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Despite optical remote sensing (and the spectral vegetation indices) contributions to digital soil-mapping studies of soil organic carbon (SOC), few studies have used active radar remote sensing mission data like that from synthetic aperture radar (SAR) sensors to predict SOC. Bearing in mind the importance of SOC mapping for agricultural, ecological, and climate interests and also the recently developed methods for vegetation monitoring using Sentinel-1 SAR data, in this work, we aimed to take advantage of the high operationality of Sentinel-1 imaging to test the accuracy of SOC prediction at different soil depths using machine learning systems. Using linear, nonlinear, and tree regression-based methods, it was possible to predict the SOC content of soils from western Bahia, Brazil, a region with predominantly sandy soils, using as explanatory variables the SAR vegetation indices. The models fed with SAR sensor polarizations and vegetation indices produced more accurate results for the topsoil layers (0–5 cm and 5–10 cm in depth). In these superficial layers, the models achieved an RMSE in the order of 5.0 g kg−1 and an R2 ranging from 0.16 to 0.24, therefore explaining about 20% of SOC variability using only Sentinel-1 predictors. [ABSTRACT FROM AUTHOR]

Western Bahia, a region in Northeast Brazil highly dependent on water availability due to the large concentration of irrigated lands, has been suffering from decreasing precipitation in the last decades. The mean climate of Northeast Brazil and its variability have been linked to teleconnections with the Atlantic and Pacific sea surface temperatures, including the Atlantic Multidecadal Oscillation (AMO). This study investigates how large‐scale (AMO) and mesoscale (orographic) interactions are related to precipitation patterns in the region. Time series of precipitation and naturalized flows (corresponding to the flow that would occur in the river section if there were no anthropogenic actions) for the period 1981–2020 are analysed, indicating an average reduction of 11.5% in rainfall since the 1980s. The analyses show a significant (α = 0.05) rainfall reduction in the wettest months, the December and January bimester (DJ). A strong and significant negative correlation between AMO and precipitation (R = −0.62, α = 0.01) indicates a decrease in DJ rainfall when the AMO index is positive. The five rainiest and five driest DJ bimesters between 1981 and 2020 were selected to investigate the changes in atmospheric circulation. In the rainiest years, large‐scale mechanisms interact with the local topography to promote a major convection centre over Western Bahia. The driest years show suppressed convection over the topographic gradient and a change in the convection centre several hundred kilometres to the west. The continued increase in temperatures in the North Atlantic may perpetuate the decline in Western Bahia precipitation, putting pressure on water availability and impacting economic activities in the region. [ABSTRACT FROM AUTHOR]

The water crisis is a reality in Western Bahia. In this region, a hydroclimatic monitoring system capable of providing water availability information in advance for water users was implemented objectively to avoid water conflicts. In this study, we proposed the integration between the hydroclimatic monitoring system and a linear programming method to optimize the agricultural net benefit considering the scenarios of rainfall delay or reduction. Case studies were demonstrated in five farms and three municipalities of Western Bahia. The results show that in irrigated areas, the model optimizes the net economic benefit by the possibility of a continuous or double-cropping system, even in rainfall delay or reduction, where irrigation can supply the water demand of crops. In rainfed areas, it is noticeable that in rainfall delay or reduction scenarios, the model response is not to crop, due to the accentuated water deficit in crops, which may cause a significant yield reduction. It was found in a farm-level analysis, where the model response was not to crop, and farmers had a yield reduction of 61% in rainfed areas. This study opens the integration between the optimization methodologies and the hydroclimatic monitoring system with new insights into how this integration can guide water governance actions in regions where the water crisis is a reality. [ABSTRACT FROM AUTHOR]

The largest and most dynamic agricultural frontier in Brazil is known as MATOPIBA, an area that covers part of the Cerrado biome. Within this region, Western Bahia stands out as a large producer of soy and cotton. There are no studies that quantify carbon stocks for different land uses and land cover types in Western Bahia, which hinders comprehension of the role of agricultural expansion in carbon dynamics and the development of sustainable agriculture policies. Here, we evaluate how the land use changes in this region have affected the carbon balance in the aboveground biomass (AGB), belowground biomass (BGB), and soil reservoirs. We collected soil samples for areas with different land uses and land cover types to estimate soil carbon stocks (SCS) and combined remote sensing results and modeling techniques to develop a historical reconstruction of spatial patterns of SCS, AGB, and BGB during the period 1990–2018. The replacement of areas from the forest formations class with pasture and rainfed agriculture reduced the 100 cm depth SCS (SCS100) by 37.3% (p = 0.031) and 30.3% (p = 0.053), respectively. By contrast, the conversion of pasture and rainfed agriculture to irrigated agriculture increased SCS100 by 34% (p = 0.034) and 26.5% (p = 0.022), respectively. Spatial changes in historical carbon stocks are strongly associated with land use changes that occurred between 1990 and 2018. We estimated a non-significant loss of 61.9 Tg-C (p = 0.726) from the total carbon stocks (calculated as the sum of AGB, BGB, and SCS) of which 80% of the losses came from soil stocks, 11% from BGB, and 8% from AGB. These findings reveal the need to monitor carbon stocks in sandy soils to reduce the uncertainties of estimates and support the development of effective sustainable agriculture policies. The best alternatives for reducing carbon losses in the Cerrado are to maintain natural forest cover and to recover soils through sustainable soil management, especially in pasturelands where soil carbon stocks are lowest. [ABSTRACT FROM AUTHOR]

Western Bahia is a critical region in Brazil's recent expansion of agricultural output. Its outstanding increase in production is associated with strong growth in cropland area and irrigation. Here we present analyses of Western Bahian historical changes in land use, including irrigated area, and suitability for future agricultural expansion that respects permanent protection areas and the limits established by the Brazilian Forest Code in the Cerrado biome. For this purpose, we developed a land use and land cover classification database using a random forest classifier and Landsat images. A spatial multicriteria decision analysis to evaluate land suitability was performed by combining this database with precipitation and slope data. We demonstrate that between 1990 and 2020, the region's total agricultural area increased by 3.17 Mha and the irrigated area increased by 193,480 ha. Throughout the region, the transition between the different classes of land use and land cover followed different pathways and was strongly influenced by land suitability and also appears to be influenced by Brazil's new Forest Code of 2012. We conclude that even if conservation restrictions are considered, agricultural area could nearly double in the region, with expansion possible mostly in areas we classify as moderately suitable for agriculture, which are subject to climate hazards when used for rainfed crops but are otherwise fine for pastures and irrigated croplands. [ABSTRACT FROM AUTHOR]

Western Bahia, part of a large Brazilian agricultural frontier, is located mainly in fragile, sandy soils in a tropical seasonal climate with dry winters, characteristics that facilitate soil carbon loss. This study evaluates whether rainfed and irrigated agriculture in Western Bahia were able to sequester carbon and re-establish the soil organic carbon content (SOCC) lost due to land use change. Between 2010 and 2018, a total of 5469 soil samples were collected in the 0.00–0.20 m soil layer from nine farms and were used to calculate the annual rate of SOCC variation. The most recent SOCC measured in plots where land use change occurred 20 years ago was compared with the SOCC measured in areas of native vegetation (Cerrado). Results showed that (i) irrigated sandy agricultural lands replenished SOCC to the level observed in native vegetation by 20 years after a land use change event and are still capturing carbon at a significant rate, (ii) clayey, rainfed agricultural lands also sequester carbon, but these soils are not representative of the region, and (iii) sandy, rainfed agricultural lands, the predominant soil type and management practice in Western Bahia, are not a sink of CO2. [ABSTRACT FROM AUTHOR]