Climate informed long term seasonal forecasts of hydroenergy inflow for the Brazilian hydropower system

Efficient management of water and energy is an important goal of sustainable development for any nation. Streamflow forecasts, have been used in complex optimization models to maximize water use efficiency and electrical energy production. In this paper we develop a statistical model for the long term forecasts of hydroenergy inflow into the Brazilian hydropower system, which consists of more than 70 hydropower reservoirs. At present, the planning of reservoir operation and energy production in Brazil is made with no reliable long term (one season or longer lead times) streamflow forecasts. Here we use the NINO3 index and the main modes of the tropical Pacific thermocline structure as climate predictors in order to achieve skillfull forecasts at long leads. Cross-validated results show that about 50% of the total hydroenergy inflow can be predicted with moderate accuracy up to 20 month lead time.