hydrogeologic characterization of owo and its environs using remote

Proceedings of the International Conference on Science, Technology, Education, Arts, Management and Social
Sciences iSTEAMS Research Nexus 2014, Afe babalola University, Ado Ekiti, Nigeria – May 29-31st, 2014.
HYDROGEOLOGIC CHARACTERIZATION OF OWO AND
ITS ENVIRONS USING REMOTE SENSING AND GIS
Anifowose A.Y.B.
Department of Remote Sensing and Geoscience Information System
Federal University of Technology
Akure, Nigeria
Adewumi A.J.
Department of Geological Sciences
Achievers University
Owo, Ondo State, Nigeria
E-mail: [email protected]
Phone: +2348167870980
ABSTRACT
The application of remote sensing and GIS in groundwater potential characterization has been internationally acclaimed.
Owo and its environment lack sufficient groundwater data that will aid proper planning and management of the resource. For
this reason, the groundwater potential study of Owo and its environment within the Basement Complex was carried out using
remote sensing and GIS. After desk study, remotely sensed data were acquired. LANDSAT TM (band 1-7) of 1988 was
acquired. The acquired imageries were processed using image processing software. The image enhancements used are the
linear stretching, equalization and low pass Gaussian methods. For drainage mapping, band 5-4-3 were combined in a RGB
(123) format. For lineament extraction, the Digital Elevation Model (DEM) was generated from the SRTM data which were
corrected for bad values. The DEM was used in manually (on-screen digitization) extracting lineaments in the study area.
The Normalized Difference Vegetation Index (NDVI) was determined by combining bands 4 and 5. The groundwater
potential of the area was calculated using score values assigned to each parameter studied. The results of the research show
that the lineament distribution in the study area is polymodal with peaks between 80o-100o accounting for 27% of the total
azimuths. The East-West fractures are most prominent, with the broad, positive correlation in frequency and length of the
lineament suggesting that they are of geological origin. Lineament density of the area shows that Owo has higher lineament
density of about 0.85km/km2 when compared other part of the study area. The density of lineament in the study area is
attributable to the high fracturing that affected the Basement Complex area during the Pan-African Orogeny. Also, the study
further revealed that there are more lineament intersection around the southeastern part of Owo Township and Iyere. These
areas are more favourable sites for groundwater accumulation.The drainage density map generated for the study area reveals
that there are more rivers around Emure-Owo than other parts of the study area (1.15km/km2). Groundwater accumulates
more in areas where lineaments intersect each other in the study area. Furthermore, it was observed that most wells studied
are very close to or on a fracture. Therefore it is safe to infer that most aquifers in the area tap groundwater from the fracture
systems within the area. The groundwater potential of the study area is high. However, there is variation in its potential
distribution with Owo and Emure-Owo having the highest potential. This followed by Ogbesse, Uso-Owo, Ipele-Owo, ObaAkoko and Alayere. Over sixty percent of wells studied are found within the moderately high to moderate groundwater
potential areas.
Keywords: Hydrogeology, Remote Sensing, GIS, Owo, Groudwater;Lineaments
1. INTRODUCTION
Groundwater in Nigeria is restricted by the fact that more than half of the country is underlain by crystalline basement
complex. The groundwater from hard-rock aquifer systems is an important water source for several domestic, industrial and
agricultural purposes, as well as for public supply. In exploring for groundwater potential of any area, two basic methods are
employed. These methods are remote sensing and geophysical techniques. Due to the fact that it allows a synoptic view of an
area, remote sensing methods can be used in groundwater mapping. In achieving this structural and drainage pattern in an
area are studied together with vegetation cover and distribution as groundwater are usually located in areas with high
lineaments, low drainage densities with healthy vegetation.
Owo and its environs lack sufficient groundwater data that can provide an insight to its potential of providing fresh water for
its populace. This is also a common problem associated with groundwater management within the Basement Complex
regions of Nigeria. This necessitated the need to carry out the research work which covers an extensive area and which
interpolation of data can be possible for necessary information about the groundwater potential of the area to be generated.
This can only be achieved using a technology that can synoptically view an area. Hence the aim of this research is to carry
out hydrogeological characterization of Owo and its environs, Southwestern Nigeria using remote sensing and GIS
techniques.
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Sciences iSTEAMS Research Nexus 2014, Afe babalola University, Ado Ekiti, Nigeria – May 29-31st, 2014.
2. LOCATION AND ACCESSIBILITY OF THE STUDY AREA
The study area is located in the Northern part of Ondo State. It is found between Latitude 7o00’ and 7o25’N and Longitude
5o20’ and 5o45’E (Figure 1). The study area covers Owo, Ayedun-Ogbesse, Alayere, Uso-Owo, Amurin-Owo, Emure-Owo,
Ipele-Owo, Ita-Ipele and Oba-Akoko areas of Ondo State. It is located on path 190 and row 50 on the Landsat TM imagery.
