Lineaments Characterization of Gound-Water Potential of the Ningi-Burra Complex, North Eastern Nigeria Using Remote Sensing Techniques
- Abba, M.J
- Danbatta, U. A
- Haruna, S.T
- Abubakar, T
- 12-23
- Nov 26, 2024
- Geology
Lineaments Characterization of Ground-Water Potential of the Ningi-Burra Complex, North Eastern Nigeria Using Remote Sensing Techniques
Abba, M.J1, Danbatta, U. A2, Haruna, S.T3, Abubakar, T4
1,3Center for Geodesy and Geodynamics, Toro, Bauchi State.
2Geology Department, Faculty of Physical sciences, Ahmadu Bello University, Zaria.
4Geology Department, Faculty of Earth and Environmental Science, Aliko Dangote University. Kano.
DOI: https://doi.org/10.51584/IJRIAS.2024.911002
Received: 11 October 2024; Revised: 22 October 2024; Accepted: 25 October 2024; Published: 26 November 2024
ABSTRACT
A Landsat Enhanced Thematic Mapper plus (ETM+) data was georeferenced using the coordinates of the Nigeria Topographic Map Sheets of Part of Birnin-Kudu sheet 105 SE, Gwaram sheet 106 SW, Kalatu sheet 127 NE and Kaffin Madaki sheet 128 NW, lies between Latitudes 10o 55’ N to 11o 10’ N and Longitudes 9o20’ E to 9o 35’ E, ERDAS imagine software (Version 8.6) was used for image processing, enhancement and filtering as well as interpretation and digitization using ILWIS 3.3, the lineaments of the Ningi-Burra was extracted from the satellite, digital elevation and surface lineaments to express the ground water potential zones in the area, the extracted lineament structures were interpreted as fractures, joints and drainage lines for the accessibility of the ground water potential of the area. The satellite lineaments are oriented in a NE – SW direction with major N-S and minor NW – SE. The lineaments from digital elevation model (DEM) were divided into several groups; N-S, E-W, NE-SW, NW-SE, NNE-SSW, ENE-WSW, WNW-ESE, and NNW-SSE. The statistical results have the sum of 898,584.40 km with minimum value of 0.00 and a maximum value of 39,101.40 km. The intensity of groundwater potential decreases with increasing distance from the lineaments. Satellite lineament bar chart has the highest lineament frequency of 5 within the class interval of 9 km and the lowest lineament frequency of 0 occurring within the class interval of 12, 13, 1617, 19 km which represents the drainage lineaments of the stream channels The satellite lineament density map has highest value of 10 – 19 and lowest values of 1.0 and 3.0 densities.
Keywords: Ground water potential zone, Satellite imagery, Digital elevation model and surface lineaments
INTRODUCTION
Background
Remote sensing can be used as a reconnaissance and feature identification technique for identifying surface and subsurface water potential zones. The study and analysis of the lineaments features of the Ningi-Burra complex using remote sensing methods for integrating maps and data is to have a Spatial distribution and lineament density that will provide a useful database in hydrogeology, ground-water potential, water borehole drilling, road and dam location and alignments, environmental planning as well as potential Hazard Monitoring and Control (Odeyemi et al., 1999)
Groundwater is a critical resource for human activities and ecosystems, particularly in regions where surface water resources are limited or unreliable. Mapping groundwater potential zones is essential for identifying areas with high potential for sustainable groundwater development and management (Kumar, 2024)
The study employs the use of remote sensing techniques that will reveal the geological lineaments structures which will help to establish the ground water potential zones in the area (Dunning et al., 1998; Jefferies et al., 2000; Ashano and Olasehinde, 2010).
Location of the Area
The area is located within Birnin-Kudu Sheet 105 SE, Gwaram Sheet 106 SW, Kalatu Sheet 127 NE and Kaffin Madaki 128 NW, is bounded between Latitudes 10o 55’ N to 11o 10’ N and Longitudes 9o20’ E to 9o 35’ E (Figure 1). The area is in Ningi local Government, Bauchi State, Nigeria. Topographically, the Ningi-Burra Complex forms a range of hills with NE-SW trend over a distance of about 70 km and a width of about 20 km. The range of hills rise about 100 – 300 m above the surrounding basement plains. Volcanic rocks occupy areas of high topography.
The drainage pattern is mainly dendritic. The main river and its tributaries take their source from surrounding hills. The area is drained by Rivers Tsangaya, Dagwalo, Tabula and Tebbi to the south and Rivers Dengir, Jigawa and Lumbu to the north, which empties their water to river Dilimi and subsequently to Lake Chad (Fig. 1). The streams and rivers in the area are seasonal with the water having their highest flow in the rainy season around August and lowest flow during the dry season around March.
