Okwu Delunzu, et. al. REJOEN 1,2018, 63 83 Assessment of

63

Assessment of groundwater potential in Anambra state using GIS and remote sensing

Okwu-Delunzu V.U., Chukwu K.E & Okoroji V.

Department of Geography and Meteorology, Faculty of Environmental Sciences, Enugu State University of Science and Technology, Agbani, Enugu state

Nigeria.

ARTICLE INFO

Article history: Received 16th Feb, 2018 Received in revised form 30th Feb, 2018 Accepted March 24th, 2018 Available online 30th August 2018

ABSTRACT

Groundwater is an important source of reliable water for various uses; therefore exploration in countries with scarce water resources requires the implementa-tion of effective tools that save time and money. In this study, geographic infor-mation systems (GIS) tools and remote sensing data were used to assess groundwater potential in Anambra State, Nigeria, to understand areas with bet-ter groundwater. In doing this the Landsat8 images of 2015 and the Shuttle Radar Topography Mission (SRTM) of 90m resolution of the study area were acquired from United State Geological Survey (USGS), The Geological map of the study area was extracted from internet, the ARC GIS 10.1 (Extension spa-tial analyst) and arc hydro extension was used for the data analysis. The SRTM Dem data was imported to Arc GIS 10.1 for hydro processing; the spatial anal-ysis tool was used to generate the hydrology such as, slope, flow direction, flow accumulation, the streams, drainage basin and drainage density. The geology data of the area was extracted from digitization of lithology map of Anambra State for calculation of drainage density for the area. Catchment area, were first calculated, then the lengths of all channels within the basin's boundaries (rivers, streams, etc.), the Calculate geometric option was chosen to calculate the length of all water channel of the study area, as well as the area for the catchment area. Supervised classification using the Gaussian Maximum Likelihood technique was used to create seven classes of the land area: (1) Forest, (2) Savannah, (3) Farm Land, (4) Built up Area, (5) River, (6) Sand and (7) swamp. The result of the analysis shows that, very Good groundwater potential in Anambra state vary from one LGA to another: Ayamelum has the best groundwater potential followed by Anambra West ,Ogbaru, Onitsha South, and Awka North. Some other parts of the LGA such as Ihiala Ekwusigo, Idemili North and South, Awka South , Newi North and South, Onitsha North, Orumba North and South, Oyi and Anambra East, Dunukofia has good ground water potentials whereas other area such as Idemili North, Njikoka , Nnewi North and South and Oyi has moderate groundwater potential. Others have poor or no groundwater water potential. This study therefore has given in a view (map) the groundwater po-tentials of Anambra State, to help hydrologist, hydrogeologist and others in related field to know the best place to assess their groundwater needs

needs.

Keywords: Ground water GIS Remote Sensing Anambra

Corresponding Author

E-mail Address: : [email protected] 08037363891

https://doi.org/10.36265/rejoen.2018.010108

ISSN - 1597 - 4488 publishingrealtime.

All right reserved.

1. Introduction

Groundwater could be defined as water situated below the ground surface in soil pore spaces and in the fractures of

lithologic formations. A unit of rock or an unconsolidated deposit, called an aquifer when it is capable of producing a usable quantity of water (Alabi, Bello, Ogunbge & Oyerinde 2010). It is a known fact that nearly all the water in the ground comes from rain that has infiltrated into the earth. Thus rainfall replenishes all other natural water source

Okwu-Delunzu, et. al. REJOEN 1,2018, 63-83

64

(Chukwudelunzu 2001). Hydrological studies have also shown that when rain falls, part of it run-off over the surface of the ground; the other part infiltrates underground and be-come the groundwater which accounts for the water for springs, lakes and wells (Oseji, Asokhia,& Okolie 2006) .Groundwater is used for many purposes such as agri-cultural, municipal and industrial purposes through the con-struction/extraction of wells. Groundwater is also widely used for drinking and irrigation (UNESCO,2004). According to Alabi et al.2010, about 53% of the world population de-pends on groundwater as a source of drinking water. Water is an indispensable resource and the concern of many earth scientists and researchers have been on the acquisition of a reliable source of drinking water (Akinbinu, 2015). Surface and groundwater resources are abundant in Nigeria

Groundwater is one of the most important natural resource of the earth required for drinking, irrigation and industriali-zation etc, but the resource quantity or quality is often not known or assessed. The resource can be optimally used and sustained only when quantity and quality of groundwater is assessed or measured. It has been observed that lack of standardization of methodology in estimating the groundwa-ter and improper tools for handling the same, leads to mis-calculation of the actual quantity and quality of groundwater. It is essential to maintain a proper balance between the groundwater quantity and its exploitation. Otherwise it will leads to large scale decline of groundwater levels, which ultimately cause a serious problem for sustainable agricultur-al production and other groundwater usages.