AyedunOgbesse which is on the North-western margin of the study area is about 15 kilometers from Akure the state capital
of Ondo State. Ipele, which is in the Southeastern part of the study area, is about 15 kilometers from Ifon, the headquarters
of Osse Local Government Area. On the Northeastern margin is Oba-Akoko which is about 10km to Idoani to the west and
about 15km from Oka-Akoko to the North. The major towns in the study area are Owo which is the largest, Uso-Owo,
Ogbesse-Ayedun, Oba-Akoko, Ipele-Owo, Amurin-Owo and Emure-Owo. Land use in the study area shows that over twenty
percent (20%) of the land is mainly used for cultivation. Other land use in the area includes government forest reserves
which make up about 50% of the total land of the area. Ten percent of the area (10%) constitutes built-up areas. The
remaining twenty percent (20%) constitute rivers which serve as a source of water for domestic and irrigation purposes.
The study area has a high topography (as high as 1,200ft above the sea level) which is the cause of ridges observed during
the course of field study. In Owo township, the quartzite ridge runs from Emure-Owo (western part of the study area) to
Ipele-Owo (eastern part of the study area). At Oba-Akoko, the granitic rock outcrops of high elevation forms inselberg and
they generally form ridges, domes and hills in other parts of the study area. Valleys are found especially around Ogbesse,
Uso-Owo and Alayere all in the western part of the study area. This allows the easy flow of some major rivers in the
area.The study area consists typically of dendritic drainage pattern which is structurally and geomorphologically controlled.
The major rivers in the area are Rivers Iporo, Ubeze and Aisenwen which run from east to west and are major tributaries of
the Osse River. The other major rivers in the study area are River Ogbesse which runs from North to South, the River
Aisenwen runs from South to North. These major rivers are generally perennial in nature and their tributaries are majorly
seasonal reaching their maximum dryness at the peak of the dry season.The study area is located within the tropical
savannah belt of Nigeria. The study area has two basic climates: the rainy season which ranges between March and
September and dry season between October and February. The temperature of the study area ranges from 12.8oC and 42.7oC
for a period of 10 years (2001-2010). The precipitation in the study area ranges from 0.00mm to 208.60mm for a period of
10 years (2001-2010) (Figure 2).
Figure 1: Location of the study area
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3. GEOLOGY OF THE STUDY AREA
The study area (Figure 3) is underlain by the Precambrian Basement Complex rocks that have been affected by the regional
tectonism that affected most part of the West African craton. The lithology of Southwestern Nigeria as proposed by
Rahaman (1989), are predominantly migmatitic and granitic gneisses; quartzites; slightly migmatized to
unmigmnatizedmetasedimentaryschists and metaigneous rocks; charnockite, gabrroic and dioritic rocks; and members of the
Older Granite suite mainly granites, granodiorites and syenites.The Migmatite-gneiss quartzite group is most widespread in
the Basement Complex of southwestern Nigeria. The structural elements common the region are foliation, lineation, minor
folds, major folds, faults. Within the Basement Complex, tectonic deformation has completely obliterated primary structures
(Oluyide, 1988). The major faulting in the area is not evident and most of those recognized have been traced from aerial
photographs and satellite imagery.
Anifowose and Borode (2007) mapped out lineament in Okemesi area using photogeological methods. The study showed
that the Itawure fault is the major lineament in the region which passes through Itawure and EfonAlaye. It trends from E-W
and it is a transcurrent fault which displaces the fold nose resulting in the double plunging of the fold axis. Field observation
according to Anifowose and Borode (2007) shows that fractures in the area is predominantly trend in the E-W direction,
while a few of them are in ENE-WSW directions.The basic rocks in the Owo are Migmatite, undifferentiated schists with
many quartzite intrusions which trends mainly from ENE-WSW. Also, granite gneiss and granitic intrusions are also present.
Ogbesse, Uso-Owo, Amurin-Owo and Emure-Owo are located on migmatite. The major geologic structures in the area are
fractures which are filled in some places by quartz intrusion.
