ABSTRACT
A study was carried out to determine the efficiency of different models for estimating hydraulic conductivity in soils of coastal plain sands of Oboro clan – Ikwuano Local Government area in Abia State. Representative undisturbed soil samples were collected from 8 communities and their properties determined using standard laboratory methods and experimental models. Five different models were used to estimate the saturated hydraulic conductivity (Ks) of the soils of the study area, these models were Hazen, Relative Effective Porosity Model (REPM), Slitcher, Terzaghi and Kozeny-Carman Models. Soil properties determined include depth, aggregate sizes, bulk density and porosity. The predicted and observed soil properties were compared using multiple linear regression test. Further evaluation of the accuracy of prediction on the models used in comparison with the laboratory Ks values were carried out with absolute mean percentage error. Generally, the results showed that the soils are of Sandy Basic soil type. There was a significant positive correlation (P<0.001) between bulk density and porosity. The hydraulic conductivity maximum and minimum values of Kozeny-Carman, Hazen, Slitcher, Terzaghi and Relative Effective Porosity Model (REPM) were 67.68m/day and 0.86m/day, 18.72m/day and 0.86m/day, 9.50m/day and 0.29m/day, 68.25m/day and 1.15m/day, 191.52m/day and 2.59m/day respectively. The result indicated that the hydraulic conductivities calculated by Slitcher models is in all cases lower than that from the other models as well as from pressure plate apparatus test result. Saturated hydraulic conductivity estimated using REPM gave the highest Ks value of 191.52m/day. This study therefore concluded that the best overall estimation of Ks is reached based on relative effective porosity model followed by Terzaghi and then Kozeny-Carman models. The research recommended that Relative Effective Porosity Model (REPM) as the best and useful alternative for estimating Ks of soils within the South-Eastern Nigeria.
TABLE OF CONTENTS
Title Page i
Cover page ii
Declaration iii
Certification iv
Dedication v
Acknowledgements
vi
Table of
Contents vii
List of
Tables ix
List of
Figures x
Abstract xi
CHAPTER 1:
INTRODUCTION
1.1 Background
to the Study 1
1.2 Justification
3
1.3 Objectives
of the Study 5
1.3.1 General
objective 5
1.3.2 Specific
objectives 5
CHAPTER 2:
LITERATURE REVIEW
2.1 Soil
Hydraulic Conductivity 6
2.2 Flow
in Soil: Macroscopic Flow 10
2.3 Importance
of Hydraulic Conductivity 13
2.4 Factors
Influencing Hydraulic Conductivity 14
2.4.1 Topography 14
2.4.2 Viscosity 16
2.4.3 Permeability
17
2.4.4 Soil
texture 18
2.4.5 Soil
structure 19
2.4.6 Soil
compaction 20
2.4.7 Soil
organisms 20
2.4.8 Bulk
density 21
2.4.9 Soil
water content 22
2.5 Measurement
of hydraulic conductivity 23
CHAPTER 3:
MATERIALS AND METHODS
3.1 Study
Area 27
3.2 Creation
28
3.3 Geography
28
3.4 Materials
28
3.5 Field
Sampling Procedures 29
3.6.1 Soil
preparation 30
3.6.2 Ceramic
plate preparation 30
3.6.3 Setting
up the nitrogen gas as a pressure source 30
3.6.4 Removing
the samples from the pressure plate apparatus 31
3.6.5 Oven
dry samples 31
3.7 Experimental
determination of hydraulic conductivity 32
3.8
Models Used in Estimating
Hydraulic Conductivity 32
3.8.1 Kozeny
– Carman model 33
3.8.2 Hazen
model 33
3.8.3 Slitcher
model 33
3.8.4 Terzaghi
model 34
3.8.5 Relative
effective porosity model (REPM) Suleiman and
Ritchie 34
3.9 Determination of soil Moisture Content at
field Capacity in
Volume
Fraction: (cm3 cm3) 34
3.10 Aggregate
Size Determination 35
3.10.1 Materials
used for aggregate size determination 35
3.10.2 Procedure 35
3.11 Determination
of Hydraulic Conductivity with Empirical Models 36
3.12 Statistical
Analysis 36
CHAPTER 4: RESULTS
AND DISCUSSION
4.1 Bulk
Density, Porosity, Field Capacity And Relative Effective
