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La degradación de las tierras es considerada uno de los más graves problemas ambientales actualmente. Sin embargo, en Brasil, el grado de conocimiento del proceso y el mapeo de su expansión aún son muy incipientes. El monitoreo de la degradación, utilizando datos de satélites y metodologías estandarizadas, es fundamental para contribuir con estrategias de combate a la degradación ambiental y adaptación a los eventos climáticos extremos, principalmente sequías. El objetivo de esta investigación es evaluar el proceso de degradación de la cobertura vegetal en el territorio brasileño y su relación con la reducción de las lluvias, a partir de series temporales de datos de satélites durante el período 2000-2021. Se identificaron las áreas del territorio brasileño donde la degradación alteró significativamente la dinámica de la vegetación a partir del análisis de las correlaciones entre la tendencia del Índice de Vegetación por Diferencia Normalizada (NDVI), el índice de quemas y la dinámica de la lluvia. Los datos permitieron identificar que 39% de la cobertura vegetal de Brasil se degradó en este período. Por otro lado, se observó un crecimiento de 33% de biomasa, caracterizada por la ganancia de cobertura vegetal agrícola o pastizales. Los resultados permitieron identificar las regiones donde hubo mayor pérdida de vegetación por deforestación y quemas, en las cuales también se registró una reducción histórica en los volúmenes de precipitación. Los resultados alertan sobre la alta velocidad de la degradación de la vegetación en el territorio brasileño. Como consecuencia, los procesos irreversibles de deterioro ambiental se han expandido, incrementando de esta forma el riesgo de savanización de la Amazonia y la desertificación en el Semiárido brasileño.

In order to better understand the extent to which global climate variability is linked to long-term mean and extreme sea level patterns, correlations between average sea levels at coastal sites throughout North America and low-frequency oscillations of several climate indices (CIs) were analyzed for the entire period of 1948–2018 as well as three equal-length sub-periods using correlation analysis. Correlation strength was assessed using Pearson’s correlation coefficient, while significance was estimated using Leave-One-Out Cross-Validation and a bootstrapping technique (p-value). The sliding window size, lag time, and beginning month were varied for optimal correlation; 60-month sliding windows, along with 0 lag time, resulted in the strongest correlations. Strong (r >= 0.60) and significant (p-value

Water has become more important in agricultural implementations over the years, as has the need for water management. Thus, Water Use Efficiency (WUE) has been used as an alternative form of detecting the variability of water management based on the carbon–water cycle. The study aimed to map and quantify the spatio-temporal distribution of WUE based on its interactions with environmental changes. It focused on an agricultural area in the westernmost region of Bahia, Northeast Brazil (NEB). For WUE estimation, data from Collection 6 MODIS Gross Primary Productivity (GPP) and Evapotranspiration (ET) products with a spatial resolution of 0.05° × 0.05° were obtained from the Earth Explorer website. Subsequently, annual WUE anomalies were calculated based on the 2001–2019 period. The results obtained indicated that the highest values of GPP (580 gC/m2), ET (3000 mm), and WUE (3.5 gC/mm·m2) occurred in agricultural areas, associated with cultural treatments and insertion of irrigation, which helped in the higher WUE values and consequently increased agricultural productivity in the study region. In addition, there was a marked influence of the phases of the climate variability mode—El Niño-Southern Oscillation (ENSO)—on the annual variability of the WUE, with a reduction of 96% during the La Niña of 2016 (an increase of 89% during El Niño of 2005). During El Niños, vegetation had greater efficiency resulting from the adaptation of vegetation in maintaining the carbon–water balance, using water more efficiently. However, unlike Las Niñas, with excessive precipitation there is an interference in the WUE, which interferes with the absorption of radiation and nutrients for the biophysical processes of vegetation and agriculture and, consequently, agricultural production. The use of WUE for agriculture is extremely important, especially for Brazil and countries with an economy based on primary production. This information on the way vegetation (native or agricultural) responds to interactions with the environment aids in decision-making about water management, possibly lowering losses or agricultural damage caused by a lack of water.