Figure 2: Precipitation in the study area over a period of 11 years (2000-2010)
(Source: Nigeria Meteorological Agency)
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Figure 3: Geologic map of the study area
4. PREVIOUS WORK
Many researchers have employed the techniques of remote sensing and GIS in exploring for groundwater. Obiefuna et al
(2010) determined potential areas of groundwater occurrences using remote sensing techniques in parts of Mubi area of
Northeast, Nigeria. The lineament fractures analysis and statistical analysis of the SPOT imagery on a scale of 1:50000 was
carried out using ILWIS 3.1 software. Normalized Difference Vegetation Index (NDVI) was also carried out using ILWIS to
highlight areas where green plants are active. The result shows that the study area has swarms of fractures in addition to
highly weathered rocks.The study led to the delineation of areas where groundwater occurrence is most promising. Also,
Anudu et al (2011) carried out lineament analysis and interpretation for assessment of groundwater potential of Wamba and
adjoining areas, Nasarawa state, North central Nigeria using LANDSAT 5-TM imagery of the area which was analysed and
interpreted in order to determine the lineament trends, lineament density and groundwater potential across the area. In their
study, it was observed that the drainage pattern in the area is structurally controlled and mostly influences both the
groundwater and surface water flow directions in the area. Rose (azimuth-frequency) diagram of the lineaments delineated
on the imagery shows trends in the NE-SW, NNE-SSW, E-W, NNW-SSE and N-S directions with NE-SW and NNE-SSW
as the major trends. Lineament density maps show that the lineament density is high around areas such as Monkwar,
Zamatak, Ninkade, Mugu, Gwanzu, Wamba, Nakere and Garko. Areas having high lineament density represent areas with
relatively high groundwater potentials.Other researchers that have worked on the hydrogeologic characterization include
amongst others. Adesida et al (2012), Bhunia et al (2012), Bera and Bandyopadhyay (2012), Phukon et al (2012), Arkoprovo
et al (2013) and Chumaet al (2013) all carried out groundwater potential mapping of different areas using the combination of
remote sensing and GIS. The results were promising and dependable.
5. RESEARCH METHODOLOGY
The research was carried out following the flow chart shown in Figure 5. The study is divided into two parts namely:
Satellite data collection and processing and field data collection and processing. The satellite data collection involves the
acquiring of satellite imagery (LANDSAT TM) followed by data correction, image enhancement and filtering, lineament
mapping and extraction, drainage mapping, Digital Elevation Model (DEM) generation and Normalized Difference
Vegetation Index (NDVI). Other data used are geologic map, topographical map and rainfall data. The maps derived from
these are topographic map, slope map, drainage map, lithology and lineament map. These were then incorporated into the
Geographic Information System (GIS) environment for processing and spatial analysis which was achieved by modeling the
generated data. Each parameter for evaluating the groundwater potential was assigned score values following the Groeneveld
et al (2005) scoring methods.
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5.1 Preliminary Studies
Before the commencement of the fieldwork exercise for this research, preliminary studies were carried out. The preliminary
studies involve desk-study of necessary materials needed for the study. Topographic map of Owo Sheet 222 of the scale
1:100000 and that of Akure sheet of the scale of 1:100000 were purchased from which the sampling points were selected.
The geologic map of the study area was also acquired from the Nigeria Geological Survey Agency (NGSA). Afterwards,
LANDSAT TM (bands one to seven) imageries of the area were acquired (Figure). Furthermore, literatures covering the
research topic were gathered and studied to have better understanding of the use of remote sensing and GIS for groundwater
characterization.
5.2 Field Study and Data Collection
5.2.1 Positional Data Collection
Positional data are data that define the location of a body or feature on surface of the Earth. Positional data taken includes the
longitude, latitude and elevation data at each point of study and samples collection. This was achieved using a Garmin Etrex
model GPS. Every data generated from this research is regarded as positional because they have positions on the surface of
the earth and are defined by distinct latitude and longitude reading (Figure 6).
5.2.2 Geologic Field Mapping
Geologic field mapping was carried out to ascertain the rock lithology in the study as this have an impact on groundwater
potential distribution of the area. The base map was gridded equally and each grid was geologically mapped. The orientation
(strike and dip) of lineaments (fractures and veins) in the study area were taken.
5.2.3 Depth to Water Level Measurement
Depth to water level measurement was carried out using a water level meter. The reading for each location was then
subtracted from the ground elevation at that point to get the groundwater elevation. The depths to water level measurement
were taken during the dry season. This is because groundwater flow pattern is best studied during this time of the year.
5.3 Image Enhancement
The objective of image enhancement is to show features of interest in an enhanced manner, by applying certain operations
available in the IP software (Meijerink et al, 2007). The image was enhanced to extract important groundwater information.
Information extracted using image enhancement are drainage pattern of the study area, lineament mapping and it aided to
clearly see the position of areas where fieldwork exercise and sampling collection took place. For drainage mapping, the
LANDSAT TM (bands 1-7) imagery was imported into the ENVI 4.3 software. The bands 5-4-3 were combined together in
a RBG (123) format. This was then enhanced by using equalization method. This made the imagery to be clearer. The areas
of sampling were easily identified and the drainages were seen. However, to clearly see the drainages in the study area, the
enhanced image was stretched using linear stretching method. The stretch range was between 25%-50% with an output data
of 25-100%.
