J. Nig. Soc. Phys. Sci. 3 (2021) 59–65 Journal of the Nigerian Society of Physical Sciences Application of Remote Sensing and Geoinformatics Techniques in Erosion Mapping and Groundwater Management in the River Amba Watershed, Central Nigeria Nuhu Degree Umara,∗, Aliyu Itari Abdullahib aDepartment of Geology, Federal University of Lafia, Nasarawa state, Nigeria bDepartment of Geology, University of Nigeria, Nsukka, Enugu state, Nigeria Abstract This research integrated an easy-to-handle remote sensing data and geoinformatics techniques for erosion mapping and groundwater management in the River Amba watershed, central Nigeria. It is aimed at: (a) the determination of the erosion prone areas, and (b) the estimation of the groundwater potential contamination risk under current and future anthropogenic activities. Rainfall intensity was evaluated from monthly rainfall data (2001 - 2011) from station located within the River Amba Watershed. Digital Elevation Model (DEM) for the terrain was created using 3D Analyst tool (Surfer 14) and was used to determine the flow direction and lineament features in each raster cells. Remote sensing data (aerial photographs and LANDSAT imagery) were used to develop land use map, while geological mapping was used to determine the local geology of the watershed area. The contributions of the various factors to the erosion hazardous areas are: elevation 31.49 %, land use 21 %, slope 14 %, geology 12.52 %, rainfall intensity 10.5 % and flow accumulation 10.5 %. The combined influences of these factors to erosion susceptibility as either: very high, high, moderate, low and very low withthe south-western part characterized as high while other parts of the study area moderate to very low erosion vulnerability. The groundwater level is shallow (4.0 –28.5 m) and discharges through the Amba river and many springs. These springs along with boreholes and wells supply drinking water to Lafia and environs. DOI:10.46481/jnsps.2021.63 Keywords: Erosion, River Amba, Watershed, Landsat imagery, GIS Article History : Received: 17 March 2020 Received in revised form: 18 March 2021 Accepted for publication: 03 April 2021 Published: 29 May 2021 c©2021 Journal of the Nigerian Society of Physical Sciences. All rights reserved. Communicated by: O. J. Abimbola 1. Introduction Erosion is the removal and transport of soil, rock debris, or weathered materials by the action of water, wind, air and human activities from one location to another on the Earth’s crust. This process is selective in a way as it removes mainly fine particles that contain relatively high proportion of organic matter. This ∗Corresponding author tel. no: +2347069247822 Email address: aliyu.itari@gmail.com (Aliyu Itari Abdullahi ) portion of the soil that is always removed is very rich in fertility and therefore supports plants growth. Soil erosion therefore, re- mains the main mechanism of soil degradation which threatens the global sustainability of the food production systems [1]. In the Amba watershed, soil erosion has often been exac- erbated by crude agricultural practices, and particularly non- implementation of appropriate soil conservation measures such as crop rotation, run-off control and contour farming. Studies showed that soil degradation leads to the loss of basic soil prop- erties relevant to the farming system and/or an increase of the 59 Nuhu & Aliyu / J. Nig. Soc. Phys. Sci. 3 (2021) 59–65 60 production costs [2]. Significant increase in erosion has been recorded all around the world in the last three decades especially in the tropics. These events which are quickly transformed into runoff, due to the high capacity of transport, can be characterized as the most significant weather-related hazards in many parts of the tropics all around the world, causing considerable economic and hu- man losses [3]. The main causes of erosion are climate change, changes in land use and other anthropogenic interventions. The most common anthropogenic interventions are urban growth, the partial or total cover of torrent banks, watercourse align- ment, improperly dimensioned bridges, deforestation and the consequent erosion, the construction of roads or other structures across the watercourse, subsidence observed in flat regions due to anthropogenic interventions such as over-pumping, and fi- nally, the change or deviation of the watercourse [4]. Due to rapid urbanization and economic growth in Lafia in the past two decades, large percentage of cultivated land and forest land have been built up. Areas where deforestation, farm- ing or urbanization leads to the formation of direct runoff will be more prone to erosion than areas where land use changes such as afforestation minimizes direct runoff [5]. One of the major contributing factors of erosion is rainfall: the degree of impact is dependent on its intensity, distribution, duration, fre- quency and kinetic energy. Erosion induced by rainfall causes many problems such as decreased in agricultural productivity due to the loss of arable land, increased landslide activity and ecosystem disturbance [6]. The lack of detailed climatic and hydrogeological data which are expensive and time consuming