Improving discharge prediction for poorly gauged hydropower potential sites : a case study of Mabula Kapi site.
| dc.contributor.author | Mukuka, Reynolds | |
| dc.date.accessioned | 2023-07-06T09:28:24Z | |
| dc.date.available | 2023-07-06T09:28:24Z | |
| dc.date.issued | 2023 | |
| dc.description | Thesis | en |
| dc.description.abstract | Kafue Gorge Regional Training Centre (KGRTC) intends to carry out full feasibility studies for the development of Mabula Kapi hydropower site located on Kaombe River in Serenje District. KGRTC installed a hydrological gauging station at the site in September 2019. However, the small hydropower potential site is considered to be poorly gauged since it lacks adequate streamflow and/or rainfall data required for hydropower planning and design. Mabula Kapi was initially investigated to prefeasibility study level, using hydrological data from an adjacent catchment on Lusiwasi River, which was considered to be hydrologically similar. The catchment area-ratio method which was applied is a simple approximation because catchment characteristics between donor and target catchments rarely match perfectly. For Mabula Kapi site, the presence of a natural lake on the Lusiwasi donor catchment raised uncertainties about similarities in the drainage network and therefore the accuracy of transposing hydrological data. Additionally, anticipated future climate changes raised uncertainties about the sustainability of the proposed hydropower plant. In this study, several discharge prediction methods were reviewed and rainfall-runoff computer modelling was selected as the most suitable method for predicting discharge for Mabula Kapi Catchment. The method was applied to accurately predict discharge time series by creating a conceptual representation of relevant hydrological processes for Mabula Kapi Catchment in a computer-based open-source model known as PITMAN. The PITMAN model was largely selected due to limitations in local input data availability and project budget. Satellite rainfall point data known as the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) was adopted as one of the modeling inputs because of its good correlation with ground measured data. A 30-year discharge time series was simulated for Mabula Kapi site using the PITMAN model. The model was calibrated by matching simulated discharge and observed discharge time series from the newly installed gauging station at Mabula Kapi site. The derived time series were used to estimate the installed capacity (8.2 MW), annual energy yield (38 GWh) and design flood (120m3 /s). Runoff simulations done in the model using future rainfall and temperature projections indicated that the average annual energy for the power plant is likely to reduce by 11% from 2040 to 2059. It is recommended that the estimated energy reduction be taken into account when conducting financial analysis for the project and that further climate tests be done using other credible climatic projections which may be available. Key words: CHIRPS, Hydropower, Modelling, Rainfall, Streamflow | en |
| dc.identifier.uri | http://dspace.unza.zm/handle/123456789/8050 | |
| dc.language.iso | en | en |
| dc.publisher | The University of Zambia | en |
| dc.subject | Hydropower. | en |
| dc.subject | Hydropower--Streamflow. | en |
| dc.title | Improving discharge prediction for poorly gauged hydropower potential sites : a case study of Mabula Kapi site. | en |
| dc.type | Thesis | en |