5.4 Image Interpretation
5.4.1 DEM generation
To generate the Digital Elevation Model (DEM) (Figure 4), SRTM data were acquired and corrected for bad values using the
ENVI software. The corrected imagery was then imported into ERDAS where it was run as modeler. The DEM was run
using the command route DEM_colour_shadow which was processed by selecting raster. The resulting imagery was then
display in the viewer. The DEM was used in manually extracting lineaments in the study area.
5.4.2 Lineament mapping
Lineaments were mapped from the DEM which was earlier enhanced using the low pass Gaussian method using ENVI 4.1.
The lineament was extracted from the enhanced DEM of the area using an on-screen digitizing method in the ILWIS 3.1
software environment.
5.4.3 Lineament intersection and density maps generation
Lineament intersection map was generated by gridding the lineament map (Figure 12). Lineament intersections were then
counted for each grid noting their longitudinal and latitudinal positions within the study area. The lineament density map was
used to determine the distribution of fractures in the study area. It was generated by gridding the lineament map using a
gridding scale of 0.100. Lengths of lineaments in each grid were measured and then divided by the total area of the grid
using ILWIS 3.1 software. The generated data were then incorporated into the SURFER software where lineament
intersection and density maps (Figures 11 and 13) were obtained.
5.4.4 Drainage mapping and drainage density calculation
The drainages in the study area were mapped by combining bands 3-2-1 (RGB). The image was enhanced using linear
enhancement method. This was then stretched to reveal drainage pattern in the study area. Afterwards, the drainages were
extracted in ILWIS using the on-screen digitizing method.The drainage density map (Figure 14) was used to determine the
distribution of drainage in the study area. It was generated by gridding the drainage map using a gridding scale of 0.100.
Lengths of drainage in each grid were measured and then divided by the total area of the grid using ILWIS 3.1 software. The
generated data were then imported in SURFER software where a contour map representing the drainage density map was
obtained.
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Sciences iSTEAMS Research Nexus 2014, Afe babalola University, Ado Ekiti, Nigeria – May 29-31st, 2014.
5.4.5 NDVI measurement
The Normalized Difference Vegetation Index (Figure 16) was used to determine the distribution of groundwater based the
distribution of healthy vegetation in an area. To determine the NDVI of the study area, LANDSAT TM band 4 and band 3
were combined. This was achieved by using the ENVI 4.3.
5.4.6 Thematic maps generation
Thematic maps were generated using both ILWIS 3.1 and SURFER 10. Thematic maps are the individual maps (e.g. the
groundwater flow map, the lineament map and the drainage map) generated before they are overlain on other maps from
which necessary information about the area being understudied are extracted.
5.5 Groundwater potential calculation
The groundwater potential of Owo and its environs was calculated using the equation (equation i) by Groeneveld et al
(2005). The equation was derived by adding the score values of lithology, lineament density, drainage density, topographic
elevation, slope gradient, land-use, annual rainfall and groundwater flow pattern. According to Groeneveld et al (2005),
areas with Basement Complex lithology are scored low when compared to areas with sedimentary rocks because they lack
primary porosity or openings that will help in the accumulation of groundwater. Also, areas with high lineament density are
scored high when compared to areas of lower lineament density because groundwater accumulates in areas with higher
amount of fractures. Areas with lower drainage densities were scored higher when compared to areas with high densities
because they depict that surface water have been lost to groundwater, whereas areas with high drainage density depicts that
the groundwater in the area loses its content to the surface water body.
(i)
Where, Gp = Groundwater potential; Rf = Rainfall; Lt = Lithology; Ld = Lineament density; Lu = Land-use; Te =
Topographic elevation; Sp = Slope; Dd = Drainage density; Gf = Groundwater flow.
6. DISCUSSION OF RESULTS
6.1 Lineament distribution in the study area
Lineaments give a clue to movement and storage of groundwater (Subba et al. 2001) and therefore are important guides for
groundwater exploration. Recently, many groundwater exploration projects made in many different countries have obtained
higher success rates when sites for drilling were guided by lineament mapping (Teeuw, 1995). The lineament distribution in
the study area is polymodal (Figures 8 and 9) with three peaks at 40o-60o, 80o-100o and 120o-140o accounting for
approximately 16%, 27% and 18% respectively. The East-West (90o) fractures are most prominent. This is similar to the
result obtained from the study of the Itawure fault (Anifowose and Borode, 2007). The broad, positive correlation in
frequency and length (Figure 10) of the lineaments suggest that they are of geological origin (Odeyemi et al, 1999).
Figure 4: The Digitial Elevation Model of the study area
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Satellite Data LANDSAT TM
Ancillary Data: Geologic map, topographic map, groundwater elevation, rainfall and structural
data.
