The need to ensure groundwater security is vital, particularly in urban areas. Assessing the impact of land use and climate variables on groundwater quality can help improve sustainable management. The vulnerability mapping of groundwater contamination identifies high-risk areas. Using models and technologies that forecast the distribution of contamination risk over time and place can help prioritize groundwater monitoring. Based on such needs, the Cape Flats aquifer in Cape Town, South Africa, was chosen as the case study for assessing the potential for groundwater contamination risk in urban and coastal hydrogeological settings. The Cape Flats aquifer has been highlighted as an alternate water supply source to augment current supply sources in Cape Town. However, the shallow aquifer is under pressure from agricultural and industrial activities and long-term climate variables, among other factors. The study assessed and validated the vulnerability of the South African coastal aquifer to contamination using an integrated method that included geospatial spatial modeling, a WorldWater model, a down-scaled GCM to the local scale, and a DRASTIC model based on the Geographic Information System (GIS). In this thesis, three approaches are taken: evaluating the effects of changes in key climate variables such as temperature, precipitation, and sea-level rise on groundwater quality in Cape Flats aquifer systems; using the DRASTIC index and selected water quality parameters to assess the vulnerability of the Cape Flats aquifer to groundwater contamination; using a GIS-based model to assess the risk of groundwater contamination in the Cape Flats aquifer under changing climate and land use. Groundwater vulnerability maps were created using ArcGIS software. The WaterWorld model calculates hydrological scenarios for 1950–2000 (baseline) and 2041–2060 using global data at a resolution of 1 km (impact period). Precipitation will increase until 2041 and then fall until 2060, according to the simulation. Temperatures were expected to increase by 1.9-2.3 ° C. In the future, a dry climate, will increase evapotranspiration by 45 mm/year (10%) and decrease water balance by 6.8%. The A1B-AIM scenarios were used to simulate precipitation, temperature, and sea-level rise for two time periods, the 2040s and 2060s, using 20 GCMs integrated into the Greenhouse Gas-Induced Climatic Variables Model/Regional Climate Scenario Generator (MAGICC/SCHENGEN). The region's climate change projections say that there will be less precipitation in the summer and more in the winter, with temperature rises of 1.9 to 2.1 degrees Celsius. The probability that coastal areas are affected by an increase in sea level rise (17–19 cm) and increases in temperature by mid-2060 ranges from 12% to 58%. The DRASTIC model uses seven layers of hydrogeological data: depth to the water table, net recharge, aquifer media, soil media, topography, the impact of the vadose zone, and hydraulic conductivity of the aquifer. The vulnerability index ranges from 109 to 222, with 9% very high, 28% high risk, 46% moderate risk, and 17% low risk. The study area shows that increasing the DRASTIC model by LU increases the very high-risk zone by 26% while decreasing the low-risk zone by 52%. In addition to mapping groundwater vulnerability, the modified DRASTIC method can explain how urban hydrogeology affects coastal aquifers. The study uses an AHP to determine the weighting value for each hydrogeological parameter. GIS tools were used to create the GWQI map. The GIS-based model divides areas at risk of contamination into four categories: very high, high, moderate, and low. The study area has a moderate risk of groundwater contamination (42%). The southern and central suburbs of the study area are the most at risk. Based on data on the levels of water quality parameters in groundwater, the modified DRASTIC vulnerability map is consistent with land use data. In a correlation of these parameters, climate variability and land-based activities had significant effects on groundwater quality. A water quality index was calculated using selected parameters for general quantification and validation. Using chemical water quality parameters, this thesis created a groundwater quality index that ranged from 56 to 142. The contamination risk index and the measured groundwater quality values showed a significant and strong positive correlation (R2 = 0.96). The findings of the study are relevant to the management of water resources in the Cape Flats catchment and elsewhere in the world, particularly in Africa. DRASTIC uses GIS to assess groundwater contamination and provide data for better water resource management. As a result, computer models of contaminant transport can be used to test the DRASTIC parameters.