is a hindrance to the use of detail modelling approach. Thus, in erosion studies, precipita- tion records and flow data have been widely used [7]. Thus, the effective use of Geographic Information Systems (GIS) man- agement tool is essential to delineate the flood prone areas [8]. Furthermore, the synthesis of available data and the mapping of the relationships between groundwater hazard and the ele- ments at risk require the use of tools such as GIS. Integrating GIS and remote sensing techniques can provide the base for analyzing quantitatively environmental process with an appro- priate degree of accuracy. Whereas research has been conducted into the geology [9, 10], mineral resources [11], hydrogeology [9, 12] and aquifers characteristics and groundwater quality [10], little or no atten- tion has been channeled towards assessing the vulnerability of Lafia Formation to erosion. The aim of this work is to use an in- tegrated and easy to handle GIS tool that incorporates geoinfor- matics techniques for erosion and groundwater management in tropics. The proposed water management tool has two compo- nents: (a) the determination of the erosion hazardous areas, and (b) the estimation of groundwater flow and the potential con- tamination risk under current and future anthropogenic pres- sures and activities. 2. Location and accessibility of the study area River Amba catchment is located in the southwest of Nasarawa State, central Nigeria. It lies between latitude 8◦ 24 ′ and 8◦ 36 ′ and longitude 8◦ 26 ′ and 8◦36 ′ (Fig. 1) and drains a surface area of about 800 km2 (Fig. 2) with the monitoring station is located at the outlet (coordinates: 8◦ 29 ′ 36.4” N and 8◦ 30 ′ 31.4” E). River Amba is the major river that drained the area and is char- acterized by the Guinean savannah vegetation. The original vegetation has been tampered with due to human activities such as farming, bush burning and grazing, which has given rise to a secondary forest [13, 10]. The area is characterized by two ma- jor distinct seasons (wet and dry), the former lasts from March to October, while the later lasts from November to February. The annual average rainfall ranges between 1000 and 1500 mm while the mean annual humidity is 70 % with relative humidity of 60 to 80 % [14]. Temperatures range from 33 – 36 ◦C with an annual average temperature of 28.5 ◦C. An annual average sunshine hour of 6.7 per day is also experienced. The elevations of this area range from 110 to 243 m above sea level. The geological bedrock is sandstone, and it is overlaid by deep and highly loose soils (Ox- isols, Ultisols, and Alfisols), with the Oxisols being the domi- nant soil class in the catchment. These soils are enriched in iron oxides and laterite. The landscape is generally character- ized by gentle slopes (3–6 %), whereas steeper slopes (5–9 %) are found near the drainage channels. Accessibility is by the Trunk ‘A’ Lafia – Akwanga and fur- ther improved by minor routes and footpaths linking villages, farm lands and streams (Fig. 3). The major stream flows in northeast - southwest direction which corresponds to the strike direction of most structures generally found in the area indicat- ing structurally controlled stream. Figure 1. Topographic map of the study area. 2.1. Geology and Land Use Geologically, the study area is underlain by the Laa Forma- tion (Fig. 4) also called the ‘Laa Sandstone’ [15]. It lies within Central Benue Trough, Nigeria, and characterized by ferrug- inized sandstones, red loose sands, flaggy mudstones, clays and claystones. Hydrogeologically, the Lafia Formation comprises 60 Nuhu & Aliyu / J. Nig. Soc. Phys. Sci. 3 (2021) 59–65 61 Figure 2. River Amba watershed map. Figure 3. Accessibility map of the study area. mainly fine-to-coarse grain sandstones, which are highly porous and permeable [13] and is the most prolific in the Central Benue Trough. Land use including farming, forests, wetlands, and urban areas cover less than 15 % of the total catchment surface area. The riparian areas (< 10 m wide) found along the river catch- ment network are narrow. They are further affected by cattle trampling, which prevents them from providing effective traps to stop sediment emanating from upper parts of the catchment. The hydrogeology of the Lafia Formation and the Central Benue Trough has been studied by [9, 15] who made a brief survey of the water resources of the area in the light of its impor- tance to the development of the region. An evaluation of some hydrogeological characteristics of the aquifers of Lafia forma- tions [10], where he reported the aquifer to be about 150 m thick, highly prolific having dominantly moderate aquifer pro- tective capacity. Four types of aquifers were identified [9, 15]. These are; the Awe Formation, the Keana / Ezeaku Formation, the Awgu For- mation and the Lafia Formation (being the youngest). In Obi village, the Lafia sandstone is sub-artesian and quite near the surface which can be tapped for domestic and industrial pur- poses [16]. 