Improved Operation of Reservoir Systems – Utility of Seasonal and Monthly Updated Climate Forecasts

Seasonal and long-lead streamflow forecasts contingent on climate information are essential for short-term planning (water allocation) and for setting up contingency measures during extreme years. Similarly, monthly updates of streamflow forecasts are required for deriving reservoir operation strategies as well as for quantifying surplus and shortfall for the specified water demand for multiple uses. In this study, an operational streamflow forecasts are developed using Atmospheric General Circulation Models (AGCM) predicted precipitation for managing the Angat Reservoir System, Philippines. The methodology employs principal components regression (PCR) to downscale the AGCM predicted precipitation fields to monthly streamflow forecasts. By performing retrospective analyses that combines streamflow forecasts with a dynamic water allocation model, we show that considerable reduction in system losses (spill and evaporation) could be achieved resulting in increased reservoir yields by utilizing climate forecasts for operational reservoir systems management. Importance of updating the climate forecasts on a monthly basis and its utility in improving hydropower generation are also demonstrated. Further, analyzing the system performance under different scenarios of storage and demand, we show that the utility of climate information based reservoir inflow forecasts is more pronounced for systems with low storage to demand ratio. As challenges in implementing these scientific developments, we emphasize the importance of institutional setting and the relevant policy instruments that will promote climate information based risk management strategies.