At present, satellite rainfall products, such as the Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) product, have become an alternative source of rainfall data for regions where rain gauge stations are sparse, e.g., Northeast Brazil (NEB). In this study, continuous scores (i.e., Pearson’s correlation coefficient, R; percentage bias, PBIAS; and unbiased root mean square error, ubRMSE) and categorical scores (i.e., probability of detection, POD; false alarm ratio, FAR; and threat score, TS) were used to assess the CHIRPS rainfall estimates against ground-based observations on a pixel-to-station basis, during 01 January 1981 to 30 June 2019 over NEB. Results showed that CHIRPS exhibits better performance in inland regions (R, PBIAS, and ubRMSE median: 0.51, −3.71%, and 9.20 mm/day; POD, FAR, and TS median: 0.59, 0.44, and 0.40, respectively) than near the coast (R, PBIAS, and ubRMSE median: 0.36, −5.66%, and 12.43 mm/day; POD, FAR, and TS median: 0.32, 0.42, and 0.26, respectively). It shows better performance in the wettest months (i.e., DJF) than in the driest months (i.e., JJA) and is sensitive to both the warm-top stratiform cloud systems and the sub-cloud evaporation processes. Overall, the CHIRPS rainfall data set could be used for some operational purposes in NEB.

Resumen El semiárido brasileño frecuentemente se ve afectado por sequías prolongadas. Durante el período 2010-2017, la región semiárida brasileña enfrentó la “sequía del siglo”, considerada la peor registrada en la historia del país. Este artículo tiene como objetivo hacer una evaluación histórica de diferentes fases de las políticas públicas implementadas en la región, con el fin de promover la convivencia con la sequía. Con base en una investigación histórica documental y el monitoreo satelital de los impactos de las sequías, se analizaron las acciones gubernamentales que contribuyeron a brindar una mayor disponibilidad de agua en la región semiárida brasileña, con énfasis en el análisis de la efectividad de la gestión del agua y los impactos de las tecnologías sociales para el almacenamiento del agua de lluvia en comunidades rurales dispersas. Los resultados de la investigación evidenciaron que las políticas implementadas a lo largo de la historia, con frecuencia en un modelo centralizado, no fueron efectivas en el desarrollo de la región. Recientemente, el acceso a las tecnologías sociales hídricas descentralizadas en las zonas rurales, están mostrando resultados positivos. Sin embargo, aún no es una realidad universal para la población que vive en la región. Por tanto, se concluye que las políticas hídricas siguen siendo insuficientes para hacer frente a los impactos de las sequías. El estudio aporta importantes lecciones históricas para la gestión del agua en la actualidad. Resumo O Semiárido brasileiro, com frequência, é afetado por secas prolongadas. No período 2010-2017, a região semiárida brasileira enfrentou a “Seca do Século”, considerada a pior já registrada na história do País. Este artigo tem o objetivo de fazer uma avaliação histórica das várias fases de políticas hídricas, implementadas na região, com o intuito de promover a convivência com a seca. Com base em investigações históricas documentais e em monitoramento por satélites dos impactos das secas, foram analisadas as ações governamentais, que contribuíram para proporcionar uma maior disponibilidade de agua na região semiárida brasileira, com foco no estudo da efetividade da governança hídrica e nos impactos das tecnologias sociais para armazenamento de agua da chuva, em comunidades rurais difusas. Os resultados da pesquisa evidenciaram que as políticas historicamente implementadas, geralmente em um modelo centralizado, não foram efetivas para desenvolver a região. Recentemente, o acesso às tecnologias sociais hídricas descentralizadas, nas áreas rurais, tem apresentado resultados positivos. Todavia, ainda não é uma realidade universal a toda a população que vive na região. Assim, conclui-se que as políticas hídricas ainda são insuficientes para fazer frente aos impactos das secas. O estudo oferece lições históricas importantes para a governança das águas nos dias atuais.

Carqueja (Baccharis crispa Spreng.) has been primarily used as a medicinal plant around the world. Commercially, the essential oil content of carqueja leaves is the most valuable crop productivity variable. We evaluated the effect of irrigation management in different growing seasons on the essential oil content of carqueja leaves using gas chromatography coupled with mass spectrometry. The experiment was conducted in a greenhouse located in Southern Brazil, where the crop was cultivated for two years in different growing seasons under six irrigation regimes: 25%, 50%, 75%, 100%, 125%, and 150% of the reference crop evapotranspiration (T25, T50, T75, T100, T125, and T150, respectively). A seasonal pattern was observed in the number of metabolites of sesquiterpenes and phenolics in the essential oil extracted from the biomass, this outcome was correlated with irrigation regimes and air temperature. Principal component and hierarchical cluster analyses were used to discriminate the influence of abiotic conditions on secondary metabolite profiles. Spathulenol was the most abundant compound in the essential oils (95.43%) collected during the summer (December&ndash, March) season during the third harvest (H3) at T150. The essential oil content was 8.84% &plusmn, 0.05% and 10.52% &plusmn, 0.10% in summer and winter (June&ndash, September), respectively, with T100 at 45 and 46 days after planting.

