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

In most cases authors are permitted to post their version of the article (e.g. in Word or Tex form) to their personal website or institutional repository. Authors requiring further information regarding Elsevier's archiving and manuscript policies are encouraged to visit: s u m m a r y 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 predic-tors 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. Introduction With more than 70 interconnected (hydraulically and through transmission lines of electrical energy) hydropower reservoirs across the country, the Brazilian hydropower system uses complex optimization models (e.g. Barros et al., 2003) to produce electrical energy to maximize reliability and minimize cost. For instance, if in September most hydropower plants have low levels of energy storage (i.e. low levels of water head in the hydropower reservoirs and hence more water needed to produce a unit of energy) and if the upcoming rainy season (January–April) is expected to be drier than normal, then the System National Operator (ONS) usually starts producing higher cost energy from stand-by thermal plants in order to reduce the hydroenergy production and avoid a complete depletion of the reservoirs, which would lead to a more dramatic rise in the cost of electrical energy in the subsequent season. However, the use of thermal plants and reduction in hydro-power production before an upcoming above normal wet season may lead to unnecessary losses of hydroenergy through spillage and evaporation and to an avoidable increase in the electrical energy cost due to the use of thermal plants. In order to make better decisions during such situations, forecasts of inflow (e.g. Costa et have been used extensively by ONS to anticipate unusual scenarios of …