Demand of groundwater resources is drastically increasing with increasing population, hence, management, assessment and planning of the groundwater resources is very crucial. Remote Sensing (RS) and GIS plays a major role in delineation, management, planning, assessment and monitoring of groundwater resources and related studies, thus found to be time and cost effective tool to be used. The study area belongs to the Middelburg Basin, Mpumalanga Province. This research entails the mapping of groundwater potential zones in the Wilgerivier Formation using the Weighted Index Overlay Analysis (WIOA) with an aid of remote sensing and GIS. Different criterion maps such as lithology, geomorphology, lineament density, drainage density and slope have been generated through the existing satellite data and converted to raster format using ArcGIS 10.4 software. To assign weights and scores to the criterion maps and classes of each criterion maps respectively, WIOA technique has been used. The weights and scores assigned ranged from one to ten depending on the importance to groundwater occurrence, with one being the least important and ten being the most important. The criterion maps were integrated to produce the groundwater potential zones map which was categorized into five distinct zones; excellent, good, moderate, poor and very poor. The map generated is validated with existing yield data of various boreholes in the study area. The output map will help researchers, local authorities and planners in formulating proper planning, management and sustainability of groundwater resources for future generations.Delineation of groundwater potential zones on the eastern part of the Middelburg Basin, Mpumalanga using Weighted Index Overlay Analysis with the aid of Remote Sensing and GIS techniques is found to be time and cost effective. Satellite images and conventional data was used to prepare the criterion maps of lithology, lineament density, drainage density, geomorphology and slope. The criterion maps were assigned weights and scores to classes and then integrated to produce the output groundwater potential zones map. From the results of the groundwater potential zones map, Middelburg Basin has been classified into five different zones; “excellent”, “good”, “moderate” “poor” and “very poor. For validation of delineated groundwater potential zones, field groundwater data on existing boreholes or wells from the Department of Water and Sanitation was used. The results revealed a good correlation with respect to derived groundwater potential zones. High yielding boreholes are located in excellent and good groundwater potential zones whereas low yielding boreholes are typically found in poor to very poor groundwater potential zones. The map prepared can be used as a guideline for future planning of artificial recharge project location in the study area to ensure sustainable groundwater utilization.The Weighted Index Overlay Analysis (WIOA) is one of the multi criterion decision making tool used to assigned weights and scores to each criterion and classes of each criterion respectively to determine the groundwater potential zones. All the criterion maps were converted to raster, assigned a weight (Wc) on a scale of one to ten depending on its suitability to hold water. 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 (Table 5.1). 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.
Individual maps were reclassified and the reclassified map together with the weightage map were integrated using the raster calculator in the spatial analyst tool in ArcGIS software. The integrated map was then classified into; excellent, good, moderate, poor and very poor groundwater potential zones and lastly correlated and validated with the field groundwater data obtained from Department of Water and Sanitation. It was observed that the majority of the boreholes are sited on excellent to good groundwater potential zones where the geology is mainly sandstone and close to contact zones with diabase intrusions. The boreholes labelled one, two and three have an average yield of 1.39 – 1.67 l/s, 2.22 – 2.5 l/s and 2.8 -5.55 and an average depth of 70 m, 105 m and 108 m respectively. The rest of the boreholes are sited on poor to very poor groundwater potential zones with a diamictite rock mass which is indicative of poor aquifer. The boreholes labelled one and two have an average yield of 1.39 – 1.67 l/s and 1.11 – 1.39 l/s respectively. The aquifer is fractured.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 (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 “very low”, “low”, “moderate”, “high” and “very high” drainage density 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). The study area is situated in the Mpumalanga Province of Republic of South Africa. It falls within the Steve Tshwete Local Municipality of the Nkangala District. It is located on the eastern part of the Middelburg Basin which covers an approximate area of 1626 km2, lying between the longitudes 25,430 and 25,800 and latitudes 29,170 and 29,600 (Figure 3). Middelburg experiences warm summers and cold winters representative of the Highveld climate, i.e., rainfall commonly occurs as thunderstorms. It experiences an annual average rainfall of 740 mm (Figure 3.1.1) and varies from an average of 132 mm in summer to 9 mm during winter. Rainfall mostly occurs between November and February. It experiences severe frosts during winter; however, it experiences hail storms during summer. Water is lost in the system due to mean annual potential evaporation of 2 060 mm.The temperature of Middelburg is representative of the temperatures occurring on the Highveld with the lowest temperature being 3 0C in July and a maximum of 31 0C in January. The average annual winter temperature is 15 0C whereas the average summer temperature is 27 0C (Figure 3.1.2).The Proterozoic Wilgerivier Formation of the Waterberg Group forms the only stratigraphic unit in the Middelburg Basin. It unconformably overlie the Pretoria Group, Silverton Formation and Loskop Formation and is turn overlain unconformably by the sedimentary rocks of the Karoo Supergroup. The Wilgerivier Formation has a maximum thickness of 2000 m (Callaghan et al. 1991).
The Wilgerivier Formation comprises arenaceous clastic sedimentary rocks. The red-brown sandstone and quartzite rocks resemble an immature texture and mineralogy that dip towards the north at angles of 10º to 15º. It is intruded by a number of diabase sills and dykes of several metres (STLM, 2008)
Middelburg comprises undulating topography in the southern part at an approximate height of 1600 m above sea level. Numerous hills and steep inclines are found towards the northwestern part of the Middelburg at a height of 1400 m (Figure 3.1.3). The Olifants River system is the largest drainage system in Mpumalanga and is found in the southern part of the area where Middelburg resides (Figure 3.1.4), (STLM, 2008).The following datasets have been used in the study area;
• Digital Elevation Model (DEM) was acquired from Global Land Cover Facility (GLCF) for generation of topography, drainage and geomorphology maps.
• The geology map was acquired from existing geology map of South Africa in vector format.
• The lineaments were extracted automatically from PCI Geomatica software
• ArcGIS 10.4 Desktop software was used to prepare and process factor maps
• Weighted Index Overlay Analysis technique used to identify Groundwater Potential Zones
• Borehole data was acquired from the Department of Water and Sanitation.