Satellite data analysis (Geometric and radiometric correction), image enhancement,
filtering, lineament mapping, drainage mapping, DEM generation and NDVI analysis
Geological Interpretation
Lineaments Interpretation
GIS Processing (Digitization and building of database)
Derived maps
Annual
Topographic
Elevation
Slope
Map
Drainage Density
Lithology
map
GIS processing (Spatial Analysis)
Integration and modeling
Hydrogeological map
Figure 5: Flow chart showing the processes of study
Figure 6: Locations of open shallow wells of the study area
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Lineament Density
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6.2 Distribution of lineament over the lithology of the study area
The distribution of lineaments in an area usually depends on the subsurface geology of that area. In Nigeria, lineaments are
generally believed to have been formed during the Pan-African Orogeny. They are common in the Basement Complex rocks,
although they also exist in sedimentary terrain. Their distribution generally depends on the stress and strain pattern within
the rocks of an area. The distribution of lineaments over lithology in the study area shows that 260 of the lineaments are
found on migmatite and accounts for 78.78%, 60 are found on quartzite 18.18%, while 10 are found on granite gneiss and
accounts for 3.03% of the total lineaments in the study area (Figure 7).Migmatite have the highest distribution of lineament
in the study area because it covers more area extent than any other rock type in the area. However, when its area extent is
reduced to that covered by quartzite, it has lesser amount of lineaments.
6.3 Isolinear contours of the study area
Isolinear contours (lineament density, lineament intersection density) are particularly advantageous in modern exploration
geoscience in that they offer a quick glance at the spatial distribution of the density of lineaments and thus provide a useful
database in hydrogeology and water borehole drilling (Odeyemi et al, 1999). In view of this lineament density and lineament
intersection density contour maps were plotted to characterize areas with sufficient groundwater in the study area. Areas with
high lineament density and intersection generally have high groundwater potential.
6.4 Lineament density and its implication for groundwater accumulation in the study area
The lineament density map of the study area (Figure 11) shows that areas around Owo (Ijegunmo, Isijogun and Sanusi) have
higher lineament density. In these areas, the lineament density ranges between 0.55 and 0.85km/km2. Ita-Ipele and IpeleOwo of the study area has lineament density of between 0.5 and 0.65km/km2, while Oba-Akoko has lineament density of
between 0.35 and 0.65km/km2. Emure-Owo has lineament density between 0.35 and 0.5km/km2. Uso-Owo, Ogbesse and
Alayere areas have lineament densities of between 0.35 and 0.7km/km2, 0.15 and 0.3km/km2 and 0.25 and 0.35km/km2
respectively. The density of lineaments in the study area is attributable to the high fracturing that affected the Basement
Complex area during the Pan-African orogenic cycle.
The aforementioned implies that groundwater will be concentrated more in areas around Owo and least concentrated in
Ogbesse area of the study area. This means that more groundwater is expected to accumulate in Owo, Isijogun, Ikarejunction, Ipele-Owo, Oba-Akoko, Uso-Owo, Emure-Owo, Alayere and Ogbesse respectively. The geology of the study area
contributed to the distribution of lineaments in the area. Areas with high lineament densities within the study area are found
to be within the quartzitic zones. Quartzites are known to be highly fractured when placed under the appropriate stress-strain
field.
Figure 7: Lineament distribution over the lithology in the study area
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Figure 8: Histogram of lineaments in the study
6.5 Lineament intersection and its implication for groundwater potential in the study area
Figure 13 shows that areas located in the northeastern and southern part of study area have more lineament intersection that
other part of the area. There are more lineaments intersecting at the southeastern part of Owo Township around Iyere (18.0).
Also, the southern parts of Owo also have higher lineaments intersection around Isijogun, Ijegunmo and Sanusi areas (14).
Also Ipele-Owo and Ita-Ipele have lineament intersection of 14. This is closely followed by Oba-Akoko where the lineament
density is up to 13. This is followed by Uso-Owo with intersection density of between 7 and 11. Emure-Owo, Ogbesse and
Alayere have the least intersection between 7 and 8 and 3 and 2 respectively.
According to Odeyemi et al (1985) points representing the intersections of two or more deep seated, open lineaments are
more favourable sites for groundwater accumulation. The implication of the aforementioned is that Iyere, Isijogun, Ijegunmo
and Oba-Akoko that have high lineament intersection density (>18) will have more groundwater potential than Ipele-Owo
which has an intersection of 14. This is also the case for Uso-Owo with an intersection of between 7 and 11. Furthermore,
Emure-Owo, Ogbesse and Alayere areas with least intersection of lineaments will have lesser groundwater than the other
aforementioned area.