The demand for water has increased over the years and this has led to water scarcity in many parts of Nigeria. The situa-tion is aggravated by the problem of water pollution or con-tamination. The study area, Anambra State is not an excep-tion to the above water problems, The area under investiga-tion is a fast growing community in terms of population and business activities. This has impacted on the growing de-mand for portable water. Suffice it to say that the area has no public water supply and depends on personal efforts in get-ting water for domestic use, the area is almost heading to-wards a fresh water crisis mainly due to improper manage-ment of water resources and environmental degradation. This situation has resulted into lack of access to safe potable water supply to millions of people. This freshwater crisis is already evident in many parts of state, varying in scale and intensity depending mainly on the time of the year, location of the place and climatic variability issues. The occurrence and movement of groundwater in an area is governed by several factors such as topography, lithology, geological structure, depth of weathering, slope, land use/ land cover (LULC) and interrelationship between these factors. There-fore this work aims to assess groundwater resource in the study area using remote sensing and geographical Infor-mation System, which requires data from geophysical survey and Remote sensing technique in order to assess the ground-water potential in Anambra State. This aim is achieved by producing the lithology map of the study area, evaluate the Slope of the study area, delineate the drainage and drainage density of the study area, represent the topography and the slope of the study area, estimate the landuse land cover of the study area and from assessment of the above, the areas with good ground water potentials will be determined.

2.0 Study Area

The Anambra State lies within longitudes 6°34' and 7°48'’E and latitudes 5°40' and 6°48'N. (Figure 1.1 and figure 1.2) and covers an estimated surface area of 7200km2. It has neighbouring State as Enugu State, in the East Delta State in West, Imo in the South and Kogi in North. The area is underlain by Cretaceous to Recent sedimentary for-mations of the Anambra Basin that are of varying aquifer potentials. Several studies including those of Ezeigbo, 1987; Ezeigbo and Ozoko, 1989; Egboka, 1990 and 1993; Ezenwa, 1996; Onwuemesi and Olaniyan, 1996 and Ofomah and Ezeigbo, 1997 have reported aspects of the hydrogeology and quality status of groundwater within the State. These reports indicated that groundwater within the State consists predominantly of low concentrations of ma-jor ions and microbial content and consequently suitable for domestic purposes. Despite these investigations, very little information yet exists on the nature of aquifer distribution and their properties, within the formations that underlie the study area.

Figure 1.1: Map of Nigeria showing Anambra State. (Produced in GIS with Nigeria geospatial data.)

Figure 1.2: Administrative map of Anambra State (Produced in GIS with Nigeria geospatial data.)

65

2.1 Geologic Units within the Anambra Basin: The Basin is dominantly filled with plastic sediments consti-tuting several distinct lithostratigraphic units ranging from Upper Campania to Recent in age. The lithostratigraphic units have a thickness of up to 2500m (Reyment, 1965) and consist of Nkporo Shale, Mamu Formation, Ajali Sandstone, Nsukka Formation, Imo Shale, Ameki Formation, Nanka Sands, Ogwashi-Asaba Formation, Benin Formation and the Alluvial plain Sands. The source of the sediments into the basin is principally from the Cameroon massif and the Aba-kaliki synclinorium (Nfor, 2003). The general stratigraphy of the Anambra-Abakaliki basins is presented in figure 1.3 Be-low.

Figure 1.3: Geological Map of Anambra State, (Source :Egboka B.C, Okoyeh E. I, 2016) 2.2. Review of Related Studies

In some works of groundwater assessment, Daniel N. Obio-ra, Adeolu E. Ajala and Johnson C. Ibuot, (2015), used surfi-cial electrical resistivity method to investigate groundwater flow potential in makurdi, north central Nigeria, Vertical electrical sounding (VES) employing Schlumberger elec-trode configuration was carried out. This was done in thirty locations to determine the aquifer resistivity, thickness, lon-gitudinal conductance, hydraulic conductivity and transmis-sivity. From the result, the averages and ranges of these pa-rameters were determined. 2D contour maps of aquifer resis-tivity, aquifer thickness, longitudinal conductance, hydraulic conductivity and transmissivity were drawn. The distribution of thickness and transmissivity maps provided a means of identifying areas where aquiferous zone is prolific. Similarly Obiajulu and Okpoko(2015); used the electrical resistivity method to determine the groundwater potential of Ihiala and its environ. The lithostratigraphic units within the study area include: Benin Formation and Ogwashi Asaba Formation. Twelve vertical electrical soundings (VES) were carried out with the Abem Tetrameter (SAS 1000) using the chlumberger electrode configuration, with a maximum cur-rent electrode spacing (AB) of 1000 meters. The interpreta-tion of the VES data was carried out by computer iteration using win Resist software. The result obtained from the study area within the geological terrain often referred to as

