Search Results (131)

The Amazonian forests located within the Guiana Shield store above-average levels of biomass per hectare. However, considerable uncertainty remains regarding carbon stocks in this region, mainly due to limited inventory data and the lack of spatial datasets that account for factors influencing variation among forest types. The present study investigates the spatial distribution of original total forest biomass in the state of Amapá, located in the northeastern Brazilian Amazon. Using data from forest inventory plots, we applied geostatistical interpolation techniques (kriging) combined with environmental variables to generate a high-resolution map of forest biomass distribution. The stocks of biomass were associated with different forest types and land uses. The average biomass was 536.5 ± 64.3 Mg ha⁻¹ across forest types, and non-flooding lowland forest had the highest average (619.1 ± 38.3), followed by the submontane (521.8 ± 49.8) and the floodplain (447.6 ± 45.5) forests. Protected areas represented 84.1% of Amapá’s total biomass stock, while 15.9% was in agriculture and ranching areas, but the average biomass is similar between land-use types. Sustainable-use reserves stock more biomass (40%) than integral-protection reserves (35%) due to the higher average biomass associated with well-structured forests and a greater density of large trees. The map generated in the present study contributes to a better understanding of carbon balance across multiple spatial scales and demonstrates that forests in this region contain the highest carbon stocks per hectare (260.2 ± 31.2 Mg ha⁻¹, assuming that 48.5% of biomass is carbon) in the Amazon. To conserve these stocks, it is necessary to go further than merely maintaining protected areas by strengthening the protection of reserves, restricting logging activities in sustainable-use areas, promoting strong enforcement against illegal deforestation, and supporting the implementation of REDD+ projects. These actions are critical for avoiding substantial carbon stock losses and for reducing greenhouse-gas emissions from this region. Full article

The Pantanal, considered the world’s largest floodplain, exhibits hydrological and ecological dynamics that are intrinsically linked to water inflows from the surrounding highlands. While the impacts of large-scale climatic phenomena and land-use changes on hydrological variables within the Upper Paraguay River Basin (UPRB) are acknowledged, their combined effects remain unknown. Recent reductions in precipitation and river discharge have adversely affected both environmental and socioeconomic aspects of the Cerrado (Brazilian Savannah) and Pantanal biomes in Brazil, raising concerns about the long-term sustainability of these important ecosystems. This study analyzes a 37-year hydrological time series (1986–2023) of rainfall, streamflow, and flooded area in three contributing basins of the Pantanal (Jauru—JB; Taquari—TB; and Miranda—MB), and reveals distinct hydrological trends influenced by different climate systems. Significant decreasing trends in rainfall and streamflow were observed in the northern JB and TB, contrasted by increasing trends in the southern MB. Consequently, a declining trend in downstream flooded areas within the Pantanal floodplain was identified. Long-term memory processes (Hurst phenomena) were identified in the time series of the Pantanal flooded area and also in the Paraguay river stage data. These findings indicate a persistent and aggregated reduction in the Pantanal’s hydrologic variables, adversely affecting its water-dependent ecology and economic activities, such as ranching, fishing, and navigation. This study underscores the necessity of adaptative management strategies to tackle the impacts of water surface loss, increased fire risks, and climate variability in the UPRB. Full article

