (e), porosity, (n) and saturation degree, (S)
of clayey sand soil samples.
Figure 7. The empirical correlation between liquid limit,
(WL), plastic limit, (Wp), and plasticity index, (PI) with resis-
tivity, (ρ) of 32 clayey sand soil samples.

91.84

8 45.89

1 45.95

10.35W
0.060
L
W
0.01
p
W
d its regression coefficient, R²
was approximately 0.645. Then, the empirical correlation
between plastic limit, Wp and resistivity, ρ is found as:
and its regression coefficient,
R² was approximately 0.133. Meanwhile, the empirical
correlation between plasticity index, PI and resistivity, ρ
is found as: and its regression
coefficient, R2 was approximately 0.473. It shows that all
these three parameters are inversely proportional to its
resistivity.
0.04PI 
A part from that, the variation between resistivity, ρ
and liquidity index, LI of 32 clayey sand soil samples are
shown in Figure 8.
Meanwhile, Figure 9 shows the empirical correlation
between liquid limit, WL and moisture content, W of 32
clayey sand soil is found as: and
its regression coefficient, R2 was approximately 0.876.
The empirical correlation between plastic limit, Wp and
moisture content, W of clayey sand soil samples is found
as:
0.829
L
W
0.258 20.60WW
0.571 10.25PI W
p and its regression coefficient,
R2 was approximately 0.186. Meanwhile, the empirical
correlation between plasticity index, PI and moisture con-
tent, W of clayey sand soil samples is
and its regression coefficient, R² was approximately 0.637.
It shows that the parameters are directly proportional to
its resistivity values.
Figure 10 shows empirical correlation between mois-
ture content, W and liquidity index, LI of clayey sand soil
is found as:
0.891 39.20LI W and its regression
coefficient, R² was approximately 0.164.
Figure 8. The variation between liquidity index, (LI) with
resistivity, (ρ) of 32 clayey sand soil samples.
Figure 9. The empirical correlation between liquid limit,
(WL), plastic limit, (Wp), and plasticity index, (PI) with
moisture content, (W) of 32 clayey sand soil samples.
Figure 10. The variation between liquidity index, (LI) and
moisture content, (W) of clayey sand soil samples.
Copyright © 2012 SciRes. IJG
A. A. BERY ET AL.
Copyright © 2012 SciRes. IJG
116
5. Conclusions and Recommendation
Soil behaviour of clayey sand soils study is difficult and
challenging study especially for monitoring and investi-
gative techniques. In this research, technical techniques
were used in purpose of investigate the physical charac-
terizations of study area. The integrated study of the phy-
sical environment with engineering laboratory practices
for soil samples collected from the investigated area is
succeed in reaching the objectives of this research.
Generally, after analyzing the data obtained collec-
tively from 32 samples of clayey sand soil within five
months monitoring period located on Batu Uban area of
Penang Island, the following conclusions and recom-
mendations are made.
The cohesion (C') of clayey sand soils can influence
the resistivity values of tropical clayey sandy soils.
The higher the resistivity values, the higher of effect-
tive cohesion values which associated with their den-
sity and compression.
The moisture content can influence the soil’s strength
and resistivity values. The present of moisture content
can reduce the soil’s strength (Ø') by lose its soil par-
ticles chain and it also able to increase the soil’s con-
ductivity.
Shear strength of this soil is determined by the angu-
larity of the sand particles and moisture content.
The moisture content significantly modifies their stren-
gth (Ø'). As moisture increase, strength decreases.
This is because increasing moisture content cause grea-
ter separation of soil particles and further, causes sof-
tening of soil cements.
The empirical correlations models in this study are
successfully determine to show strong correlations with
granitic residual soils of Batu Uban area which signi-
ficant to tropical clayey sand soil’s behaviour.
6. Acknowledgements
Special thanks are due to Prof. Dr. Fauziah Ahmad who
gave permission to use the Direct Shear Test equipment
in USM Engineering Campus, Penang. The author also
wishes thank to Assoc. Prof. Siti Noor Linda Taib from
UNIMAS, Sarawak, Malaysia. Lastly, I wished thanks to
Ms. Eva Diana and Mr. Jeff Steven.
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