sedimentary environment revealed four to seven geo-electric layers at the various locations Accordingly Nfor, Olobaniyi, and Ogala,(2007) Investigated the extent and Distribution of Groundwater Resources in Parts of Anambra State, Southeastern, Nigeria, Pre-drilling geophysical surveys were conducted at each site with an SAS 300B ABEM Terrameter and its accessories, using the Schlumberger configuration. The main objective of the sur-veys was to determine the depths to potable water. Probe depth (AB/2) was 600m. Hydrogeological/geological sur-veys were undertaken on existing boreholes with the aim of knowing the static water level, drilled depths, casing and screen positions etc. During drilling, return cuttings were collected at 1meter-drilled depth interval and used to study grain-size, colour and associated interstitial materials useful in the determination of screen slot and gravel pack specifica-tion. After drilling to target depth, each borehole was logged for electromagnetic properties including spontaneous poten-tial and resistivity (16’’short normal and 64’’ long normal) using ABEM Terrameter. In the absence of observation wells, all measurements during pumping tests were done on the pumping wells. An integration of the results of predrill-ing geophysical survey, hydrogeological/geological survey, drill cuttings, granulometric analysis, down-hole logging, drill time and pumping test/analysis for each borehole, pro-vided the basis for establishing the extent and distribution of the groundwater resources in Anambra State. Anand Kumar (2010), in his study Applied Remote Sensing and GIS in Groundwater Prospects Mapping and Sitting Re-charge Structures, This study was carried out for some parts of Bhilwara district, Rajasthan to explore the groundwater prospects of the area. All the hydro-geological themes was created by the interpretation of satellite data and subsequent-ly verified by field check. Apart from this, a hydrological and base theme was also created in GIS. All the themes was integrated and analyzed to prepare the groundwater pro-spects maps. Based on the hydrogeology and drainage pat-tern, suitable site for recharge structures was suggested in the map. In the same vain Jawad Al-Bakri, & Yahya Al-Jahmany,(2013), applied GIS and Remote Sensing to Groundwater Exploration in Al-Wala Basin in Jordan. In this study, geo-graphic information systems (GIS) tools and remote sensing data were used to prepare and analyze digital layers of lithol-ogy, geological structure, drainage and topography to detect the most promising sites for groundwater exploration in an arid basin in Jordan. A separate map of existing wells was intersected with the generated maps to calculate the percent-age of wells in each interval of density and count of linea-ments and drainage. Different GIS functions of intersection and spatial query were then applied to produce the final map for the most promising sites for groundwater exploration. The possibility of using digital classification of remote sens-ing data for mapping the most promising sites for groundwa-ter exploration was also investigated by applying unsuper-vised classification to a Landsat ETM+ image. Results showed that spatial distribution of the most promising sites for groundwater exploration was dependent on the interrelat-ed factors of lithology, topography and geologic structure. The most promising sites were distributed within 4% of the study area. The highest percentage of groundwater wells was within the alluvial and wadi sediments, which were accurate-ly detected by the digitally classified ETM+. The study showed that remote sensing and GIS provided efficient tools


66

for mapping promising sites for groundwater exploration. In a similar vain this work is applying GIS and Remote Sensing to asses groundwater potentials in Anambra State thus the gap it wants to fill in and contribute to Knowledge 3.0 Methodology To assess and map out the groundwater potential area in Anambra State Using GIS and remote sensing technology, data acquisition and data processing are explained below. 3.1 Data Acquisition

The major data input for this study includes; The Shuttle Radar Topography Mission (SRTM) of 90m resolution of the study area extracted from Global land Cover Facility (GLCF) web site : http://glcf.umd.edu/data/srtm/ (Figure 3.1). The Landsat8 images of 2015 acquired from United State Geo-logical Survey (USGS).(Fig 3.1b). The Geological map of the study area was extracted from internet on the research

(A) Shuttle Radar Topogra-

phy Mission (SRTM) of

Anambra State

Figure 3.1a & b. Map of SRTM and CBLandsat8 of Anambra (State Source: http://glcf.umd.edu/data/srtm/ )

entitle: Extent and Distribution of Groundwater Resources in Parts of Anambra State, Southeastern, Nigeria (Nfor, Olobaniyi, Ogala, 2007). The Geophysical survey was conducted in three local Government areas (Onitsha North, Idemili North, Nnewi South) in Anambra state for verification and confirmation of result generated from GIS and remote sensing Analysis.

67

(B): Composite band of

Landsat8 of Anambra

State

Figure 3.1a & b. Map of SRTM and CBLandsat8 of Anambra (State Source: http://glcf.umd.edu/data/srtm/ )

3.2 Method of Data Analysis

3.3.1 Data processing.

At the geographical Information System (GIS) environment,

the ARC GIS 10.1 (Extension spatial analyst) and arc hydro

extension was used for the data analysis. The SRTM Dem

data was imported to Arc GIS 10.1 for hydro processing, the

spatial analysis tool was used to generate the hydrology

such as, slope , flow direction, flow accumulation, the

streams, drainage basin and drainage density . All this data

were derived from Shuttle Radar Topographic Mission

(SRTM) data gotten from satellite imageries. Grid interpola-

tion was carried out with 3D spatial analysis tool to produce

digital Terrain model (DTM). The lithology data was ex-

tracted from digitization of lithology map of Amanbra State.