Soil erosion poses a significant global environmental challenge, causing land degradation, deforestation, river siltation, and reduced agricultural productivity. Although the Revised Universal Soil Loss Equation (RUSLE) has been widely applied in Brazil, its use in the tropical river basins of the Amazon remains limited. This study aimed to apply a GIS-integrated RUSLE model and compare its soil loss estimates with multiple linear regression (MLR) models based on terrain attributes, aiming to identify priority areas and key geomorphometric drivers of soil erosion in a tropical Amazonian river basin. A digital elevation model based on Shuttle Radar Topography Mission (SRTM) data, land use and land cover (LULC) maps, and rainfall and soil data were applied to the GIS-integrated RUSLE model; we then defined six risk classes—slight (0–2.5 t ha⁻¹ yr⁻¹), slight–moderate (2.5–5), moderate (5–10), moderate–high (10–15), high (15–25), and very high (>25)—and identified priority zones as those in the top two risk classes. The Caeté River Basin (CRB) was classified into six erosion risk categories: low (81.14%), low to moderate (2.97%), moderate (11.88%), moderate to high (0.93%), high (0.03%), and very high (3.05%). The CRB predominantly exhibited a low erosion risk, with higher erosion rates linked to intense rainfall, gentle slopes covered by Arenosols, and human activities. The average annual soil loss was estimated at 2.0 t ha⁻¹ yr⁻¹, with a total loss of 1005.44 t ha⁻¹ yr⁻¹. Additionally, geomorphological and multiple linear regression (MLR) analyses identified seven key variables influencing soil erosion: the convergence index, closed depressions, the topographic wetness index, the channel network distance, and the local curvature, upslope curvature, and local downslope curvature. These variables collectively explained 26% of the variability in soil loss (R² = 0.26), highlighting the significant role of terrain characteristics in erosion processes. These findings indicate that soil erosion control efforts should focus primarily on areas with Arenosols and regions experiencing increased anthropogenic activity, where the erosion risks are higher. The identification of priority erosion areas enables the development of targeted conservation strategies, particularly for Arenosols and regions under anthropogenic pressure, where the soil losses exceed the tolerance threshold of 10.48 t ha⁻¹ yr⁻¹. These findings directly support the formulation of local environmental policies aimed at mitigating soil degradation by stabilizing vulnerable soils, regulating high-impact land uses, and promoting sustainable practices in critical zones. The GIS-RUSLE framework is supported by consistent rainfall data, as verified by a double mass curve analysis (R² ranging from 0.64 to 0.77), and offers a replicable methodology for soil conservation planning in tropical basins with similar erosion drivers. This approach offers a science-based foundation to guide soil conservation planning in tropical basins. While effective in identifying erosion-prone areas, it should be complemented in future studies by dynamic models and temporal analyses to better capture the complex erosion processes and land use change impacts in the Amazon. Full article

This study fosters tropical hydroclimatology research by implementing a computational modeling framework based on artificial neural networks and machine learning techniques. We evaluated two models, Multilayer Perceptron (MLP) and Support Vector Machine (SVM), in their ability to simulate 20-year monthly time series (2001–2021) of minimum and maximum river stage in the Itacaiúnas River Basin (BHRI), located in the eastern Brazilian Amazon. The models were configured using explanatory variables spanning meteorological, climatological, and environmental dimensions, ensuring representation of key local and regional hydrological drivers. Both models exhibited robust performance in capturing fluviometric variability, with a comprehensive multimetric statistical evaluation indicating MLP’s superior accuracy over SVM. Notably, the MLP model reproduced the maximum river level during a sequence of extreme hydrological events linked to natural disasters (floods) across BHRI municipalities. These findings underscore the computational model’s potential for refining hydrometeorological products, thus supporting water resource management and decision-making processes in the Amazon region. Full article

The complex interaction of hydrothermal fluids and carbonate rocks is recognized to promote significant impacts on petroleum systems, reservoir porosity, and potential. The objective of this study is to investigate the fluid phases entrapped in the mineral phases of the Barra Velha Formation (Santos Basin), including their petrographic paragenetic relationships, relative timing, temperatures of migration events, and maximum temperature reached by the sedimentary section. The petrographic descriptions (387), Rock-Eval pyrolysis (107), fluid inclusion petrography (14), and microthermometry (428) were performed on core and sidewall samples from two wells from one field of the Santos Basin. Hydrocarbon source intervals were primarily identified in lithologies with high argillaceous content. Chert samples still retain some organic remnants indicative of their original composition prior to extensive silicification. Redeposited intraclastic rocks exhibit the lowest organic content and oil potential. A hydrothermal petroleum system is identified by fluids consisting in gas condensate, light to heavy undersaturated oil, occasionally accompanied by aqueous fluids influenced by juvenile and evaporitic sources, and localized flash vaporization events. These hydrothermal fluids promoted silicification and dolomitization, intense brecciation, and lead to enhanced porosity in different compartments of the reservoir. The relative ordering of paleo-hydrothermal oils and the main oil migration and accumulation events has improved our understanding of the petroleum systems in the basin. This contribution is significant for future regional research on the evolution of fluid systems and their implications for carbonate reservoirs. Full article