6.6 Statistical analysis of lineament data
The study reveals that the length of the lineaments in the study area ranges between 0.58km and 183.00km (Table 3). The
total length of lineaments on the imagery is 1,223.57km. Lineament azimuth ranges between 5.47o and 180o. Lineament
azimuth between 0-10o has a frequency of 3 with a percentage frequency of 0.91%. The lineament azimuths between 11-20,
21-30, 31-40, 41-50, 51-60, 61-70, 71-80, 81-90, 91-100, 101-110, 111-120, 121-130, 131-140, 141-150, 151-160, 161-170
and 171-180 have a frequency of 06, 06, 09, 28, 24, 25, 21, 58, 30, 19, 21, 27, 28, 11, 08, 02 and 04 respectively. These have
percentage frequencies of 1.82%, 1.82%, 2.73%, 8.49%, 7.27%, 7.58%, 6.36%, 8.18%, 8.49%, 3.33%, 36.60%, 5.11% and
4.71% respectively. Azimuths between 81o-90o have the highest frequencies of 17.98%.
The minimum azimuth in the area is 5.47o and maximum of 180o. The statistical analysis of data reveals that the mean
azimuth of lineaments in the area is 90.89o while the median and mode is 90o respectively. The standard deviation is
1316.90.The skewness is 0.02 which shows that the lineaments in the study area have a geologic origin.
The mean length of lineaments in the study area is 371km and the median is 2.54km, while the mode is 1.43km and the
standard deviation is 10.13km. Variance analysis gave a value of 102.69 and skewness of 16.95. The range of the length is
between 182.42 and the total sum of the length of lineament in the area is 1223.57km. The minimum length of lineament in
the study area is 0.58km and the maximum length is 183.00km.
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6.7 Drainage distribution of the study area
6.7.1 Drainage Density
Drainage pattern is one of the most important indicators of hydrogeological features, because drainage pattern, texture and
density are controlled in a fundamental way by the underlying lithology. In addition, the drainage pattern is a reflection of
the rate that precipitation infiltrates compared with surface runoff. The infiltration-runoff relationship is controlled largely by
permeability, which is in turn, a function of the rock type and fracturing of the underlying rock or bedrock surface (Edet et
al. 1998).
The drainage pattern in the study area is dendritic in nature and are structurally controlled (Figure 14). The drainage density
map generated for the study area (Figure 15) reveals that there are more drainages around Emure-Owo (1.15km/km2) (Table
2) than other parts of the study area. Uso-Owo has drainage density of between 0.5 and 0.85km/km2. Ogbesse and Alayere
have drainage densities between 0.05 and 0.45km/km2. Oba-Akoko has drainage density between 0.15 and 0.55km/km2.
Drainage density between 0.55 and 0.8km/km2 are found on the north-western part of Owo. On the north-eastern part, the
drainage density is between 0.35 and 0.6km/km2. On the southern part of Owo (Sanusi, Ipele and Ita-Ipele), the drainage
density is less than 0.25km/km2. The implication of these is that areas with high drainage densities will have less
groundwater potential, while areas with low drainage density will have high groundwater potential. Therefore, lesser
groundwater potential is expected around Emure and Uso-Owo, while high groundwater potential is expected around Owo
and Ipele area of the study area. Geologically, areas with higher drainage densities tend to have lower groundwater potential.
This condition is observable in unfractured rocks type. The soil types in this type of area are usually less porous and less
permeable making the loss of groundwater to the surface more prominent. However, in areas with less drainage densities, the
rock would either have a primary or secondary porosity with the ability to allow the easy flow of groundwater. The soil types
in this type of area are usually well drained, which makes more groundwater to be retained within the subsurface rather
flowing to the surface.
Figure 9: Rose diagram for lineaments in the study area
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Sciences iSTEAMS Research Nexus 2014, Afe babalola University, Ado Ekiti, Nigeria – May 29-31st, 2014.
N%
L%
Figure 10: Correlation between the frequency/length and azimuth of lineament in the study area
6.7.2 Normalized Difference Vegetation Index (NDVI) and its implication for groundwater occurrence in the study
Area
The NDVI analysis of the study area shows that more than sixty percent (60%) of the study area have healthy vegetation
(white part), while about forty percent (40%) have non-healthy or no vegetation (Figure 16). Healthy vegetation is common
around Ogbesse, Uso-Owo, Alayere, Emure-Owo, Amurin-Owo, Ipele-Owo, parts of Isijogun, Ijegunmo, Sanusi and ObaAkoko. Areas of non-vegetation or unhealthy vegetation (black part) are common in areas with rock outcrops. This is the
case in Oba-Akoko, Isijogun, Ijegunmo and Sanusi. However, healthy vegetation is also found in lowland areas and river
courses. The geologic implications of healthy vegetation as indicated by NDVI to groundwater is that more subsurface water
will be found in areas with healthy vegetation than areas with non-healthy vegetation.