3. Materials and Methods 3.1. Estimating the Erosion Hazardous Areas in the Amba Wa- tershed Based on factors that form and influence erosion; slope, land use, rainfall intensity, geology and flow accumulation the study area was divided into five regions characterized by differ- ent degrees of erosion susceptibility (very high, high, moder- ate, low and very low). Relative weights were assigned to each factor based on its influence in triggering erosion according to Kourgialas & Karatzas [4]. Thematic maps are produced for each parameter in a GIS environment. A combination of these thematic maps and the selection of the weights yield the final map of erosion prone areas. The original data include the topographic map (Fig. 1) and the monthly rainfall data (Table 1) from station located in the surrounding area. The Digital Elevation Model (DEM) for the terrain was created by Surfer 14. Remote sensing data (aerial photographs and Landsat Imagery) were used to determine the land use, while geological mapping was used to determine the geology of the watershed area. From the DEM, the flow direc- tion in each raster cell was determined. This was followed by the identification of the water accumulation points. The flow concentration map, which indicates the number of cells that hy- drologically contribute to each raster cell was developed by us- ing the flow direction map combined with a suitable algorithm (flow accumulation - Arc Hydro). Output cells with a high flow accumulation (pixels) are areas of concentrated flow [4]. The rainfall intensity was determined from the meteorolog- ical data (2001-2011) of area surrounding the Amba watershed (Table 1). The rainfall intensity map was created by using the Modified Fourier Index (MFI) methodology [17]: MF I = 12∑ 1 P2 P (1) where ∑12 1 is the 12-month summation, P 2 is the average monthly rainfall and P is the average annual rainfall. The MFI indicator expresses the sum of the average monthly rainfall intensity at a station. 3.2. Estimating the Groundwater Direction and Groundwater Contamination Risk in the Amba Watershed The static water levels (SWL) of over two hundred wells and boreholes were measured using dipper (the dipper-T model) while the topographic elevation and coordinates (latitude and longitude) of each was established using Geographical Posi- tioning System (e-Trek 20 Garmin model). Hydraulic head for 61 Nuhu & Aliyu / J. Nig. Soc. Phys. Sci. 3 (2021) 59–65 62 Figure 4. Geologic Map of the Amba Watershed [10]. each well was estimated from the SWL and topographic ele- vation above mean sea level measured for such well. These measurements were used to construct hydraulic head map. This map describes the groundwater flow direction in the study area. Groundwater contamination risk was estimated in the extended area by combining information of the equipotential contours map created in a GIS environment with lineament map of the area (Fig. 5). The primary data for the creation of the above maps include: a) land uses based on aerial photographs, b) hydrogeological layers maps, c) soil maps, and d) groundwater level data from wells in the study area. Figure 5. Lineaments Density Map of the Amba Watershed. 4. Results and Discussion 4.1. Erosion Prone Areas The six factors viz; flow accumulation (Fig. 6), slope (Fig. 7), elevation (Fig. 8), rainfall intensity (Table 1), geology (Fig. 4), and land use (Fig. 9), were used to estimate the erosion sus- ceptible areas and create the corresponding maps. These fac- tors were assigned numeric values, except geology and land use which were expressed in descriptive form [4]. In the case of the numeric-valued factors, five classes of susceptibility were iden- tified while in the case of the non-numeric-valued factors, clas- sification depends mainly on the influence of the factor on the generation of erosion process. For instance, for the geology fac- tor, a loamy soil indicates very low erosion vulnerability while in the case of the land use factor, limited land cover (low land cover) indicates a very high erosion susceptibility. It is almost impossible to estimate erosion susceptibility of an area by considering the influence of a single factor, there- fore the integration of all related factors is necessary in order to obtain the overall erosion vulnerability map as all factors have varying degrees of influence on the vulnerable areas. A weight- ing approach, where a different weight is assigned to each fac- tor, was applied while the factor weights were determined ac- cording to Kourgialas & Karatzas [4]. Based on this methodology, the effects of each factor on all other factors are depicted in Fig. 10. A solid line between two factors indicates that one factor has a main effect on the other pointed by the arrow, that is, a change of the first factor has a direct effect on the other (main avenue). A dashed line between two factors indicates that one factor has a secondary effect on the factor pointed by the arrow, that is, a change of the first factor has an indirect effect on the other (minor avenue). For example, flow accumulation has a main effect on land use and a secondary effect on slope. In order to quantify the two different 62 Nuhu & Aliyu / J. Nig. Soc. Phys. Sci. 3 (2021) 59–65 63 Table 1. Mean Monthly Rainfall Data (mm) from 2001 – 2011 (Source: NIMET, Lafia). YEAR 