The climate of the area is marked by three distinct seasons: –
i Late November – February: Harmattan (NE trade wind from the Sahara that blows toward the south western coast of Africa).
ii. March – May: Dry season, usually very hot with few isolated rain falls. The wind blows from northeast to southwest and temperature may rise more than 350 C.
iii. May – September: Wet or rainy season, wind blows to the south-westerly direction with occasional sunshine and temperature reaches more than 350 C. September-Late November is characterized by wind from south-west to north east.
Rainfall is usually very heavy in August and finally fading in early November. The mean annual rainfall is about 100 cm. while the mean relative humidity at 0600 hours and 1200 hours is 50 percent and 58 percent respectively (Schroeder, 1974).
The vegetation in the area corresponds to the Sudan-Savannah type, which is characterized by a sparsely distributed shrubs and grasses. The grasses can be as tall as 1m above ground surface during the raining season. Common trees include; Acacia albida, Adansonia digitata, Meliaindica, Delamixregia, Pamae Adenium obtusum due to their ability to survive dry season.
Figure 1: Simplified geological map of the Nigerian Younger Granite (NYG) complexes (after Kinnaird, 1985) rectangle showing the location of the Ningi-Burra Complex.
Aim and Objectives
The aim of the study is to interpret the satellite lineaments structures for Ground water potential of the Ningi-Burra complex.
The objectives are to:
i) Produce lineament maps of the area.
ii) Compile and interpret the satellite imageries of the area and interpret the structural features for Ground Water potential
METHODOLOGY
The satellite data used in this research is acquired from LANDSAT-TM which covered an area located between latitudes 10°55’N-11°10’N and longitudes 8°55′-9°55’E. Bands 7 is selected according to Marghany et al., (2009) which can provide accurate geological information, the Digital Elevation Model (DEM) data with a resolution of 30m covering the area was obtained from the United State Geological Survey Website (USGS). The ASTER-DEM was imported into ArcMap software where the extended elevation range was classified using the classification algorithm of spatial analysis tool of ArcMap. A hill shade value of 2 was assigned in order to reveal the third dimension of hills. The final image was embellished and exported. The data was georeferenced using the coordinates of the Nigeria Topographic Map within the Sheets of Birnin-kudu 105, Gwaram 106, Kalatu 127 and Kaffin-Madaki 128. The georeferenced projection in Universal Transverse Mercator (UTM), Minna Datum.
ERDAS imaging software (Version 8.6) was used for image processing, image enhancement and filtering as well as interpretation and digitization were carried out using ILWIS 3.3.
For this study, the Landsat 7 ETM+ image data was used, the application of the Landsat spectral bands is presented in Table 1. Band 7 of this image data according to this table is useful for the discrimination of minerals, rocks, lineament and structural types (Lilles and Kieffer, 1994). Satellite images acquired in this band have high information content that means there is large variation in the spectral response of materials in the environment. Band 7 is the least affected by atmospheric attenuation compared with the reflected infrared bands. Landsat 7 also carries a panchromatic band (visible through near infrared), with 15 meters’ resolution for “sharpening” of multispectral images.
This procedure of lineament extraction has been used to extract lineaments pattern from LANDSAT TM satellite images. Following (Maged and Mazlan, 2008) image enhancement contrast, as demonstrated in figure 2, stretching and linear enhancement are applied to acquire an excellent visualization.
Figure 2: Flow chart of lineament mapping from LANDSAT-TM satellite data
RESULTS AND INTERPRETATION
Lineament Source | Lineament Length Characteristics (km) | |||||
Sum | Minimum | Maximum | Average | Standard Deviation | Skewness | |
Satellite | 8,98,584.40 | 0 | ####### | 4,992.10 | 6,854.70 | 1.89 |
Surface | 9,44,834.20 | 0 | ####### | 5,249.10 | 3,530.20 | 0.8 |
DEM | 6,84,512.00 | 0 | ####### | 3,802.80 | 3,069.00 | 1.19 |
The most common method of graphical data presentation is the histogram or Bar chat, which is a plot of the proportional frequency of observed values lying within given numerical values. The ordinate of the plot is obtained by dividing the number of values within the particular interval by the total number of values. For the purpose of this work, the frequency of the lineaments was plotted against the lineament length class (km).
