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Several years with extreme floods or droughts in the past decade have caused human suffering in remote communities of the Brazilian Amazon. Despite documented local knowledge and practices for coping with the high seasonal variability characteristic of the regions hydrology (e.g., 10 m change in river levels between dry and flood seasons), and despite civil defense interventions by various levels of government, the more extreme years seem to have exceeded the coping capacity of the community. In this paper, we explore whether there is a real increase in variability, whether the community perceives that recent extreme events are outside the experience which shapes their responses to normal levels of variability, and what science-based policy could contribute to greater local resilience. Hydrological analyses suggest that variability is indeed increasing, in line with expectations from future climate change. However, current measures of hydrological regimes do not predict years with social hardship very well. Interviewees in two regions are able to express their strategies for dealing with normal variability very well, but also identify ways in which abnormal years exceed their ability to cope. Current civil defense arrangements struggle to deliver emergency assistance in a sufficiently timely and locally appropriate fashion. Combining these insights in the context of socialecological change, we suggest how better integration of science, policy and local knowledge could improve resilience to future trends, and identify some contributions science could make into such an arrangement.

The HAND (Height Above the Nearest Drainage), a quantitative topographic descriptor, is used to classify terrain in a manner that is related to local soil water conditions, providing hydrological meaning to the SRTM DEM. In this paper, we compare performance of using the HAND grid instead of the SRTM DEM for classifying, at regional scale (19 000 000 km2), drainage conditions of terra firme environment (plateau, slope, ecotone and waterlogged) in the Eastern Amazon, Brazil. Additionally, we emphasize the need to attenuate the canopy effects of the SRTM DEM for the boundary between forested and deforested areas, in order to produce coherent data for hydrological modeling.

Abundant research has been devoted to understanding the complexity of the biogeochemical and physical processes that are responsible for greenhouse gas (GHG) emissions from hydropower reservoirs. These systems may have spatially complex and heterogeneous GHG emissions due to flooded biomass, river inflows, primary production and dam operation. In this study, we investigated the relationships between the waterair CO2 fluxes and the phytoplanktonic biomass in the Funil Reservoir, which is an old, stratified tropical reservoir that exhibits intense phytoplankton blooms and a low partial pressure of CO2 (pCO2). Our results indicated that the seasonal and spatial variability of chlorophyll concentrations (Chl) and pCO2 in the Funil Reservoir are related more to changes in the river inflow over the year than to environmental factors such as air temperature and solar radiation. Field data and hydro-dynamic simulations revealed that river inflow contributes to increased heterogeneity during the dry season due to variations in the reservoir retention time and river temperature. Contradictory conclusions could be drawn if only temporal data collected near the dam were considered without spatial data to represent CO2 fluxes throughout the reservoir. During periods of high retention, the average CO2 fluxes were 10.3 mmol m−2 d−1 based on temporal data near the dam versus −7.2 mmol m−2 d−1 with spatial data from along the reservoir surface. In this case, the use of solely temporal data to calculate CO2 fluxes results in the reservoir acting as a CO2 source rather than a sink. This finding suggests that the lack of spatial data in reservoir C budget calculations can affect regional and global estimates. Our results support the idea that the Funil Reservoir is a dynamic system where the hydrodynamics represented by changes in the river inflow and retention time are potentially a more important force driving both the Chl and pCO2 spatial variability than the in-system ecological factors.

Study region: The Amazonian wetlands of Bolivia, known as the Llanos de Moxos, are believed to play a crucial role in regulating the upper Madeira hydrological cycle, the most important southern tributary of the Amazon River. Because the area is vast and sparsely populated, the hydrological functioning of the wetlands is poorly known. Study focus: We analyzed the hydrometeorological configurations that led to the major floods of 2007, 2008 and 2014. These data, together with flood mapping derived from remote sensing images, were used to understand the dynamics of the Llanos during the three flood events. New hydrological insights for the region: The results showed that large floods are the result of the superimposition of flood waves from major sub-basins ofthe region. As a previous study suggested, the dynamics of the floods are controlled by an exogenous process, created by the flood wave originating in the Andes piedmont that travels through the Mamoré River; and by an endogenous process, which is the runoff originating in the Llanos. Our study showed that the first process is evident only at the initial phase of the floods, and although important for attenuating the rising flood wave, it is of lesser importance compared to the endogenous process. We conclude that the endogenous process controls the magnitude and duration of major floods.