Porosity of Soils
of The Different Communities 37 4.2 Relationship between bulk density and
porosity of the
study location at various depths 38
4.3 Estimated
Mean and Standard Deviation of Aggregate Size
Distribution Test 45
4.4 Comparative
Results of Hydraulic Conductivity of Models
and Pressure Plate
Apparatus Test 52
4.5 Comparison
based on Absolute Mean Percentage Error
(AMPE) at Various
Depths 59
CHAPTER 5:
CONCLUSION AND RECOMMENDATIONS
5.1 Conclusion 61
5.2 Recommendations 62
REFERENCES 67
LIST OF TABLES
4.1: Estimated
parameter values for the relative effective
porosity model
(REPM) depth 0-10cm 39
4.2: Estimated parameter values for the
relative effective
porosity model
(REPM) depth 10-20cm 40
4.3: Correlation
between bulk density and porosity for
depth 0-10cm 41
4.4: Correlation
between bulk density and porosity for
depth 10-20cm 42
4.5: Estimated
Mean and Standard Deviation of Grain Size
Distribution Test
at depth 0-10cm 47
4.6: Estimated
Mean and Standard Deviation of Grain Size
Test at depth
10-20cm 49
4.7 Basic
Soil Type Classification 51
4.8: Estimated
Mean and Standard Deviation of Hydraulic
conductivity calculated from the Models at
depth 0-10cm 55
4.9: Estimated
Mean and Standard Deviation of Hydraulic
conductivity
calculated from the Models at depth 10-20cm 56
LIST OF
FIGURES
2.1:
The Relationship Between Hydraulic
Gradient and Flux (q). 11
2.2: Comparative results of Hydraulic
conductivity of empirical formulae and
constant head parameter (S1
Soil sample 1, S2 Soil sample 2…..) 12
3.1: Map of Abia State showing
the study area (Ikwuano LGA) and
Oboro Clan-sample locations
27
4.1: Relationship
between bulk density and porosity for the study
locations at depth 0-10cm. 43
4.2:
Relationship between bulk density and
porosity for the study
locations at depth 10-20cm. 44
4.3: Aggregate Size Distribution curve for Soil Samples at Depth
0-10cm 48
4.4: Aggregate Size Distribution curve for Soil Samples at Depth
10-20cm 49
4.5: Hydraulic Conductivities using Various
Models at Depth 0-10cm. 57
4.6: Hydraulic Conductivities using Various
Models at Depth 10-20cm. 58
4.7: Absolute Mean Percentage Error for Models
at Various Depths 60
CHAPTER
1
INTRODUCTION
1.1 BACKGROUND TO THE STUDY
The rate of water movement through soil is of
considerable importance. The entry of water into soil, the movement of water to
plant roots, the flow of water to drains and wells and the evaporation of water
from the soil surface are but a few of the obvious situations in which the rate
of movement plays an important role. An important soil property involved in the
behaviour of soil water flow is the conductivity of the soil to water.
Qualitatively, hydraulic conductivity is the ability of the soil to transmit
water (Klute, 1965).
Hydraulic conductivity, symbolically represented as k,
is a property of vascular plants, soils and rocks, that describes the ease with
which a fluid (usually water) can move through pore spaces or fractures in the
presence of an applied hydraulic gradient. It depends on the intrinsic
permeability of the material, the degree of saturation and on the density and
viscosity of the fluid.
Another similar term is permeability, which is defined
as the property of the porous medium controlled only by the pore geometry
(Richards, 1952). It is the most important physical property of porous medium,
which is a measure of the ability of a material to transmit fluid through it (Alabi,
2011). It settlement and stability of roads, foundation building and even crop
production (Okagbue, 1995).
Economic consideration associated with field
operations and well construction may also be a limiting factor in determining Ks.
Alternative methods of estimating hydraulic conductivity from empirical
formulae based on grain-size distribution characteristics have been developed
and used to overcome these problems (Odong, 2007).