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 Mean STD DEV Jan 0 0 0 0 0 0 0 0 0 0 0 0.0 0 Feb 0 0 26 0 0 0 0 0 0 0 9.3 3.2 7.68 Mar 0.4 0 0 0 58 40 21 14 0 0 0 12 19.03 Apr 118 55 109 148 43 1.9 89 92 128 75 28 81 42.91 May 205 143 170 159 162 225 164 181 190 116 198 176 29.01 Jun 231 48 128 181 106 166 255 229 324 125 222 183 74.98 Jul 278 298 262 268 242 304 244 188 230 382 74 252 73.35 Aug 312 337 266 283 356 251 233 241 193 230 275 271 46.67 Sep 216 162 319 183 154 248 274 109 146 312 228 214 66.40 Oct 54 139 105 84 169 84 0 77 376 177 227 136 160.99 Nov 0 12 24 0 0 0 0 0 8.8 20 0 5.9 8.61 Dec 0 0 0 0 0 0 0 0 0 0 0 0.0 0 Total 1415 1192 1406 1305 1129 1319 1279 1136 1595 1438 1261 1316 529.63 Figure 6. Flow Direction and Accumulation map of the study area (Note: colour bands show demarcation of watersheds). types of effects, one (1) point is assigned to a main and half a point ( 12 ) to a secondary effects [17]. Then, the rate for a factor is computed as the summation of the points corresponding to the effects emanating from the factor. Based on the above weighting approach, the contribution of each factor to the erosion vulnerable areas, expressed as a percentage, is for the elevation: 31.49 %, land use: 21 %, slope: 14 %, geology: 12.52 %, rainfall intensity: 10.5 %, and flow accumulation: 10.5 %. The resulting map of the erosion vulnerability areas includes the combination of the above six variables that are related di- rectly to any erosion event that occurs in the watershed. Specif- ically, the six maps that were developed after the classification method were combined using a weighted linear combination approach in a GIS environment. Accordingly, each factor is multiplied by its percentage weight and the summation of all factors yields the final hazardous area map [18]. S = ∑ wi xi (2) Figure 7. Slope Classification map of the study area. Figure 8. Elevation map of the study area. 63 Nuhu & Aliyu / J. Nig. Soc. Phys. Sci. 3 (2021) 59–65 64 Figure 9. Land Use map of the study area. where, S is the final hazardous areas map, wi is the weight of factor I (percentage) and xi is the rate of the factor i. The fac- tors (maps) were combined according to Equation (2) and the final flood hazardous areas map was produced (Fig. 11). Ac- cording to this figure, the study area of Amba watershed can be classified with respect to erosion hazard from high to very low. Based on the results, the south-eastern parts of the watershed can be characterized as high flood prone areas. Figure 10. A Schematic Depiction of the Interaction between Factors that Influence the Flood hazard [4]. 4.2. Groundwater Risk under an Intensive Agriculture Due to recent agricultural activities in the study area, partic- ularly fertilizers and pesticides application and the hypothetical scenario of charging pollutants and whether these may create environmental problems in the extended area, the map of hy- draulic heads (equipotential lines) for the entire watershed area was created (Fig. 4) based on the groundwater level data from over two hundred wells. It describes the flow direction, perpen- dicular to the equipotential lines. The direction of groundwater flow is northwest, through this flow direction groundwater en- countered various soil types of varying porosities resulting in many springs particularly at contact points. From the study, it was observed that a) based on the ground- water level data the aquifer in the Amba watershed is shallow (4.0–28.5 m) [10],b)the study area receives significant amounts of rainfall, fact that lead to a rapid recharging of groundwa- ter resources, and c) the groundwater flow in the study area discharges through the Amba river and many springs. These springs supplies drinking water to Lafia settlements and envi- rons. Based on the above, the highly significant groundwater con- tamination risk in the study area from any excessive use of agro- chemicals through intensification of agricultural activity is ob- vious. Any deposition of contaminants such as nitrates in this area may have the final recipient of the Amba River and adjoin- ing springs. Figure 11. Erosion Vulnerability Zone Map of the Study Area. 5. Conclusion This study specifically evaluated the erosion prone areas and estimated the groundwater contamination risk in the Amba watershed by utilizing a combined remote sensing and geoin- formatics approach. Thus, the following conclusions based on the results of this study: 1. The erosion hazard phenomena in the study area is char- acterized as high in south-western part and moderate to very low in other parts of the study area. 2. The loamy soil of the Amba watershed is characterized by high clay content and shallowness. All these features contribute to a high groundwater contamination risk due to increased fertilizers and pesticides application. Re- garding the possible contamination in surrounding areas, 64 Nuhu & Aliyu / J. Nig. Soc. Phys. Sci. 3 (2021) 59–65 65 especially the spring, the groundwater hazard can be clas- sified as very high. The estimation of erosion and the groundwater hazardous areas are fundamental components of a water management strategy. 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