Water availability in Southern Africa is highly variable both in time and space, thereby exposing the region to high risks in water availability. This is further compounded by numerous human activities which have significant impact on water resources. The brunt of the risks associated with water scarcity is particularly heaviest on resourceconstrained farmers who depend largely on rain-fed agriculture for subsistence. With continuously increasing demands on the water resources, the need for a better understanding of the hydrological systems becomes crucial as it forms the gateway for providing reliable information for managing water resources. It is also increasingly becoming more important to address land and water linkages because land use decisions are water use decisions. Operational hydrology provides an insight into the effects of man-made changes, the foreseeable hydrological characteristics at a given site, and the long-term prediction of the future hydrological effects of human activities. This provides for a more holistic approach in managing land and water resources as well as the impact of land use on partitioning rainfall into streamflow. This report discusses the application of the SWAT model to the B72E - F quaternary catchments in the Olifants Water Management Area to assess streamflow generation and the effects of human-environment interactions on the hydrology. Results show an expected correlation between land cover and the hydrologic response where an increase in land cover corresponds to a reduction in the streamflow. Range grass shows a higher reduction in the streamflow followed by forestry with arid land giving the highest increase in streamflow. Prediction in the similar neighbouring and ungauged B72A catchment gives a MAR of 68mm. Additionally, a rigorous analysis of the concepts of a local hydrological model, HDAM, is done with respect to rainfall which is the main driver of the model. Modifications of some of the relationships used in the model are suggested with the potential of streamlining the model and making it more applicable in the region.