The Role of Multimodel Climate Forecasts in Improving Water and Energy Management over the Tana River Basin, Kenya

Abstract

The Masinga Reservoir located in the upper Tana River Basin, Kenya, is extremely important in supplying country’s hydropower and protecting downstream ecology. The Dam serves as the primary storage reservoir, controlling streamflow through a series of downstream hydro-electric reservoirs. The Masinga dam’s operation is crucial in meeting the power demands thus contributing significantly to the country’s economy. La Nina related prolonged droughts of 1999-2001 resulted in severe power shortages in Kenya. Therefore, seasonal streamflow forecasts contingent on climate information are essential to estimate pre-season water allocation. Here, we utilize reservoir inflow forecasts downscaled from monthly updated precipitation forecasts from ECHAM4.5 forced with constructed analogue SSTs and multimodel precipitation forecasts developed from ENSEMBLES project to improve water allocation during April-June (AMJ) and October-December (OND) seasons for the Masinga reservoir. Three-month ahead inflow forecasts developed from ECHAM4.5, multiple GCMs and climatological ensemble are ingested into a reservoir model to allocate water for power generation by ensuring climatological probability of meeting the end of the season target storage required to meet seasonal water demands. Retrospective reservoir analysis shows that inflow forecasts developed from single GCM and multiple GCMs perform better than climatology by reducing the spill and increasing the allocation for hydropower during above-normal inflow years. Similarly, during below-normal inflow years, both these forecasts could be effectively utilized to meet the end of the season target storage by restricting releases for power generation. The multimodel forecasts preserves the end of the season target storage better than the single model inflow forecasts by reducing uncertainty and the overconfidence of individual model forecasts.