Areas with healthy vegetation, low drainage density, high intersecting lineament and well drained soils are good potential
areas for groundwater recharge. The recharge areas as confirmed by the groundwater flow pattern and the NDVI (Figure 16)
confirms that are more recharge zones in the study area than discharge areas. Areas with lesser outcrop are observed to
contain healthier vegetation than areas with high outcrop. This observable around Oba-Akoko of the study area (Figure 16).
Figure 11: Lineament density map of the study area
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Proceedings of the International Conference on Science, Technology, Education, Arts, Management and Social
Sciences iSTEAMS Research Nexus 2014, Afe babalola University, Ado Ekiti, Nigeria – May 29-31st, 2014.
Figure 12: Lineament distribution in the study area
6.8 Groundwater potential of the study area
The groundwater potential map of the study area is as shown in Figure 17. Table 1 show the score value used in estimating
the groundwater potential of the study area. Generally, the groundwater potential of the study area is high. However, there is
variation in the potential distribution. The southern parts of Owo Township have the highest groundwater potential than any
other parts of the study area. This followed by the central part of Owo Township and Emure-Owo. Ipele-Owo has more
groundwater potential than Oba-Akoko which in turn has more groundwater potential than Alayere area. Lesser groundwater
potentials are observable in the northeastern and northwestern parts of Uso-Owo. This is also observable in the southern part
of Alayere in the study area.
For any productive well to be dug, Owo Township, Ipele-Owo, Emure-Owo and the southern part of Owo will be the safest
area to explore for groundwater due to its high potential to store and transmit undergroundwater. This is followed by
Ogbesse, Uso-Owo, Oba-Akoko and Alayere areas respectively. Over fifty (50) percent of wells studied were found in areas
with high-moderately high groundwater potential (Figure 18). Over thirty (30) percent of wells in the study area are found
within the moderately high to moderate groundwater potential areas. About twenty (20) percent of the wells studied were
found within areas with low groundwater potential.
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Proceedings of the International Conference on Science, Technology, Education, Arts, Management and Social
Sciences iSTEAMS Research Nexus 2014, Afe babalola University, Ado Ekiti, Nigeria – May 29-31st, 2014.
Figure 13: Lineament intersection map of the study area
Figure 14: The effect of lineament on drainage pattern and distribution in the study area
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Proceedings of the International Conference on Science, Technology, Education, Arts, Management and Social
Sciences iSTEAMS Research Nexus 2014, Afe babalola University, Ado Ekiti, Nigeria – May 29-31st, 2014.
Figure 15: Drainage density map of the study area
Figure 16:Lineament overlaid over the NDVI map for delineating recharge zones in the study area
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Proceedings of the International Conference on Science, Technology, Education, Arts, Management and Social
Sciences iSTEAMS Research Nexus 2014, Afe babalola University, Ado Ekiti, Nigeria – May 29-31st, 2014.
Figure 17: Groundwater potential map of the study areas
Figure 18: Correlation of wells with groundwater potential of the study area
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Proceedings of the International Conference on Science, Technology, Education, Arts, Management and Social
Sciences iSTEAMS Research Nexus 2014, Afe babalola University, Ado Ekiti, Nigeria – May 29-31st, 2014.
7. CONCLUSION
The importance of remote sensing and Geographic Information System (GIS) in hydrogeological characterization cannot be
overestimated. In this research work, remote sensing and GIS techniques were employed to characterize the hydrogeology
Owo and its environment, southwestern Nigeria. The lineament distribution in the study area is polymodal with three peaks
with azimuth 80o-100o having the highest percentage (27%). The East-West (90o) fractures are most prominent. The broad,
positive correlation in frequency and length of the lineament suggest that they are of geological origin. Lineament
distribution is most prominent in areas underlain by migmatite and accounts for 78.78% of the total lineament across the area
due to its area of coverage. The lineament density around Owo (Ijegunmo, Isijogun and Sanusi) has higher lineament density
in the study which is greater 0.85km/km2. There are more lineaments intersecting at the southeastern part of Owo Township
around Iyere (18.0). The drainage density map generated for the study area reveals that there are more drainage around
Emure-Owo (1.15km/km2) than other parts of the study area.
The NDVI analysis of the study area shows that more than sixty percent (60%) of the study area have healthy vegetation
(white part), while about thirty percent (40%) have non-healthy or no vegetation. The implication of this is that areas with
healthy vegetation will have more groundwater than areas will lesser healthy vegetation. The groundwater flow pattern of the
area showed that there more recharges areas than discharge areas in the study area, which shows that the expected
groundwater potential of the area is high. The study further revealed that the groundwater flow pattern in the study area is
structurally controlled by the distribution of lineaments. The groundwater potential map revealed that the southern parts of
Owo Township have the highest groundwater potential than any other parts of the study area.Over sixty percent of wells in
the study area are found within the moderately high-moderate groundwater potential areas. Thirty percent of the wells
studied were found within areas with low groundwater potential. It was observed that all the wells studied are found close to
or on a fracture zone.