The thematic maps so prepared were converted into raster

form so that they can be easily integrated using GIS. Each

of these thematic maps has been assigned suitable weight-

age factor.

3.3.2. Calculating Geometry and Drainage Density

In order to calculate drainage density for Anambra State

Catchment area, we first calculate the lengths of all chan-

nels within the basin's boundaries (rivers, streams, etc.);

the Calculate geometric option was chosen to calculate the

length of all water channels of the study area, as well as

the area for the catchment area. The sum of the stream

length was calculated within each catchment area using

spatial joining data from another table (Stream Link) base

on spatial location (fig3.2).


68

Figure 3.2: Spatial joining Data from another table (Stream Link) The stream link feature and the catchment area were con-verted in raster using stream length and catchment area re-spectively. Drainage density is calculated using the formula:

The raster calculator tool Figure 3.3 below was used to cal-culate the drainage density using the formula above.

69

Figure 3.3: Raster calculator

3.3.3 Maximum Likelihood Image Classification Supervised classification using the Gaussian Maximum Likelihood technique was used to create five classes: (1) Forest, (2) Savannah, (3) Farm Land, (4) Built up Area, (5) River, (6) Sand and (7) swamp. These land use land cover classes were derived from Land sat 8 imagery of 2016 for the study areas. This was due to the fact that the operator has familiarized himself with the study area through dedi-cated field observation, whereby the spectral characteristics of the classes in the sampled area have been identified. At

least five samples set was selected in training site for each classes to indicate their spectral signature (Figure 3.4. be-low). The Maximum likelihood algorithm was applied in ArcGis 10.1 for image classification which generate up to one hundred classes based on spectral signature prede-fined, the recode tool under GIS analysis in Erdas was used to reclassify the image into seven major classes. Fig-ure 3.9 below is the image classification process in ArcGis 10.1 environment

70

Figure 3.2: Spatial joining Data from another table (Stream Link)

Figure 3.4: Maximum likelihood image classification process.

3.3.4. GIS Ranking and Determination of Ground potential

The thematic layers (Land uses, Geology, Slope, Drainage

Density, and Elevation) were rank in GIS, environment

based on their influence in the suitability of groundwater

potential area. The Ranking value assigned to the features

categories were:

= Which was given to the feature classes with very high

influence factor?

= Which was given to feature classes with high influence

factor?

= Which was given to medium influence factor and

= Which was given to low influence factor. (See table 3.1

Below).

The integration of various thematic maps describing favora-

ble groundwater zones into a single groundwater potential

map has been carried out through the application of GIS. It

required mainly three steps of spatial database building, spa-

tial data analysis and data integration. Spatial data analysis is

an analytical technique associated with the study of locations

of geographic phenomena together with their spatial dimen-

sion and their associated attributes (like table analysis, classi-

fication, polygon classification, and weight classification).

All thematic maps were reclassified and assigned suitable

ranking values. Layers were aggregated in a linear combina-

tion equation in Arc Map GIS Raster Calculator module as

given here:

Groundwater= "Geology_class.tif" + "slope_reclass1.tif"

+ "Landuse_reclass2.tif" + "Drainage_density.tif" +

"Elevation_reclass.tif"

The resultant map is classified into very good, good, moder-

ate and poor groundwater prospective zones.


71

Figure 3.5: Ranking Process of thematic layer using raster Calculation.

Thematic Layers Features Categories Rank

Landuse

Forest 2

Savannah 2

Farm Land 2

Built Up Area 4

River 1

Sand 1

Swamp 1

Geology

Alluvial Plain Deposits 1

Imo Shale 2

Nanka / Ameki Sand 4

Ogwashi-Asaba 3

Slope

0 - 1.07 (Gentle) 1

1.07 - 2.24 (Moderate) 1

2.24 - 3.84 (Moderatly Steep) 2

3.84 - 5.98(Steep) 2

5.98 - 9.29 (Very Steep) 3

9.29 - 27.22 (Escape Steep) 4

Darinage Density

0.0 - 0.002 (Poor) 1

0.002 - 0.01 (Medium) 2

0.01 - 0.05 (High) 3

0.05 - 0.1 (Very High) 4

Elevation

Canyons, deeply incised streams 1

U shaped valleys 1

Plains 2

Open slopes 3

Upper slopes, mesas 4

Mountain tops, high ridges 4

Table 3.1: Ranking of thematic Layer based on their influence Factor.