The exchanges of carbon, water and energy between the atmosphere and the Amazon basin have global implications for the current and future climate. Here, the global atmospheric inversion system of the Monitoring of Atmospheric Composition and Climate (MACC) service is used to study the seasonal and interannual variations of biogenic CO2 fluxes in Amazonia during the period 20022010. The system assimilated surface measurements of atmospheric CO2 mole fractions made at more than 100 sites over the globe into an atmospheric transport model. The present study adds measurements from four surface stations located in tropical South America, a region poorly covered by CO2 observations. The estimates of net ecosystem exchange (NEE) optimized by the inversion are compared to an independent estimate of NEE upscaled from eddy-covariance flux measurements in Amazonia. They are also qualitatively evaluated against reports on the seasonal and interannual variations of the land sink in South America from the scientific literature. We attempt at assessing the impact on NEE of the strong droughts in 2005 and 2010 (due to severe and longer-thanusual dry seasons) and the extreme rainfall conditions registered in 2009. The spatial variations of the seasonal and interannual variability of optimized NEE are also investigated. While the inversion supports the assumption of strong spatial heterogeneity of these variations, the results reveal critical limitations of the coarse-resolution transport model, the surface observation network in South America during the recent years and the present knowledge of modelling uncertainties in South America that prevent our inversion from capturing the seasonal patterns of fluxes across Amazonia. However, some patterns from the inversion seem consistent with the anomaly of moisture conditions in 2009.

Study region: The Tapajós Basin is an important Amazon tributary affected byhuman activities with great potential for water conflicts. The basin, as otherswithin the Amazon region, is receiving a number of hydropower plants, amongthem the Teles Pires plant, projected to operate in 2015.Study focus: Hydrological impacts due to climate change affect human activi-ties, such as hydroelectric generation, and should be carefully studied for betterplanning of water management. In this study, we assess climate change impactsby applying the MHD-INPE hydrological model using several climate modelsprojections as inputs. The impact assessment consisted of statistical shifts ofprecipitation and discharge. Energy production in a projected hydropower plantwas assessed through the development of annual power duration curves for eachprojection, also considering its design and structural limitations.New hydrological insights for the region: The high inter-model variability inthe climate projections drives a high variability in the projected hydrologicalimpacts. Results indicate an increase of basins sensitivity to climate change andvulnerability of water exploitation. Uncertainties prevent the identification of asingular optimal solution for impacts assessment. However, exploratory analysisof the plant design robustness for hydropower generation show a reduction in theenergy production even under projections of increased discharge, due to plantcapacity limitations. This is valuable information for stakeholders to decide aboutenergy production strategies.

We analyzed soils under forest across an elevation range (100 m, Lowland Forest, 400 m, Submontane Forest, and 1000 m, Montane Forest) in the Atlantic Rainforest of São Paulo State, Brazil. We hypothesized that soil nutrient content would increase with elevation in the surface mineral soil as a result of higher organic matter stocks, and the observation that both above and below ground biomass increase with elevation in the Atlantic Forest. This hypothesis was partially confirmed. Percent silt, carbon (C) and nitrogen (N) increased with elevation. Base cation concentrations, pH (< 4), and extractable phosphorus (P) concentration were low across the sites and did not differ among elevations. Extractable aluminum (Al) was highest at 1000 m, but there was no trend with elevation. The sharp decrease in P and cation concentration with soil depth and the low concentration of these elements in the parent material, suggest that the vegetation of the Atlantic Forest is dependent on recycling of these nutrients or atmospheric deposition to maintain productivity.