Table 1:Score value for groundwater potential of the study area
S/N
Easting
Northing
Lithology
Lineament
density
(km/km2)
Drainage
Density
(km/km2)
Topographic
elevation (ft)
Slope
gradient (o)
Land
Use
Annual
Rainfall
(mm)
Groundwater
flow
Total
1.
2.
3.
4.
5.
6.
7.
8.
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
5.3661
5.3691
5.3759
5.3703
5.3787
5.4527
5.4386
5.9071
5.4514
5.4567
5.5534
5.5509
5.5515
5.5497
5.5496
5.6498
5.6554
5.6476
5.6504
5.6718
5.7203
5.7233
5.7208
5.7214
5.7228
7.4116
7.3435
7.2338
7.1590
7.0595
7.4073
7.3546
7.2517
7.1420
7.0655
7.4056
7.3316
7.2509
7.1497
7.0510
7.4082
7.3333
7.2594
7.1412
7.0157
7.4065
7.3435
7.2483
7.1369
7.0672
15
15
15
15
15
15
15
15
15
15
15
15
15
15
15
15
15
15
15
15
15
15
15
15
15
30
30
30
30
30
40
30
30
30
30
30
30
30
40
40
30
30
30
40
40
40
30
30
30
30
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
50
50
50
50
50
50
50
50
50
50
50
50
50
50
50
50
50
50
50
50
50
50
50
50
50
30
20
30
30
10
20
20
20
30
20
20
30
20
20
30
30
30
30
30
20
20
20
20
20
20
20
30
70
70
20
70
60
30
30
30
60
70
70
70
60
70
60
60
80
100
60
60
60
60
70
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
20
20
100
50
50
70
100
100
50
20
20
20
100
80
100
20
20
100
80
100
20
20
100
100
70
275
275
405
355
285
375
395
355
315
285
305
335
395
395
405
325
335
415
415
435
325
300
380
385
370
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Proceedings of the International Conference on Science, Technology, Education, Arts, Management and Social
Sciences iSTEAMS Research Nexus 2014, Afe babalola University, Ado Ekiti, Nigeria – May 29-31st, 2014.
Table 2: Lineament intersection and drainage density data of the study area
S/N
1.
2.
Northing
5.3562
7.3455
Easting
7.4098
5.3638
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
21.
22.
23.
24.
25.
7.2504
7.153
7.0638
7.4090
7.3518
7.2433
7.1565
7.0541
7.4056
7.3531
7.2408
7.1523
7.0676
7.4086
7.3645
7.2492
7.1533
7.0638
7.4090
7.3395
7.2692
7.1562
7.0588
5.3612
5.3612
5.3684
5.4481
5.4476
5.4608
5.4493
5.4498
5.5505
5.4515
5.5425
5.5501
5.5493
5.6615
5.6446
5.6446
5.6462
5.6327
5.7250
5.7204
5.7301
5.7229
5.7246
Lineament Intersection
01
01
Table 3: Analysis of lineaments in the study area
Frequency
S/N
Azimuth (o)
1.
0-10
03
2.
11-20
06
3.
21-30
06
4.
31-40
09
5.
41-50
28
6.
51-60
24
7.
61-70
25
8.
71-80
21
9.
81-90
58
10.
91-100
30
11.
101-110
19
12.
111-120
21
13.
121-130
27
14.
131-140
28
15.
141-150
11
16.
151-160
08
17.
161-170
02
18.
171-180
04
Drainage Density(km/km2)
0.0546
0.1731
03
0
0
01
02
01
04
02
00
12
08
12
15
01
14
06
18
12
02
05
03
05
08
Length (km)
3.66
17.99
25.74
24.43
80.78
92.21
75.69
91.50
361.55
70.92
51.85
78.70
80.52
79.23
42.38
36.60
5.11
4.71
353
0.1149
0.3802
0.2130
0.0562
0.5542
0.2891
0.4050
0.5225
0.0261
0.8498
0.4687
0.6651
0.4846
0.1097
1.1089
1.0331
0.8102
0.2036
0.5529
0.6329
0.8579
0.3779
0.2698
% Frequency
0.91
1.82
1.82
2.73
8.49
7.27
7.58
6.36
17.58
9.09
5.76
6.36
8.18
8.49
3.33
2.42
1.55
1.43
% Length
0.30
1.47
2.10
1.20
6.60
7.54
6.19
7.48
29.55
5.80
4.24
6.43
6.58
6.48
3.47
2.99
0.42
0.39
Proceedings of the International Conference on Science, Technology, Education, Arts, Management and Social
Sciences iSTEAMS Research Nexus 2014, Afe babalola University, Ado Ekiti, Nigeria – May 29-31st, 2014.
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