72

4.0 Data Presentation and Analysis

4.1. Lithology of the Study Area

The spatial distribution of lithologic outcrops and formations

within the study area is presented in figure 4.1. The Anambra

state lithology is comprise of four type such as Alluvial plain

Sands deposited by the river, the sand and silt, the Ameki/

Nanka Sands and the Ogwashi- Asaba Formation. Sand-

wiched between the Alluvial plain Sands and the Imo Shale,

around the central and southern portions of the study area, are

two formations, the Ogwashi- Asaba Formation and the

Ameki/Nanka Sands. The lithostratigraphic sequence within

the Ogwashi-Asaba Formation underlains towns extending

from Oba, Oraifite, Nnewi to parts of Ihiala etc. It consists of

a top layer of black to brownish humus and laterite, under-

lain by horizons of sands, clays, gravels and cobbles with

intercalations of brown to black lignitic coal. The Ameki/

Nanka Sands consists of a top lateritic sandy layer underlain

by a near monotonous sandy horizon, with occasional inter-

calations of thin clay and gravelly beds. Alluvial plain Sands

deposited by the river underlains town extending from

Gbedor, Orometiti and Ochuche while Imo shale underlain

towns extending from Umueje, Anaku,Shagu.

Figure 4.1. Geological Map Of Anambra State.


73

4.2 Evaluation of Slope of Anambra State the Study Area Slope of an area represents steepness or inclination of an area determined from two points on a line. Slope plays a vital role in determining soil erosion in hilly terrain. A steep slope will cause more runoff and will enhance the soil erosion in absence of vegetation cover leading to land degradation. Based on the slope value (in Degree Celsus) the entire catchment was classified into six categories. The gentle slope varied from 0 to 1.07 degree celcus is. This region of low slope comprised of low lying plains and flat lands and is conterminous with the flood plain of Anambra State. The moderate and moderately slope varied from 1.07 to 2.24 and 2.24 to 3.84 Degree Celsus respectively, it mostly narrow strip of land.

The steep slope region varied from 3.84 to 5.98 Degree Cel-sus is partially under thick forest cover and partially under pockets of bare ground and sizable pastures. Very steep slope region varied from 5.98 to 9.29 Degree Celsus is highly rugged and dissected by narrow and deep river valleys and is dominated by peaks and scarps. The region with slope of above 9.29 Degree Celsus is consti-tuted of escarpment, deep gorges and peaks. Gentle slope of 0 to 1.07 degree celcus indicates the presence of high groundwater potential zones, high slope >9.29 shows the presence of poor groundwater potential zones as water runs rapidly off the surface.

74

Figure 4.2. Slope Map of Anambra State. 4.3. Estimation of Land Use/ land cover (LULC) of the Study Area

The LULC of the area provides important indications of the extent of groundwater requirement and utilization (Narendra et al. 2013). The synoptic viewing through remote sensing has provided the multi-spectral data, which has been utilized for classifying LULC. The land use/land cover map (Figure 4.3) of the entire catchment was generated and the derived statistical data (Table 4.1).

The major land use/land cover classes such as Forest (13.10%), Savannah (7.13%), Farm land (10.25%), Built up area (3.96%), River (0.9%), Sand (55.287%), Swamp Area (9.30%). From the point of view of land use, Farm Land and swamp area is an excellent site for groundwater exploration. The area with water bodies is good for groundwater re-charge. the catchment area, covered Sand, Savannah, For-est,Swamp area land and water bodies is favourable for groundwater potential.

Value Class Count Area (km2) Area (%)

1 Forest 6439959 5795.96 13.10

2 Savannah 3502974 3152.68 7.13

3 Farm Land 5040004 4536.00 10.25

4 Built Up Area 1946014 1751.41 3.96

5 Water Body 478649 430.78 0.97

6 Sand 27174387 24456.95 55.28

7 Swamp Area 4573446 4116.10 9.30

TOTAL 49155433 44239.89 100

Table 4.1: Statistical table of Land Use/Land Cover (LULC)

Figure 4.3: Land Use Land Cover map of Anambra State.


75

4.4 Representation Topography of study area

Significant topographic units commonly observed on the basis of their image characteristics include canyons, deeply incised streams, U- shaped valleys, plains, open slopes, upper slopes, mesas, mountain tops, high ridges. The topographic of the area varie from 3m to 385m level above the sea. see figure (4.4). (i) From 3 to 66.667m the area is Canyons, deeply in-cised stream (ii) From 66.667 to 130.333m the area is U shaped val-leys

(iii) From 130.333 to 194m the region is a plain area. (iv) From 194 to 257.667m the region is open slope area (v) From 257.667 to 321.333 the region is upper slope area with mesas. (vi) From 321.33 to 385 the region is hilling area , top mountain with high ridge. The lower relief areas, from 3 to 130.333 are characterized by softer lithology permitting more recharge to groundwater, whereas high relief areas, with elevation 194 to 389 m eleva-tion comprising have hard and massive rocks forming runoff zone.

