The following proposed methodology (Figure 4.1) was used to generate groundwater potential zones map. Different datasets comprising remote sensing data and conventional maps were used. All the acquired data have been geo-referenced into Universal Transverse Mercator (UTM), spheroid, and datum WGS-1984. Five different factor maps including; geomorphology, lithology, slope, lineament density and drainage density, were prepared and processed using ArcGIS 10.4 software. All the criterion maps were converted to raster, assigned a weight (Wc) on a scale of one to ten depending on its relative influence on the occurrence, origin and movement of groundwater. Different classes of each criterion map were also assigned a score (Scc) on a scale of one to ten according to their relative influence on the groundwater occurrence. With one being the least important and ten being the most important factor. The average score is given by; (Nag and Kundu, 2018)
?=(?Scc x Wc)/(?Wc)
Where ? is the average weight score of the polygon, Wc is the weight of each criterion map and Scc is the rating score of the class of the criterion map.
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All these factor maps have been integrated to produce groundwater potential map using the weighted index overlay method through the spatial analyst tool in ArcGIS. Four different zones have been identified, namely; “excellent”, “good”, “moderate” and “poor”, hence, the higher the average weight score, the most favourable the groundwater potential. The field groundwater data on existing wells or boreholes from Department of Water and Sanitation was then used to validate the presence of water in the study area
The lithology map is used to deduce possible groundwater aquifers and it was prepared by using existing geological map of South Africa. Image enhancement techniques were applied for characterization of rock type (Singh et al. 2013). The major groundwater storage units observed are sandstone, shale, diamictite and diabase where the sedimentary rocks are found to be good groundwater prospecting units due to their high permeability (Figure 4.2.1).Geomorphological map depicts how the land forms and its features that have direct influence on the groundwater occurrence (Singh et al. 2013). Based on interpretation of satellite images and contour lines extracted from a DEM of the study area, different geomorphological units have been delineated. The major geomorphic units observed are steep inclines, valleys and hills and (Figure 4.2.2). Hills and steep inclines are characterised by high drainage densities, thus make poor groundwater prospecting zones since runoff precedes infiltration and the valleys make good groundwater prospecting zones since they have low drainage densities and are characterised by gentle slopes where infiltration precedes runoff (Singh et al. 2013).
The rate of groundwater recharge is influenced by the drainage system characteristics. Drainage density is given by the ratio of the total length of the stream network in a given basin to the total basin area. Higher drainage density results in lower recharge rate since the rock is less permeable therefore, runoff precedes infiltration. However, lower drainage density favours groundwater recharge since infiltration precedes runoff due to high permeability of the rock (Singh et al. 2013). Hence, areas of low drainage density make good groundwater prospecting zones. The stream networks were extracted from the DEM of the study area using the hydrology tool under the spatial analyst tool in ArcGIS software and the drainage density was calculated using the line density also found under the spatial analyst tool. The drainage network of the study area are typical of the dendritic pattern. The stream networks were then grouped into three classes of “low”, “moderate” and “high” drainage density (Figure 4.2.3).Identification of linear features such as faults, folds and dykes is important especially in hard rock terrains since they store and transmit groundwater through the presence of secondary permeability (Srivastava and Bhattacharya, 2006). Lineament density is given by the ratio of the total length of the lineaments in a given basin to the total basin area. The lineaments were extracted automatically from the PCI Geomatica software and the lineament density was calculated using the line density under the spatial analyst tool in ArcGIS software. It was grouped into four classes of “very low”,”low”, “moderate” and “high” lineament density (Figure 4.2.4). High lineament density is indicative of good groundwater prospecting zones.Slope relates to the steepness and incline of the line and is calculated by finding the ratio of the vertical change to the horizontal change between any points in a line (Nag and Kundu, 2018). Slope plays a major role on runoff and infiltration. In areas where infiltration precedes runoff, the slope is said to be gentle and make good groundwater prospecting zones. Whereas, on steep slopes, runoff precedes infiltration, hence, makes poor groundwater prospecting zones. The DEM was generated from the Global Land Cover Facility (GLCF). It was converted to slope under spatial analyst tool in ArcGIS software (Figure 4.2.5).