The use of pesticides in agriculture can leave residues in the treated crops. Pesticides are also potential contaminants of ground and surface water, as reported in many countries. The development of efficient analytical methods to quantify pesticides in water samples is a challenge due to the low levels present. The objective of this work was to develop and validate a method for pesticide analysis in water using sample lyophilization followed by UHPLC–MS/MS and to determine pesticide levels in samples from a Brazilian hydrographic basin. In total, 77 compounds were included, of which 28 were considered only qualitatively. The method was applied to analyze 142 water samples collected during the dry and rainy seasons of 2021–2022, of which 90 were surface and 52 were groundwater samples. In total, 19 compounds were detected in the samples (≥LOD), mainly atrazine (72.5%), atrazine-2-hydroxy (50%), fipronil (18.3%), and pirimiphos-methyl (15.5%). Most compounds (17) were detected during the rainy season regardless of the environmental compartment. Twenty-five samples had quantified levels of the compounds (≥LOQ), of which 80% were collected during the dry season, and 58.3% were groundwater samples (up to 1.045 µg L⁻¹ of 2,4-D in an artesian well). The highest concentrations found in surface water were of atrazine-2-hydroxy (0.171 and 0.179 µg L⁻¹), levels that represent a potential risk to aquatic organisms (risk quotient of 1.1). This work provides an analytical method for determining pesticides in water that can be applied to other environmental pollutants. Although the levels found in the samples complied with Brazilian legislation, constant monitoring should be conducted in the region to guarantee safe levels of the pesticide in water. Full article

Deforestation and agricultural practices, such as livestock farming, disrupt biogeochemical cycles, contribute to climate change, and can lead to serious environmental problems. Understanding the water cycle and changes in discharge patterns at the watershed scale is essential to tracking how deforestation affects the flow to downstream water bodies and the ocean. The Amazon basin, which provides about 15–20% of the freshwater flowing into the oceans, is one of the most important river systems in the world. Despite this, it is increasingly suffering from anthropogenic pressure, mainly from converting rainforests to agricultural and livestock areas, which can drive global warming and ecosystem instability. In this study, we applied a calibrated Soil and Water Assessment Tool (SWAT) model to the Jari River Watershed, a part of the Brazilian Amazon, to assess the combined effects of deforestation and climate change on water resources between 2020 and 2050. The model was calibrated and validated using observed streamflow. The results show an NS of 0.85 and 0.89, PBIAS of −9.5 and −0.6, p-factor of 0.84 and 0.93, and r-factor of 0.84 and 0.78, for periods of calibration and validation, respectively, indicating a strong model performance. We analyzed four scenarios that examined different levels of deforestation and climate change. Our results suggest that deforestation and climate change could increase surface runoff by 18 mm, while groundwater recharge could vary between declines of −20 mm and increases of 120 mm. These changes could amplify streamflow variability, affect its dynamics, intensify flood risks, and reduce water availability during dry periods, leading to significant risks for the hydrology of Amazonian watersheds and human water supply. This, in turn, could profoundly impact the region’s megadiverse flora and fauna, which directly depend on balanced streamflow in the watersheds. Full article

The main focus of this study, from a sustainable perspective, was to develop mineral circularity actions for the minimization of environmental impacts, generated over decades by the processing of run-of-mine (ROM) coal in the Catarinense coal basin–Brazil (CCB–Br), from the use of potential residual fractions (candidate residues) as raw materials for the production of organo-mineral fertilizers, or OMFs (candidate products). Therefore, the objective was to assess the potential of the residual fractions, generated in the distinct phases of ROM coal processing, as candidate waste for valorization, contributing directly to the advancement of the Sustainable Development Goals (SDGs). The samples from ROM processing resulted in 24 waste fractions identified by geological characteristics and a sustainable processing methodology. These fractions were subjected to a systematic analysis using the criteria for waste valorization CPQvA (classification (C) of hazardousness, potentiality (P), quantities/viability (Qv), and applicability (A)). Two samples were identified with significant potential for valorization in the agro-industry as sustainable raw materials for the organo-mineral fertilizers. Both samples exhibited neutral stock pH values (7.0 and 7.1), low percentage Fe₂O₃ content (4.2% and 3.2%), low SO₃ content (0.5% and 1.2%), and low total sulfur content (1.0%). These characteristics qualified the studied ROM samples as raw materials suitable for the production of organo-mineral fertilizers (OMFs), and which comply with Brazilian legislation. Full article

