Study region
This paper describes a major ensemble-forecasts verification effort for inflows of three large-scale river basins of Brazil: Upper São Francisco, Doce, and Tocantins Rivers.

Study focus
In experimental scenarios, inflow forecasts were generated forcing one hydrological model with quantitative precipitation forecasts (QPF) from three selected models of the TIGGE database. This study provides information on the regional ensemble performance and also evaluates how different QPF models respond for the different basins and what happens with the use of combined QPF in a greater ensemble.

New hydrological insights for the region
This work presents one of the first extensive efforts to evaluate ensemble forecasts for large-scale basins in South America using TIGGE archive data. Results from these scenarios provide validation criteria and confirm that ensemble forecasts depend on the particular EPS used to run the hydrological model and on the basin studied. Furthermore, the use of the Super Ensemble seems to be a good strategy in terms of performance and robustness. The importance of the TIGGE database is also highlighted.

Study region
The Tapajós Basin is an important Amazon tributary affected by human activities with great potential for water conflicts. The basin, as others within the Amazon region, is receiving a number of hydropower plants, among them the Teles Pires plant, projected to operate in 2015.

Study focus
Hydrological impacts due to climate change affect human activities, such as hydroelectric generation, and should be carefully studied for better planning of water management. In this study, we assess climate change impacts by applying the MHD-INPE hydrological model using several climate models projections as inputs. The impact assessment consisted of statistical shifts of precipitation and discharge. Energy production in a projected hydropower plant was assessed through the development of annual power duration curves for each projection, also considering its design and structural limitations.

New hydrological insights for the region
The high inter-model variability in the climate projections drives a high variability in the projected hydrological impacts. Results indicate an increase of basin’s sensitivity to climate change and vulnerability of water exploitation. Uncertainties prevent the identification of a singular optimal solution for impacts assessment. However, exploratory analysis of the plant design robustness for hydropower generation show a reduction in the energy production even under projections of increased discharge, due to plant capacity limitations. This is valuable information for stakeholders to decide about energy production strategies.

This study investigates the applicability of error corrections to satellite-based precipitation products in streamflow simulations. A three-year time series (2008–2011) is considered across 19 sub-basins of the Tocantins–Araguaia basin (764,000 km2), located in the center-north region of Brazil. A raingauge network (24 h accumulation) of approximately 300 collection points (∼1 gauge every 2500 km2) is used as reference for evaluating the following four satellite rainfall products: the Tropical Rainfall Measuring Mission real-time 3B42 product (3B42RT), the Climate Prediction Center morphing technique (CMORPH), the Global Satellite Mapping of Precipitation (GSMaP), and the NOAA Hydroestimator (HYDRO-E). Ensemble streamflow simulations, for both dry and rainy seasons, are obtained by forcing the Distributed Hydrological Model developed by the Brazilian National Institute for Space Research (MHD–INPE) with the satellite rainfall products, corrected using a two-dimensional stochastic satellite rainfall error model (SREM2D). The ensemble simulations are evaluated using streamflow output derived by forcing the model with reference rainfall gauge data. SREM2D is able to correct for errors in the satellite precipitation data by pushing the modeled streamflow ensemble closer to the reference river discharge, when compared to the simulations forced with uncorrected rainfall input. Ensemble streamflow error statistics (MAE and RMSE) show a decreasing trend as a function of the catchment area for all satellite products, but the rainfall-to-streamflow error propagation does not show any dependence on the basin size.

Extreme events are part of climate variability. Dealing with variability is still a challenge that might be increased due to climate change. However, impacts of extreme events are not only dependent on their variability, but also on management and governance. In Brazil, its semi-arid region is vulnerable to extreme events, especially droughts, for centuries. Actually, other Brazilian regions that have been mostly concerned with floods are currently also experiencing droughts. This article evaluates how a combination between climate variability and water governance might affect water scarcity and increase the impacts of extreme events on some regions. For this evaluation, Ostrom’s framework for analyzing social-ecological systems (SES) was applied. Ostrom’s framework is useful for understanding interactions between resource systems, governance systems and resource users. This study focuses on social-ecological systems located in a drought-prone region of Brazil. Two extreme events were selected, one in 1997–2000, when Brazil’s new water policy was very young, and the other one in 2012–2015. The analysis of SES considering Ostrom’s principle “Clearly defined boundaries” showed that deficiencies in water management cause the intensification of drought’s impacts for the water users. The reasons are more related to water management and governance problems than to drought event magnitude or climate change. This is a problem that holdup advances in dealing with extreme events.

The Tocantins River, located at the northern region of Brazil with over 300 000 km2 of drainage area, is an important water body in terms of hydropower production. The occurrence of floods along the Tocantins River is a relatively frequent event that affects hydropower plant operations and several cities and their inhabitants. Motivated by recent flooding issues, a hydrological forecasting system was developed in order to assist the decision making of dam operation for flood control. The model uses merged rainfall information from ground-based telemetric gauges and real-time TRMM satellite rainfall estimates. Streamflow forecasts are obtained based on quantitative precipitation forecasts from two different sources, CPTEC Eta 15 km regional deterministic model and the Global Ensemble Forecasting System-VII, maintained by the National Center for Environmental Prediction-National Oceanic and Atmospheric Administration. We present here the forecasting system analysis of the 2011/2012 rainy season flood predictions with the use of ensemble forecasts, and comparison results of deterministic and ensemble forecasts for the major flood of 2012/2013.