Potential skill of continental-scale, medium-range ensemble streamflow forecasts for flood prediction in South America

Recent scientific and computational developments have pushed hydrological forecasting systems up to continental and global scales. In this study, we evaluate the potential skill of ensemble streamflow forecasts for flood prediction in South America (SA), with a closer look on some of the large basins of the continent. Medium-range precipitation forecasts from the ECMWF Ensemble Prediction System were used to force a continental-scale, fully coupled hydrologic-hydrodynamic model to produce streamflow forecasts up to 15 days in advance. Forecasts were evaluated over a 4-year period against a reference simulation, derived from the hydrological model forced with a gridded precipitation dataset that merges data from multiple sources (MSWEP). To provide a benchmark for assessing the potential skill, forecasts based on the Ensemble Streamflow Prediction (ESP) technique were produced by running the hydrological model with precipitation data resampled from past MSWEP observations. Overall, ECMWF-based forecasts were skillful mainly at the eastern and southeastern regions of the continent (e.g., Sao Francisco, Parnaiba, Upper Parana, Tocantins-Araguaia and Uruguay basins), showing little or no added skill in large rivers draining the Andes such as the Magdalena, Orinoco, Madeira (Amazon) and right-bank tributaries of the Paraguay. In the latter basins, ECMWF-based forecasts largely overestimated the exceedance probabilities of critical thresholds due to a positive bias in the predicted precipitation (in relation to MSWEP), visible mostly during the wet season. In addition, forecasts were found to perform better than ESP in terms of both overall quality and discrimination skill at regions characterized by a warm temperate, fully-humid climate. A direct relation between forecast skill and basin size was not always valid, since the former can vary geographically along tributaries. Limitations and future developments needed for continental-scale hydrological forecasting in SA are also discussed.