The extensive development of lamination structures in shale significantly influences its mechanical properties. However, a systematic analysis of how laminae affect the macroscopic mechanical behavior of rocks remains absent. In this study, field emission scanning electron microscopy (FE-SEM), thin section observation, X-ray diffraction (XRD), triaxial compression and Brazilian tests were carried out on the deep marine shale of the Wufeng-Longmaxi Formation in Sichuan Basin. The results reveal four distinct laminasets: grading thin silt–thick mud (GSM₁), grading medium thick silt–mud (GSM₂), grading thick silt–thin mud (GSM₃) and alternating thick silt–thin mud (ASM). GSM₃ and ASM laminasets exhibit the weakest mechanical properties and the simplest fracture patterns, while GSM₂ demonstrates moderate mechanical properties and more complex fracture patterns. GSM₁ shows the highest mechanical strength and the most intricate fracture patterns. Mechanical properties are positively correlated with siliceous mineral content and negatively correlated with clay mineral content and scale of laminae development (average density and thickness), revealing that lamination plays a key role in fracture behavior, with more intensively developed laminasets leading to the concentrated distribution of brittle silty minerals, facilitating microcrack propagation. Moreover, microstructure has an important effect on both mechanical properties and fracture pattern. In grain-supported structures, closely packed silty brittle mineral grains reduce the energy required for crack extension. In matrix-supported structures, widespread silty brittle mineral grains increase energy requirements for crack extension, leading to more irregular and complex fracture networks. This study enhances the understanding of the effects of lamination on the rock mechanical behavior of shales, optimizing hydraulic fracturing design in shale reservoirs. Full article

The implementation of large-scale water infrastructure projects, such as the São Francisco River Integration Project with the Northeastern Hydrographic Basins (PISF), causes territorial transformations of great proportions, constituting a new hydrosocial cycle, resulting in hydrosocial territories in which not only water but also power relations and socioeconomic and physical resources circulate. In this sense, this article aims to historically analyze the interconnection between water and land issues in the Brazilian Northeast, shedding light on the territorial dynamics produced by the new hydrosocial cycle constituted by the implementation of the largest water project in the country. To this end, we interviewed actors from different groups and in various locations, conducted on-site field research, and collected and systematically analyzed important documents from the institutional websites of the Brazilian government. The main results of the research indicate that since the implementation of the PISF, a context of deep and historical political and socioeconomic inequalities in hydrosocial territories has been impacted, which has deepened conflicts over land and water and increased socio-spatial injustices. Contrary to most available approaches, which consider water scarcity a ‘natural’ (hydrological) problem that requires technical and administrative solutions, the water problem reflects the profound asymmetry of power consolidated over time and the strength of the reactionary agrarian sectors that control the State apparatus. Full article

The rising demand for clean energy production due to climate change emphasizes the importance of optimizing water resources, particularly in countries with significant hydropower potential. Existing models for the Operational Planning of Hydropower Systems (HPSOP) typically focus on the natural flows of rivers, often overlooking the potential of water transfers between rivers and basins. To address this gap, this article employs an improved mathematical model of hydropower production, considering the adjustment of the water transfer in the operation schedule as an additional optimization variable. A customized meta-heuristic, named the Evolutionary Socio-Bio Inspired Technique (ESBIT), has been tailored to integrate water transfer mechanisms into the operational planning model. The proposed model was validated through a case study at the Henry Borden Complex in São Paulo, Brazil, using real power plant parameters and inflow data from the Brazilian system. The results obtained from the test case, both with and without water transfer, demonstrate that the proposed methodology effectively captures the operational characteristics of a system that allows water transfers between rivers or basins to optimize the available water resources and system costs. Full article

Most of South America, particularly the region between the southern Amazon and southeastern Brazil, as well as a large part of the La Plata Basin, has its climate regulated by the South American Monsoon System. Extreme weather and climate events in these areas have significant socioeconomic impacts. The Madeira, São Francisco, and Paraná river basins, three major watersheds in Brazil, are especially vulnerable to wet and drought periods due to their importance as freshwater ecosystems and sources of water for consumption, energy generation, and agriculture. The scarcity of surface meteorological stations in these basins makes meteorological studies challenging, often using reanalysis and satellite data. This study aims to identify extreme weather (wet) and climate (wet and drought) events during the extended wet season (October to March) from 1980 to 2022 and evaluate the performance of two gridded datasets (CPC and ERA5) to determine which best captures the observed patterns in the Madeira, São Francisco, and Paraná river basins. Wet weather events were identified using the 95th percentile, and wet and drought periods were identified using the Standardized Precipitation Index (SPI) on a 6-month scale. In general, CPC data showed slightly superior performance compared to ERA5 in reproducing statistical measures. For extreme day precipitation, both datasets captured the time series pattern, but CPC better reproduced extreme values and trends. The results also indicate a decrease in wet periods and an increase in drought events. Both datasets performed well, showing they can be used in the absence of station data. Full article