The satellite lineament Bar chat in figure 12, is positively skewed with the highest lineament frequency of 5 occurring within class interval of 9km and the lowest lineament frequency of 0 occurring within the class interval of 12 – 13, 16-17, 19 kilometers.
Figure 12: Satellite Lineament Bar chart
The surface lineament Bar chat (Fig. 13), has the highest lineament frequency of 9 within the class interval of 5 and 7 kilometers and the lowest lineament frequency of 0 within the class of 15, 17-18, 21-23 and 25 kilometers.
Figure 13: Surface Lineament Bar chart
The lineament density Bar chat (Fig. 14), extracted from Digital Elevation Model (DEM) produces highest lineament frequency value within the class of 3 km and 10 km with minimum frequency value of 1 within 4,9,16 and 17 kilometers.
Figure 14: DEM Lineament Bar chart
Lineaments Trend
Preamble
These lineament directions correlate well with joint directions mapped on the surface; the lineaments correspond with alignment of stream segments which signifies a form of structural control of the drainage system. The lineaments trends presented in rose diagrams reveals several trends in NE-SW, NW-SE, N-S and E-W directions; with the dominant structural trends in NE-SW and NW-SE directions.
Lineaments Orientation Trends on Rose Diagrams
Directional data extracted during analysis of the fractures as summarized on Table 3 and presented in a rose diagram in figures 15, 16 and 17, the trend and / or strike data are organized into bin sizes (class intervals) of 100, where each bin represents the number of values that fall within the specific angular region. A family of concentric circles provides scaled control for the number of fracture orientation values that occupy each bin size
Table 3: Lineament Orientation Trend
Data Type | Number of Trends | Orientation Description | ||||
10 | 20 | 30 | 40 | 50 | ||
Satellite | 6 | N3200 W | N550 E | N3400 W | (1) N650E (2) N3550 W | N3150 W |
Surface | 6 | N600E | N3350W | (1) N450E (2) N3150 W | N250E | N2900 W |
DEM | 6 | N3550W | N550E | (1) N900E (2) N3250 W | N350E | N3100 W |
Satellite lineament density rose diagram represented in figure 15, produces six (6) numbers of trends which is one primary (10) trend of N3200 W with one secondary (20) trends of N550 E with one tertiary (30) trends of N3500 W and two quaternary (40) N650 E, N3350 W and one pentagonal (50) trends of N3150 W.
Figure 15: Satellite Lineament Rose Diagram
Surface lineament density rose diagram represented in figure 16, produces six (6) numbers of trends, one primary (10) trend of N600E with one secondary (20) trends of N3350 E, with two tertiary (30) trends of N45E and N3150W with one quaternary (40) trends of N250 E and one pentagonal (50) trends of N2900 W.
Figure 16: Surface Lineament Rose Diagram
DEM lineament density rose diagram represented in figure 17, produces six (6) numbers of trends which are one primary (10) trend of N355W with one secondary (20) trend of N550E, two tertiary (30) trend of E90W and N3250W with one Quaternary (40) trends of N350E one pentagonal (50) trends of N3100W.
Figure. 17: DEM Lineament Rose Diagram
CONCLUSION
Based on the results obtained it is very possible that Ground water is more than the surface water found in the area, as the area is very porous due to high lineaments density. The use of remote sensing data has helped in obtaining detailed surface situation which is a representation of the subsurface situation in the study area.
Based on the results obtained, lineament characterization will enable a better understanding of the role of structural features, such as joints and faults, in groundwater infiltration and accumulation.
Remote sensing techniques can be used for mapping groundwater potential zones which has important applications in various sectors, such as agriculture, industry, and urban water supply.
The map of the lineament density produced from Landsat imagery and DEM tend to show the area of high lineament density, which could be the target area for exploration.
The result obtained is of advantage in modern exploration geosciences in that they offer quick glance at the spatial distribution of the density of lineament and hence provide database in hydro geology, mineral exploration, hazard assement and engineering construction.
RECOMMENDATIONS
i) Based on the results obtained, remote sensing should be used for geological mapping as a data acquisition method complementary to field observation. About one-fourth of the Earth’s total surface area is exposed land where information is ready to be extracted from detailed earth observation via remote sensing to be used in the study of modeling of subsurface flow and natural recharge, pollution control and hydro geologic process monitoring.
ii) Geological mapping methods have been undergoing continuous change along with technological and scientific advances in other relevant fields. Remote sensing techniques are now being increasingly used to prepare geological maps and obtain the basic geological information on which further detailed work is based.
iii) Based on the results obtained from this research work, it is recommended that more detailed geophysical investigation should be carried out to study the sub-surface ground water potential
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