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.

The modeling of seasonal and interannual streamflow forecasting at northeastern Brazil represents a great relevance problem to the use and management of water resources; which demands greater prediction ability models. This is still a difficult task to solve due to the seasonal and interannual climate variability at the semi-arid region. This work presents the artificial neural networks (ANN) as an alternative for modeling the seasonal to interannual climate prediction,. For the development of this task the hydropraphic Oros weir Basin was chosen due to its importance as water resources in the State of Ceara. According to recent studies, the temperatures of the North Atlantic, South Atlantic and equatorial Pacific can be satisfactorily as predictors for the Northeast climate. The proposed model predicts, in July, the next rainy season (January to June) river flow regime. This time frame is of great relevance for the allocation of water resources. Among the studied models, those using the average temperature anomalies of April, May and June preceding the predicted year as input data showed the highest Nash-Suttcliffe efficiency (0.80).

O Semiárido brasileiro está sujeito a secas cada vez mais severas em razão das mudanças climáticas, o que exige a adoção de medidas mitigadoras e adaptativas. Essas medidas serão mais eficientes se favorecerem ações proativas que minimizem a vulnerabilidade e gerenciem o risco de secas. A captação e o armazenamento da água de chuva em cisternas foram idealizados como medidas de gestão do risco e têm sido apontados como estratégia de sucesso no processo de adaptação de comunidades vulneráveis à seca. No entanto, os mecanismos de suporte ao uso das cisternas possuem falhas, favorecendo seu uso na gestão de crise para o armazenamento não água de chuva, mas da fornecida por carros-pipas. Com base nesses pressupostos e utilizando dados disponibilizados pelo Observatório da Seca, apresentam-se reflexões acerca da eficácia das cisternas como medida de adaptação e gestão do risco. Foi observado que as cisternas são úteis na gestão do risco e da crise, no entanto ainda há dificuldades em se mensurar sua contribuição para a redução da vulnerabilidade à seca. Além disso, os problemas relacionados ao sistema podem contribuir para seu emprego prioritário na gestão da crise, ao invés de assumir o seu papel genuíno de adaptação e gestão de riscos.

Approximately 57% of the Brazilian northeast region is recognized as semi-arid land and has been undergoing intense land use processes in the last decades, which have resulted in severe degradation of its natural assets. Therefore, the objective of this study is to identify the areas that are susceptible to desertification in this region based on the 11 influencing factors of desertification (pedology, geology, geomorphology, topography data, land use and land cover change, aridity index, livestock density, rural population density, fire hot spot density, human development index, conservation units) which were simulated for two different periods: 2000 and 2010. Each indicator were assigned weights ranging from 1 to 2 (representing the best and the worst conditions), representing classes indicating low, moderate and high susceptibility to desertification. The results indicate that 94% of the Brazilian northeast region is under moderate to high susceptibility to desertification. The areas that were susceptible to soil desertification increased by approximately 4.6% (83.4 km2) from 2000 to 2010. The implementation of the methodology provides the technical basis for decision-making that involves mitigating actions and the first comprehensive national assessment within the United Nations Convention to Combat Desertification framework.

Brazilian strategic interest in the Madeira River basin, one of the most important of the southern Amazon tributaries, includes the development of hydropower to satisfy the country’s growing energy needs and new waterways to boost regional trade and economic development. Because of evidences that climate change impacts the hydrological regime of rivers, the aim of this study was to assess how global climate change and regional land cover change caused by deforestation could affect the river’s hydrological regime. To achieve this goal, we calibrated a large-scale hydrological model for the period from 1970–1990 and analyzed the ability of the model to simulate the present hydrological regime when climate model simulations were used as input. Climate change projections produced by climate models were used in the hydrological model to generate scenarios with and without regional land-use and land-cover changes induced by forest conversion to pasture for the period from 2011–2099. Although results show variability among models, consensus scenarios indicated a decrease in the low-flow regime. When the simulations included forest conversion to pasture, climate change impacts on low flows were reduced in the upper basin, while, in the lower basin, discharges were affected along the whole year due to the more vigorous land-use conversion in the Brazilian region of the basin.

O sistema solo-planta-atmosfera compreende uma série de processos complexos que se inter-relacionam com atributos físicos, químicos e biológicos do solo, da água, da planta e da atmosfera. As trocas entre a superfície terrestre e a atmosfera ocorrem ao longo dos ciclos de, praticamente, todos os elementos biogeoquimicamente ativos, tais como água, carbono, nitrogênio, metano, compostos orgânicos voláteis, entre outros. Esses ciclos são de suma para
o funcionamento do sistema terrestre, definindo padrões de clima, vegetação e solos, razão pela qual o estudo do sistema solo-planta-atmosfera tem sido área de interesse em várias disciplinas: ciências do solo, hidrologia, recursos hídricos, climatologia, ecologia, engenharia florestal, agronomia, entre outras.

As projeções de vazões para as bacias brasileiras que possuem plantas produtoras de hidroeletricidade foram obtidas usando as precipitações dos modelos globais do CMIP3 (utilizados no quarto relatório do Intergovernmental Panel on Climate Change – IPCC-AR4) para o período de 2010 a 2099 dos cenários A1B, B1 e A2. As vazões foram geradas a partir desta chuva pelo modelo hidrológico Soil Moisture Account Procedure (SMAP), sendo inicializado por precipitações corrigidas estatisticamente a partir dos dados de chuva mensal do Climatic Research Unit (CRU) e por evaporações estimadas pelo método de Penann-Mothieth. Foram analisados os impactos percentuais nas vazões médias anuais para os períodos de 2010 a 2039, 2040 a 2069 e 2070 a 2099 em comparação ao período de 1931 a 1999. Os modelos do IPCC-AR4 convergem quanto ao impacto no setor elétrico na região sudeste/centro-oeste e Sul, mostrando que possivelmente as vazões devem reduzir em até 5% em cada período de 30 anos em Furnas e aproximadamente 4% até o final do século em Itaipu. Quanto ao setores Norte e Nordeste a divergência entre modelos indica bastante incerteza nestas regiões, porém sugerem uma margem na qual o planejamento de infraestrutura deve ocorrer. As divergências dos modelos IPCC-AR4 quanto às projeções demonstram grande incerteza. Entretanto, estas informações definem uma margem dos possíveis cenários futuros de vazões e podem ser consideradas na adoção de políticas de gestão.

The 2012 drought in Northeast Brazil was the harshest in decades, with potentially significant impacts on the vegetation of the unique semi-arid caatinga biome and on local livelihoods. Here, we use a coupled climate–vegetation model (CCM3-IBIS) to: (1) investigate the role of the Pacific and Atlantic oceans in the 2012 drought, and; (2) evaluate the response of the caatinga vegetation to the 2012 climate extreme. Our results indicate that anomalous sea surface temperatures (SSTs) in the Atlantic Ocean were the primary factor forcing the 2012 drought, with Pacific Ocean SST having a larger role in sustaining typical climatic conditions in the region. The drought strongly influenced net primary production in the caatinga, causing a reduction in annual net ecosystem exchange indicating a reduction in amount of CO2 released to the atmosphere.