Studies on numerical modeling in Amazonia show that the models fail to capture important aspects of climate variability in this region and it is important to understand the reasons that cause this drawback. Here, we study how the general circulation 5 models of the Coupled Model Intercomparison Project Phase 5 (CMIP5) simulate the inter-relations between regional precipitation, moisture convergence and Sea Surface Temperature (SST) in the adjacent oceans, to assess how flaws in the representation of these processes can translate into biases in simulated rainfall in mazonia. Using observational data (GPCP, CMAP, ERSST.v3, ERAI and evapotranspiration) and 21numerical simulations from CMIP5 during the present climate (19792005) in June, July and August (JJA) and December, January and February (DJF), respectively, to represent dry and wet season characteristics, we evaluate how the models simulate precipitation, moisture transport and convergence, and pressure velocity (omega) in different regions of Amazonia. Thus, it is possible to identify areas of Amazonia that are more or less influenced by adjacent ocean SSTs. Our results showed that most of the CMIP5 models have poor skill in adequately representing the observed data. The regional analysis of the variables used showed that the underestimation in the dry season (JJA) was twice in relation to rainy season as quantified by the Standard Error of the Mean (SEM). It was found that Atlantic and Pacific SSTs modulate the 20 northern sector of Amazonia during JJA, while in DJF Pacific SST only influences the eastern sector of the region. The analysis of moisture transport in JJA showed that moisture preferentially enters Amazonia via its eastern edge. In DJF this occurs both via its northern and eastern edge. The moisture balance is always positive, which indicates that Amazonia is a source of moisture to the atmosphere. Additionally, our results showed that during DJF the simulations in northeast sector of Amazonia have a strong bias in precipitation and an underestimation of moisture convergence due to the higher influence of biases in the Pacific SST. During JJA, a strong precipitation bias was observed in the southwest sector associated, also with a negative bias of mois-ture convergence, but with weaker influence of SSTs of adjacent oceans. The poor representation of precipitation-producing systems in Amazonia by the models and the difficulty of adequately representing the variability of SSTs in the Pacific and Atlantic oceans may be responsible for these underestimates in Amazonia.

The Amazon hosts one of the largest stocks of arable land in the world. However, little is known about the available extent of agricultural land in conformity with legal, agronomical and environmental requirements. This study aims to identify and quantify potentially available areas for agricultural expansion in the Brazilian Amazon considering the extent of: (i) legally available forested lands, (ii) previously converted lands with suitable productive capacity and (iii) previously converted lands free of land use conflicts. This analysis was carried out by integrating georeferenced information on land use, soil fertility, terrain slope, biomass, protected areas and land use policies (e.g. Brazilian Forest Code) into a conditional decision support procedure, based on Boolean inference techniques. Our results showed that 11.69% (493,103.03 km2) of the Brazilian Amazon would be potentially available for agricultural expansion in the year 2010. This area was essentially dominated by forests (59.37%), followed by previously converted lands (40.63%). The extent of this area was equivalent to 75.86% of the total cultivated area in Brazil in 2010. However, the effective usage of these areas would have direct political and environmental implications. First, it is expected that the effective usage of available forests would detract recent achievements of the Brazilian Action Plan for Prevention and Control of Deforestation in the Amazon, which has reduced deforestation by 79% from historical rates. Moreover, the conversion of these areas could result in a committed emission of 13 ± 1 Pg CO2eq to the atmosphere which is equivalent to the total emissions from land cover change registered in Brazil during the 20002010 period. Therefore, the compensation of environmental liabilities stands as the most consistent destination for the available forests mapped in this study. To minimize environmental impacts, agricultural expansion in the Brazilian Amazon should be restricted to already converted areas. This land cover class totalizes 200,000 km2, which could support agricultural expansion without promoting the advance of deforestation.