Hydraulic conductivity can vary by more than 10 orders
of magnitude from very low values in gravels and boulders. Hydraulic
conductivity varies widely even for a given material. The coefficient of
variation, defined as the ratio between the standard deviation and the mean,
can range from 100 to 800 percent for both natural sediments (Libardi et al, 1980; Warvick and Nielsen, 1980;
Cassel, 1983; Albrecht et al, 1985; Duffera
et al, 2007) and remolded sediments
(Benson, 1993; Benson and Daniel, 1994). Ks may vary over several
orders of magnitude within a single soil series or formation. This variability
may increase if Ks is determined in laboratory using small-size
undisturbed soil cores (Mallants et al,
1997), which is sometimes essential for the studies such as upflux,
infiltration and seepage, for individual layers. The properties of natural
soils are quite variable. For example, Ks can vary significantly
since the structure of pores in soils may be varied as affected by different
rates of biological, physical and chemical processes.
The K-value of a soil profile can be highly variable from
place to place and also at different depth. K-values can be variable not only
in connection with different soil layers, but also within one soil layer. A vertical variation in a soil can be partly
due to layered composition of the parent material, but more commonly the
results of profile development. Horizontal variations in soil properties are
common at any scale, even at less than 1 meter. In some cases the change in
colour, salinity, texture, structure at the soil surface is quite sharp, but
more generally is gradual (Brain and Krujin, in Ritzema 2006).
Coastal plain sands usually have only moderate slopes,
being more level in the low-lying parts nearer
the coastline and more hilly farther inland, where streams and rivers
flowing down the steeper grades have more deeply dissected the landscape.
It was reported that spatial variability of coastal
plain sands of southeastern Nigeria originates dominantly from intrinsic
factors associated with texture and mineralogy (Obi and Udoh, 2011; Obi et al., 2011). The texture and mineralogy
of coastal plain sands bear the imprints of quartz arenite which is not rich in
most plant growth nutrients dominantly sandy and coarse texture (Chikezie et al, 2010). Crop production system
within the coastal plain sands geomorphic unit of southeastern Nigeria is
characterized as rain fed, low input, intensive and extensive with the use of
traditional hand held tools (Ibia et al.,
2011; Obi and Udoh, 2011).
1.2 JUSTIFICATION
Soil hydraulic properties such as saturated hydraulic
conductivity (Ks) govern many soil hydrological processes,
therefore, they are very important and even necessary in water and mass models,
irrigation and drainage studies.
Knowledge of hydraulic conductivity is very important
in solving environmental problems because it is one of the most important soil
physical properties for determining infiltration rate, irrigation requirement
and efficiency, computing water conveyance efficiency, design of drainage
system and other hydrological processes in the soil system (Gulser and
Candemir, 2008).
In general, soil hydraulic conductivity is a major
factor in determining the use to which a soil can be put, stability of roads
and building foundations, crop production potential, growth of trees, shrubs
and grasses are all affected to some degree by the ease or difficulty with
which the soil drains.
Over the years many direct methods have been developed
for measuring soil hydraulic properties in the field, for example the internal
drainage method (Hillel et al., 1972;
Libardi et al., 1980), the zero plane
flux method (Richards et al., 1956)
and the Guelph permeameter method (Reynolds and Elrick, 1985), and in the
laboratory, e.g the hot-air method (Arya
et al., 1975) the outflow method
(Gardner, 1956) and the constant head method (Klute and Dirksen, 1986).
Direct measurement of soil hydraulic properties
including Ks is costly and time-consuming and becomes impractical due to
spatial and temporal variabilities when hydrologic predictions are needed for
large areas.
In past few decades, as an alternative, indirect
approximation of hydraulic properties from some basic and easily measured soil
properties (such as clay, sand and silt content, bulk density etc) using
pedotransfer functions has received considerable acceptance. Now there is no
standard information system on soil hydraulic properties in Oboro clan-Ikwuano
L.G.A of Abia State.
In recent years, with improvement of science, many
materials about hydraulic conductivity information appeared, but there is no
uniform and standard system to implement. Despite the fact that Oboro clan has
large and varying amount of land resource, there is still poor management of
these properties due to lack of good information, monitoring techniques and
predicting models.
1.3 OBJECTIVES OF THE STUDY
1.3.1 General objective
The main objective of the study was to estimate the
hydraulic conductivity of soils of coastal plain sands based on undisturbed
soil sample using pressure plate apparatus.
1.3.2 Specific objectives
The specific objectives were to:
1.
determine the basic soil
types of the study area using a standard British soil classification system.
2.
determine the
relationship between the soil bulk density and porosity in the study area.
3.
evaluate and justify the
comparative efficiency of different models for estimating hydraulic
conductivity of soils of coastal plain sands in the study area.
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