Advancing Medium-Range Streamflow Forecasting for Large Hydropower Reservoirs in Brazil by Means of Continental-Scale Hydrological Modeling

• Published in: Water (Basel) Vol. 15; no. 9; p. 1693
• Main Authors: Kolling Neto, Arthur, Siqueira, Vinícius Alencar, Gama, Cléber Henrique de Araújo, Paiva, Rodrigo Cauduro Dias de, Fan, Fernando Mainardi, Collischonn, Walter, Silveira, Reinaldo, Paranhos, Cássia Silmara Aver, Freitas, Camila
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 27.04.2023
• Subjects: Analysis; Autoregressive models; Bias; bias correction; Climatology; ensemble forecasting; Hydroelectric plants; Hydroelectric power; Hydroelectric power plants; Hydrologic models; Hydrology; Parameter estimation; post-processing; Precipitation; Rain; Reservoirs; Rivers; Runoff; Scale models; Snow surveys; South America; Stochastic models; Stream discharge; Stream flow; Streamflow; Streamflow forecasting; Subsystems; Water-power; Weather forecasting; Brazil; South America
• ISSN: 2073-4441; 2073-4441
• DOI: 10.3390/w15091693

Streamflow forecasts from continental to global scale hydrological models have gained attention, but their performance against operational forecasts at local to regional scales must be evaluated. This study assesses the skill of medium-range, weekly streamflow forecasts for 147 large Brazilian hydropower plants (HPPs) and compares their performance with forecasts issued operationally by the National Electric System Operator (ONS). A continental-scale hydrological model was forced with ECMWF medium-range forecasts, and outputs were corrected using quantile mapping (QM) and autoregressive model approaches. By using both corrections, the percentage of HPPs with skillful forecasts against climatology and persistence for 1–7 days ahead increased substantially for low to moderate (9% to 56%) and high (72% to 94%) flows, while using only the QM correction allowed positive skill mainly for low to moderate flows and for 8–15 days ahead (29% to 64%). Compared with the ONS, the corrected continental-scale forecasts issued for the first week exhibited equal or better performance in 60% of the HPPs, especially for the North and Southeast subsystems, the DJF and MAM months, and for HPPs with less installed capacity. The findings suggest that using simple corrections on streamflow forecasts issued by continental-scale models can result in competitive forecasts even for regional-scale applications.