Understanding the impacts of climate change requires the development of hydrological modelling tools. However, data scarcity hinders model application, performance, process simulation and uncertainty, especially for Sub-Saharan Africa. In this study, a multi-catchment approach was used to assess hydrological process variability in the Western Cape (WC) of South Africa using the JAMS/J2000 rainfall–runoff model and a Monte Carlo analysis (MCA). Due to much steeper slopes and lower evapotranspiration, the models suggest that WC is dominated by surface runoff from mountainous regions and regional groundwater flow. The results highlight the impact of the catchment size, availability and position of hydroclimatic and anthropogenic factors and the frequency of the signal-to-noise ratio (water balance). For large catchments (>5000 km2), the calibration was able to achieve a Nash–Sutcliffe efficiency (NSE) of 0.61 to 0.88. For small catchments (<2000 km2), NSE was between 0.23 to 0.39. The large catchments had an overall surface runoff, interflow and baseflow contribution of 44, 19 and 37%, respectively, and lower overall uncertainty. The simulated flow components for the small catchments were variable and these results are less certain. The use of a multi-catchment approach allows for identifying the specific factors impacting parameter sensitivities and in turn provides a means to improve hydrological process simulation.