In this study, we used machine learning (ML) to estimate time-lapse velocity variations in a reservoir region using seismic data. To accomplish this task, we needed an adequate training set that could map seismic data to velocity perturbation. We generated a synthetic seismic database by simulating reservoirs of varying velocities using a 2D velocity model typical of the Brazilian pre-salt ocean bottom node (OBN) acquisition, located in the Santos basin, Brazil. The largest velocity change in the injector well was around 3% of the empirical velocity model, which mimicked a realistic scenario. The acquisition geometry was formed by the geometry of 1 shot and 49 receivers. For each synthetic reservoir, the corresponding seismic data were obtained by estimating a one-shot forward-wave propagation using acoustic approximation. We studied the reservoir illumination to optimize the input data of the ML inversion. We split the set of synthetic reservoirs into two subsets: training (80%) and testing (20%) sets. We point out that the ML inversion was restricted to the reservoir zone, which means that it was inversion-oriented to a target. We obtained a good similarity between true and ML-inverted reservoir anomalies. The similarity diminished for a situation with non-repeatability noise. Full article

Laboratory-scale experiments were conducted on Carboniferous Limestone gravels from the Mendip Hills area, England; sandstones from the Pirambóia and Botucatu formations, Paraná sedimentary basin, Brazil; samples of schist and quartzite from Caldas Novas Hydrothermal Complex, Brazil; and the minerals tantalite, cassiterite, and columbite from mining areas at Rio Grande do Norte State, Brazil, with the purpose of evaluating the release of ²²²Rn to the water phase. The specific surface area of the samples corresponded to 1.69–81.36 cm²g⁻¹, which provided values of 0.001–1.68 dpm/g and 3.18 × 10⁻⁶ to 0.59 for the radon released and radon emanation coefficient, respectively. These results allowed us to calculate the radon flux with respect to the radon leakage, which corresponded to values of 0.00016–0.00158 Bq/m²/d for the denser materials and 0.018–0.43 Bq/m²/d for limestones and sandstones. They also permitted us to find an inverse, significant relationship between the radon generated by the minerals/rocks and the radon flux into the water phase, which was tested for sediments in coastal and inland Brazilian areas, demonstrating utility for evaluating the diffusive radon flux from the sediments, which is an important parameter to monitor submarine groundwater discharge (SGD) by means of radon as a natural tracer. Full article

The aim of this work was to determine the concentrations, distribution, and fate of potentially toxic elements [lead (Pb), zinc (Zn), nickel (Ni), copper (Cu), mercury (Hg), arsenic (As), and cadmium (Cd)] in sediments of a hydropower plant water reservoir located in the Brazilian Cerrado biome (used as system model). The purpose of this study was achieved with an analysis of the level of contamination based on the geoaccumulation index (Igeo) and factor contamination (FC) and comparisons with values established by environmental legislation. The physical–chemical–biological properties of sediment samples, the distribution, and the fate of potentially toxic elements (PTEs) in the basin of the stream studied were also investigated using Pearson’s correlation coefficient (r) and principal component analysis (PCA). Cu, Hg, and Cd concentrations in the sediment samples from most of the points analyzed were above level II of the categorization stipulated in environmental legislation, characterizing sediments of poor quality. Moreover, Igeo and FC values indicated potential pollution of the water reservoir sediment by Cd. Concentrations of Cd exceeding 0.34 mg kg⁻¹ surpassed the reference values for water quality established by Conama Resolution No. 454/2012, highlighting the urgent need for ongoing sediment quality monitoring strategies. Hence, the study water reservoir was classified as being moderately to extremely polluted due to the fate of potentially toxic metals in the sediment samples. Frequent monitoring of the sediment quality in watersheds with hydropower plants is indispensable for the assessment of water resources, considering the importance of the water supply and power generation for the population. Moreover, water contaminated by PTEs poses potential risks to river basins, as well as to human and animal health. The results of this work can assist in the investigation of other water reservoirs around the world. Full article