Figure 4.4. Digital Terrain Model Map of The Study Area. 4.5. Determination of Drainage of the study area A drainage map of the area gives an idea about the permeabil-ity of rocks and also gives an indication of the yield of the basin (Wisler and Brater 1959). Evaluation of the drainage map (Figure 3) reveals that the catchment is consequent in nature mainly due to the original slope of the land surface. The flow of the direction of tributaries joining the main

stream is controlled by structural features. Majority of the lower order streams are found to be in sequent in nature joining the higher order main stream at higher angles and lacking structural and geological controls. The tributaries have spread irregularly in all directions and join the main stream at all angles.

76

Figure 4.5. Drainage Map of The Study Area.

4.6 Generation of Drainage Density of the study area

Drainage density is the ratio of the total length of the stream

to the area of the drainage basin. The drainage density map

shows that generally the drainage density in Anambra State

is poor ranging Between 0 to 0.002, except of Umue-

je,Igbeodor, Anaku area,Ishiagu, Onitsha and Azia that have

a medium drainage ranging between 0.002 to 0.01m/m2. The

high density is between 0.01 and above and its located at

Isiagu, Ezira, Ochuche and Anaku village. High drainage

density is an unfavourable site for groundwater existence,

moderate drainage density has moderate groundwater poten-

tial and less/no drainage density is high groundwater poten-

tial zone [44]. Drainage density map of the study area is

shown in Figure 4.6.


77

Figure 4.6. Drainage Density Map of The Study Area. 4.7 Discussion

4.7.1 Groundwater Potential

The table below shows the distribution of groundwater po-tential in Anambra State The level of groundwater varies from Very Good , Good , Moderate, Poor and Very poor.

78

Table 4.2: Statistical table of Groundwater potential (LULC) the Study area.

S/N LGA Area (Km2)

Very Good (Km)

Pct (%)

Good (Km2)

Pct (%)

Moder-ate (Km2)

Pct (%)

Poor (Km2

) Pct (%)

Very Poor (Km2)

Pct (%)

Total (%)

1 Aguata 162.2 0.0 0.0 4.0 2.5 38.9 24.0 94.5 58.3 2.1 1.3 86.0

2 Anambra East 378.9 98.7 26.1 144.4 38.1 101.5 26.8 26.5 7.0 2.9 0.8 98.7

3 Anambra West 740.5 598.3 80.8 4.3 0.6 0.0 0.0 0.0 0.0 0.0 0.0 81.4

4 Anaocha 104.9 0.0 0.0 5.5 5.2 27.6 26.3 70.7 67.4 1.0 1.0 100.0

5 Awka North 388.1 200.5 51.7 123.0 31.7 39.7 10.2 1.4 0.4 0.0 0.0 93.9

6 Awka South 170.8 7.6 4.4 46.5 27.2 77.1 45.1 36.0 21.1 1.2 0.7 98.5

7 Ayamelum 567.8 474.1 83.5 49.6 8.7 2.7 0.5 0.2 0.0 0.0 0.0 92.7

8 Dunukofia 58.4 0.0 0.0 14.4 24.6 34.0 58.3 9.8 16.7 0.2 0.3 99.9

9 Ekwusigo 107.0 16.6 15.5 55.0 51.5 31.1 29.1 3.9 3.7 0.2 0.2 99.9

10 Idemili North 87.3 0.0 0.0 25.8 29.5 49.9 57.2 11.7 13.4 0.0 0.0 100.1

11 Idemili South 110.7 0.5 0.4 54.5 49.2 47.5 42.9 8.2 7.4 0.1 0.1 99.9

12 Ihiala 221.5 3.9 1.8 140.9 63.6 46.6 21.0 7.7 3.5 0.0 0.0 89.9

13 Njikoka 93.7 0.0 0.0 10.4 11.1 47.6 50.8 33.3 35.5 2.5 2.7 100.0

14 Nnewi North 64.6 0.0 0.0 27.4 42.4 34.0 52.7 2.8 4.3 0.3 0.5 100.0

15 Nnewi South 168.1 0.0 0.0 62.3 37.1 80.0 47.6 9.6 5.7 0.3 0.2 90.5

16 Ogbaru 397.5 269.0 67.7 20.6 5.2 0.6 0.2 0.2 0.0 0.0 0.0 73.1

17 Onitsha North 28.0 2.1 7.6 11.5 41.0 5.9 21.1 0.3 1.1 0.0 0.0 70.8

18 Onitsha South 17.1 11.8 69.0 1.8 10.2 0.0 0.0 0.0 0.0 0.0 0.0 79.2

19 Orumba North 363.3 59.4 16.3 96.4 26.5 73.9 20.3 97.2 26.8 12.6 3.5 93.4

20 Orumba South 231.0 0.5 0.2 43.0 18.6 73.0 31.6 60.6 26.2 4.4 1.9 78.6

21 Oyi 131.2 0.0 0.0 33.5 25.5 67.9 51.7 26.2 20.0 3.4 2.6 99.8

Total 4592.5 1742.9 38.0 974.6 21.2 879.5 19.1 500.7 10.9 31.1 0.7 89.9


79

Figure 4.7: Groundwater potential map of Anambra State. 4.7.1.1 Very Good Groundwater

The Histogram 4.8 below shows that, the very Good ground-

water potential in Anambah state vary from one LGA to an-other. the Ayamelum has the best groundwater potential fol-lowing by Anambra West , Ogbaru , Onitsha South, and Aw-ka North.

