According to estimates from previous energy studies, Zambia has a hydropower generation potential of more than 6,000 MW. Development of small hydropower plants which are widely considered to be renewable energy technology will help to foster sustainable development as well as increase access to electricity in the country. However, most of the small hydropower potential sites which are located in rural or remote areas are poorly gauged, lacking adequate streamflow and/or rainfall data required for hydropower planning and design. As a result, a number of sites are crudely planned, merely using hydrological data transposed from donor catchments, leaving uncertainties about project bankability. Mabula Kapi site located on Kaombe River, in Serenje District for example was initially investigated using hydrological data from an adjacent catchment on Lusiwasi River, which was considered to be hydrologicaly similar. However, the presence of a natural lake on Lusiwasi catchment raised uncertainties about the accuracy of the transposed hydrological data.In this study, satellite rainfall point data known as the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), which has adequate time series was adopted as one of the modeling inputs. Statistical analysis was done to compare the two data sets and the results indicated a good correlation. Hydrologic modeling, including calibration was done using South African open-source software known as the WRSM2000/PITMAN model and a 30-year discharge time series was simulated for Mabula Kapi site. The derived time series were used to estimate the installed capacity (8 MW) and annual energy yield (38 GWh) for the hydropower site. It is recommended that satellite rainfall point data such as CHIRPS be considered as alternative input data in hydrologic modelling of poorly gauged hydropower sites in Zambia. Such data can be useful in extending or deriving adequate discharge time series, required for design of water resources infrastructure projects.

Keywords : CHIRPS, Hydropower, Modelling, Rainfall, Streamflow.