Forecast-informed reservoir operations to guide hydropower and agriculture allocations in the Blue Nile basin, Ethiopia
Sarah Alexander, Guang Yang, Girmachew Addisu, Paul Block
Abstract
Predictive hydroclimate information, coupled with reservoir system models, offers the potential to mitigate climate variability risks. Prior methodologies rely on sub-seasonal, dynamic/synthetic forecasts at short timescales, which challenge application in practice. Here, coupling a local-scale seasonal, statistical streamflow forecast with a reservoir model addresses this gap, to explore hydropower and agricultural production benefits under various operational strategies. Forecast-informed optimization of reservoir releases increases energy production (6–14%), agriculture allocations (54–68%), and net profit. Application to Ethiopia showcases a novel seasonal-scale statistical forecast coupled reservoir model that translates hydroclimatic predictions into actionable information for better management at the local scale.