80

Figure 4.8: Histogram of Very Good Groundwater

potential Area in Anambra State.

4.7.1.2 Good Groundwater Potential

The histogram 4.9 below show that the Good

groundwater potential is vary. Ihiala has the high

value following by Ekwusigo, Idemili North And

South,Awka North and South , Newi North and

South, Onitsha North, Orumba North and South,

Oyi and Anambra East,Dunukofia.

Figure 4.9: Histogram of Good Groundwater potential Area in Anambra State. 4.7.1.3 Moderate Groundwater Potential

The Histogram 4.10 below shows that Dunukofia has the Highest moderate value followed by Idemili North, Njiko-ka , Nnewi North and South and Oyi


81

Figure 4.10: Histogram of Moderate Groundwater potential Area in Anambra State. 4.7.1.4 Poor Groundwater Potential

The histogram 4.11 below shows that Anaocha has the poor-est groundwater potential followed by Aguata .

Figure 4.11: Histogram of Poor Groundwater potential Area in Anambra State. 4.7.1.5. Very Poor Groundwater Potential

The histogram 4.12 below show that Orumba North has the worst Groundwater potential, following by Njikoka , ,Orumba South and Oyi.

82

Figure 4.12: Histogram of very poor Groundwater potential Area in Anambra State.

5. Conclusion

Remote sensing and GIS is usefull in understanding the fac-tors responsible for maintaining the hydrological cycle; mainly the vegetal cover, surface water bodies, litho types and landform. They helped in integrating all the data to gen-erate various thematic maps in the study area such as: slope, drainage density, lithology, topography, land use/land cover and elevation for preparing water potential map. The result shows that, the very Good groundwater potential in Anamba state vary from one LGA to another: Ayamelum has the best groundwater potential following by Anambra West , Og-baru , Onitsha South, and Awka North. Some part LGA such as Ihiala Ekwusigo, Idemili North And South,Awka North and South , Newi North and South, Onitsha North, Orumba North and South, Oyi and Anambra East,Dunukofia . other area suh as Idemili North, Njikoka , Nnewi North and South and Oyi has moderate groundwater potential. Other has poor or no groundwater water potential The groundwater pro-spects maps form a very good database and help in identify-ing favourable zones (prospective zones) around the problem villages, thereby narrowing down the target areas. Then, by conducting detail ground hydro-geological and geophysical surveys within these zones, most appropriate sites can be selected for drilling. Recharge is the most important factor in groundwater studies. If sufficient recharge is not there, the most favorable aquifer zones will also become dry. It is true that satellite alone cannot provide information regarding confined aquifers, then geophysical and drilling data have to be consulted for acquiring subsurface information and deci-sions file shall be created through overlay by GIS technique. The groundwater prospects maps will serve the twin benefit of helping the field geologists to quickly identify the pro-spective groundwater zones for conducting site specific in-vestigations, Select the sites for planning recharge structures to improve sustainability of drinking water sources, wherev-er required. 5.2 Recommendation: Based on Findings of this Research Work the following Recommendation are made; 1. The groundwater potential map could be useful for various pur-poses such as the development of sustainable scheme for

groundwater in the area.

2. The integration of GIS and data extracted from satellite images coupled with geophysical data and the geological knowledge of the area under investigation, could provides a powerful tool in groundwater investigation. 3. Groundwater potential zones map revealed that the plain areas are prospective zones in the catchment and can be help-ful in better planning and management of ground resources Reference

A. Alabi, R. Bello, A. S. Ogungbe, H. O. Oyerinde, (2010). Determination of groundwater potential in Lagos State University, Ojo; using geoelectric methods (vertical elec-trical sounding and horizontal profiling), Report and Opinion, 2(5): 68-75

Anand Kumar 2015, Application of Remote Sensing and GIS in Groundwater Prospects Mapping & Siting Recharge Structures, Development Alternatives 111/9-Z, Kishan Garh Vasant Kunj /New Delhi – 110 070, INDIA/ Email: [email protected]/[email protected]/ Website : www.devalt.org

Amarachi R Alisiobi, and B. D. Ako, 2012: Groundwater Investigation Using Combined Geophysical Methods, AAPG Annual Convention and Exhibition, Long Beach, California, April 22-25, 2012,

Ayoade J .O. (1988). Tropical Hydrology and Water Re-sources, John Wiley, New York. Pp125-223.

Becky Oskin 2015, What is Groundwater?, Contributing Writer | January 8, 2015 08:37pm ET

Bennet, R. B. & Olatunde, P. O. (1984). General Geography in Diagrams for West Africa. Longman Britiain. Pp 379.

