The Amazon basin, the world’s largest river basin, is a key global climate regulator. Due to the lack of an extensive network of gauging stations, this basin remains poorly monitored, hindering the management of its water resources. Due to the vast extension of the Amazon basin, hydrological modeling is the only viable approach to monitor its current status. Here, we used the Soil and Water Assessment Tool (SWAT), a process-based and time-continuous eco-hydrological model, to simulate streamflow and hydrologic water balance in an Amazonian watershed where only a few gauging stations (the Jari River Basin) are available. SWAT inputs consisted of reanalysis data based on orbital remote sensing. The calibration and validation of the SWAT model indicated a good agreement according to Nash-Sutcliffe (NS, 0.85 and 0.89), Standard Deviation Ratio (RSR, 0.39 and 0.33), and Percent Bias (PBIAS, −9.5 and −0.6) values. Overall, the model satisfactorily simulated water flow and balance characteristics, such as evapotranspiration, surface runoff, and groundwater. The SWAT model is suitable for tropical river basin management and scenario simulations of environmental changes.

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.

The Basin of São Francisco River is essential for Brazil, possessing many physical, social, environmental, and economic characteristics that vary depending on the region. This article presents changes in land use and land cover in the basin for the years 1985 and 2021, using data from the MapBiomas Project, compiled through Google Earth Engine (GEE) and processed with QGIS software. Activities within the basin generate significant impacts, making the study of land use and land cover crucial to understanding both natural and anthropogenic dynamics. The results show an overall reduction trend in forested areas and non-forest formations. In contrast,areas devoted to agriculture and livestock farming as non-vegetated regions, have increased. Urbanization and the development of industrial areas contribute to habitat fragmentation and pollution. Sustainable urban planning strategies, such as the incorporation of green spaces and the adoption of ecological building practices, are necessary to mitigate the impacts of urban expansion and preserve the ecological integrity of the basin. The contributions and advancements of geotechnology to this study are undeniable, demonstrating the feasibility of conducting analyses over large areas while optimizing time for such studies.

Os gases traços liberados pela queima de biomassa afetam significativamente o meio ambiente, alterando o balanço de energia, os ciclos biogeoquímicos e o clima. Partindo deste fato, com o objetivo de identificar o período e as principais áreas afetadas por entradas de plumas de aerossóis de queimada na atmosfera do bioma Amazônia e de analisar as dinâmicas de uso e ocupação do solo nas principais áreas de emissões, foram analisadas imagens do sensor Multiangle Imaging Spectro Radiometer (MISR) a bordo do Satélite TERRA, com resolução de 275 m em nove ângulos, variando de 0° nadir a 70° fora do nadir e, posteriormente, comparadas a dados oriundos do projeto MapBiomas. Com o software MISR INteractive eXplorer (MINX) foram processadas as alturas das plumas, permitindo a criação de mosaicos multitemporais. Posteriormente, a partir de um programa originado em IDL/ENVI obteve-se os dados de interesse, como a localização, a potência radiativa do fogo e a altura de injeção de cada pluma. Após o processamento inicial, sucedeu a conversão dos dados e a inserção em Sistemas de Informações Geográficas (SIG), sobrepondo estes dados com os demais, originários do MapBiomas. Nesse contexto, ressalta-se que o trabalho realizado pode servir como um importante banco de dados para a visualização e análise da distribuição de fenômenos, auxiliando na tomada de decisões e posteriores ações de gestão e redução de possíveis riscos à sociedade.

Esse trabalho possui como objetivo a utilização de produtos orbitais para investigar a suscetibilidade da vegetação à queima, bem como a relação da condição da vegetação com a recorrência de incêndios e o volume da precipitação no estado de Minas Gerais nos anos de 2000 a 2015. A pesquisa foi desenvolvida partindo da aquisição e processamento de dados orbitais provenientes do sensor Moderate Resolution Imaging Spectroradiometer (MODIS) e dados de precipitação provenientes do satélite Tropical Rainfall Measuring Mission (TRMM). A metodologia consistiu na geração de mapas de médias anuais do Vegetation Condition Index (VCI) a partir do produto MOD13A3 do sensor MODIS para a análise da suscetibilidade da vegetação à queima; geração de dados anuais de precipitação acumulada a partir do produto 3B43 do TRMM e geração de mapas anuais de focos66 de incêndios obtidos a partir dos produtos MYD14 e MOD14 do sensor MODIS. Embora a condição da vegetação e sua suscetibilidade à queima esteja diretamente relacionada com a influência da precipitação, notadamente o estudo mostra que o uso e ocupação da terra é o fator crucial em relação as ocorrências de queimadas.