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Impacts of Climate Variability on Power Generation on within the 7-Forks Dams in the Tana River Basin

Volume 5:2

Christopher Oludhe

University of Nairobi; Email: This email address is being protected from spambots. You need JavaScript enabled to view it.

Abstract

The 7-Forks Dams are located in the upper Tana River Basin and form extremely important components of the Tana River System. The Masinga Dam serves as a storage reservoir, controlling hydrology through a series of downstream hydro-electric reservoirs. The opera on of Masinga Dam is therefore crucial in mee ng the power demands for the country, thus contribu ng signifi cantly to the country’s economy. The prolonged droughts of 1999-2001 and 2009-2010 in the Tana River basin due to La Nina related condi ons resulted in power shortages and prolonged power ra oning in Kenya. The overall objec ve of this study is to assess the impacts of climate variability on the hydropower sector in Kenya and to demonstrate the poten al use of climate informa on and predic on products in the decision making process in reservoir opera ons in the 7 Forks Dams of Tana River Basin in Kenya. This paper examines the impacts of climate variability on the power genera on at the 7-Forks dams and provides a forecas ng model for the management of water in the Masinga Dam for power genera on. The data used for this study were monthly rainfall observa ons over the upper Tana River catchment over the period 1947 – 2010. The data were obtained from Kenya Meteorological Department (KMD) while monthly Tana River streamflow discharge, Masinga Dam levels, 7-Forks power genera on and spill over the period July 1981 – July 2010 were obtained from the Kenya Electricity Generating Company (KenGen). The study u lized the reservoir inflow forecasts downscaled from monthly updated precipitation forecasts from ECHAM4.5 forced with persisted SSTs to generate the probabilistic streamflow forecasts for the April-June (AMJ) and October-December (OND) seasons for the Masinga reservoir in Kenya. Principal component regression (PCR) was employed to obtain the mean monthly streamflow forecasts during the AMJ and OND seasons. The results from retrospective reservoir analysis showed that the operations of the reservoir utilizing the forecasted inflows can significantly reduce the overall spill by increasing water allocation for hydropower during above-normal inflow years and reducing the spill during the below-normal inflow years.

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