Forecast-informed reservoir operations to guide hydropower and agriculture allocations in the Blue Nile basin, Ethiopia

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.

Automated summary

The combination of predictive hydroclimate information with reservoir system models has the potential to mitigate climate variability risks. By coupling seasonal, statistical streamflow forecasts with reservoir models, it is possible to increase energy production, agriculture allocations, and net profit, showcasing a novel approach for better water resource management at the local scale.