Besler, H. (1981). Slope Properties, Slope Processes and Soil Risk in Tropical Rain Forest of Kalimantan Timur (Indonesia Borneo). Earth Surface Processes and Land-forms 13, Pp 195-204

Chukwu, K.E. (2004). Infiltration Process and Overland Flow in A Small Humid Tropical Watershed Affected By Ur-banization; An Investigation From Southern Nigeria. ESUT Journal of Environmental Management, Vol-


mailto:[email protected]/[email protected]/

83

ume 2 No.1 August. Pp75-91. Chukwudelunzu, V. U. (2002). Implications of Rainfall Char-

acteristics on Agriculture in Enugu State of Southeastern Nigeria Unpublished M.Tech.,Project; Federal University of Technology, Minna Niger State.

Daniel N. Obiora, Adeolu E. Ajala and Johnson C. Ibuot,2015, Investigation of groundwater flow potential in Makurdi, North Central Nigeria, using surficial electrical, resistivity method, African Journal of Environmental Sci-ence and Technology : Vol. 9(9), pp. 723-733, September, 2015/ DOI: 0.5897/AJEST2015.1983/Article Number: 3E62B3F48280/ ISSN 1996-0786/Copyright © 2015

Ebisumeju F. S. (1979). Analysis of Drainage Density and Similar Parameters in Relation to Soil and Vegetation Characteristics in Nigeria. Geographical Journal 22 (1) Pp 33-44.

Ebisemiju, F. S. (1989a). Patterns of Stream Channel Re-sponse to Urbanization in the Humid Tropics and Their Implications for Urban Land Use Planning; A Case Study From Southern Nigeria. Applied Geography. Volume.9, No.4 Pp.275-286

Erdas, (2003). Erdas Field Guide, Leica Geosystems. GIS and Mapping, Atlanta, USA.

Evans, R.(1980a). Characteristics of Water Eroded Fields in Lowland England, in M.De Boodt and D. Gabriels (Eds.). Assessment of Erosion. John Wiley, N.Y.

Evans, R. (1980b). Mechanisms of Water Erosion in Kirkby M. J. and Morgan R. P. C. (Eds.) John Wiley, London.

FAO, (Food and Agricultural Organisation) (1992). The Con-servation and Rehabilitation of African Lands. Improving Land use Rome 1992 .Pp 23.

FAO, (Food and Agricultural Organisation) (2000). Water harvesting for improved agricultural production. Water report 3. Rome. FAO, 2003. State of the world's forests, Rome, Italy.

J. O. Oseji, M. B. Asokhia, E. C. Okolie 2006, Determination of groundwater potential in Obiaruku and environs using surface geoelectric sounding, Environmentalist, 26: 301-

308 (2006). Narendra K, Rao KN, Latha PS (2013) Integrating Remote

Sensing and GIS for Identification of Groundwater Pro-spective Zones in the Narava Basin, Visakhapatnam Re-gion, Andhra Pradesh, Journal Geological Society of India 81:248-260.

Nfor, B N; Olobaniyi, S B; Ogala, J E, 2007: Extent and Dis-tribution of Groundwater Resources in Parts of Anambra State, Southeastern, Nigeria, J. Appl. Sci. Environ. Man-age. June, 2007 Vol. 11 (2) 215 – 221

Obiajulu, O.O; Okpoko, E.I.,2015, Geoelectric Investigation

of Groundwater Potential of Ihiala and Its Environ, Anam-bra State, Nigeria, IOSR Journal of Applied Geology and Geophysics (IOSR-JAGG) e-ISSN: 2321–0990, p-ISSN: 2321–0982.Volume 3, Issue 6 Ver. III (Nov. - Dec. 2015), PP 14-20 www.iosrjournals.org.

Philips 2015, Live Science site, http://www.livescience.com/39579-groundwater.html

Saraf A, Choudhary PR (1998). Integrated remote sensing and GIS for ground water exploration and identification of artificial recharge site. International Journal of Remote Sensing 19: 1825-1841.

Srinivasan RY, Jugran KD (2003) Delineation of groundwa-ter potential zones and zones of groundwater quality suita-ble for domestic purposes using remote sensing and GIS. Hydrogeology Science Journal 48:821-833.

Saraf A, Choudhary PR,1998), (Krishnamurthy JN, Venkate-sa K, Jayaraman V, Manivel M,1996) and (Srinivasan RY, Jugran KD, 2003). These thematic maps were then inte-grated using “Raster Calculation” tool of GIS to delineate groundwater potential zones.

UNESCO, 2004, Groundwater resources of the World and their use. In: Zekster IS, Everett LG (eds), IHP-VI Series on Groundwater, 6 (2004).

http://www.iosrjournals.org

http://www.livescience.com/39579-groundwater.html

http://www.livescience.com/39579-groundwater.html

Documents

Okwu Delunzu, et. al. REJOEN 1,2018, 63 83 Assessment of