Satellite-based rainfall is an alternative source of information for regions such as the Northeast Brazil (NEB) where there are large areas that do not have ground observation stations. In this study, the monthly rainfall derived from the satellite-based rainfall product, Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS v.2), is compared with observation from 21 ground stations in the NEB, for the period 1981–2013. Various metrics based on pairwise comparison were applied to evaluate its performance in estimating rainfall amount and rain detection capability. Results show that the CHIRPS data correlate well with observations for all stations (r = 0.94), but tend to overestimate low and underestimate high rainfall values (>100 mm/month). Although CHIRPS achieves better results during the wet season (March to May; bias = −4.60%), its ability for the rain detection is poor (probability = 0.44). The best global performance was noted in the Cerrado biome (r = 0.93; rain detection = 0.53), but fails to detect rain in other biomes (r = 0.92; rain detection = 0.16). The study concluded that the CHIRPS v.2 dataset can be a useful substitute for rain-gauge precipitation data outside the semiarid NEB.

The Amazon River Basin (ARB) plays an important role in the hydrological cycle at the regional and global scales. According to the Intergovernmental Panel on Climate Change (IPCC), the incidence and severity of droughts could increase in this basin due to human-induced climate change. Therefore, the assessment of the impacts of extreme droughts in the ARB is of vital importance to develop appropriate drought mitigation strategies. The purpose of this study is to provide a comprehensive characterization of dry spells and extreme drought events in terms of occurrence, persistence, spatial extent, severity, and impacts on streamflow and vegetation in the ARB during the period 1901&ndash, 2018. The Standardized Precipitation-Evapotranspiration Index (SPEI) at multiple time scales (i.e., 3, 6, and 12 months) was used as a drought index. A weak basin-wide drying trend was observed, but there was no evidence of a trend in extreme drought events in terms of spatial coverage, intensity, and duration for the period 1901&ndash, 2018. Nevertheless, a progressive transition to drier-than-normal conditions was evident since the 1970s, coinciding with different patterns of coupling between the El Ni&ntilde, o/Southern Oscillation (ENSO) phenomenon and the Pacific Decadal Oscillation (PDO), Atlantic Multidecadal Oscillation (AMO), and Madden&ndash, Julian Oscillation (MJO) as well as an increasing incidence of higher-than-normal surface air temperatures over the basin. Furthermore, a high recurrence of short-term drought events with high level of exposure to long-term drought conditions on the sub-basins Ucayali, Japur&aacute, Caquet&aacute, Jari, Juta&iacute, Mara&ntilde, &oacute, n, and Xingu was observed in recent years. These results could be useful to guide social, economic, and water resource policy decision-making processes in the Amazon basin countries.

Sugarcane (Saccharum officinarum L.) is one of the most important crops in Brazil and its growth and development can be simulated through process-based models. The current study evaluated a model based on the decision support system for the transfer of Agrotechnology DSSAT/CANEGRO to simulate the sugarcane crop productivity in the western region of São Paulo. The DSSAT/CANEGRO model was calibrated using published yield parameters from a selection of five Brazilian sugarcane cultivars, while sugarcane yield data (tons of stems per hectare) from commercial land were used as benchmark data. Other modeling inputs were derived from the primary regional cultivar. The root mean square error (RMSE), Willmott agreement index (d), and mean absolute error (MAE) were used as performance metrics. The DSSAT/CANEGRO model resulted in a good RMSE performance. The productivity estimates were better for the cultivars SP791010 and RB835486, with RMSE equal to 2.27 and 4.48 Mg ha-1, respectively. The comparison between model-based estimates and observed data produced d values in the range from 0.86 to 0.99, and MAE values in the range of 1.84 to 4.22 Mg ha-1.

Microwave-based satellite rainfall products offer an opportunity to assess rainfall-related events for regions where rain-gauge stations are sparse, such as in Northeast Brazil (NEB). Accurate measurement of rainfall is vital for water resource managers in this semiarid region. In this work, the SM2RAIN-CCI rainfall data obtained from the inversion of the microwave-based satellite soil moisture (SM) observations derived from the European Space Agency (ESA) Climate Change Initiative (CCI), and ones from three state-of-the-art rainfall products (Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS), Climate Prediction Center Morphing Technique (CMORPH), and Multi-SourceWeighted-Ensemble Precipitation (MSWEP)) were evaluated against in situ rainfall observations under different bioclimatic conditions at the NEB (e.g., AMZ, Amazônia; CER, Cerrado; MAT, Mata Atlântica; and CAAT, Caatinga). Comparisons were made at daily, 5-day, and 0.25° scales, during the time-span of 1998 to 2015. It was found that 5-day SM2RAIN-CCI has a reasonably good performance in terms of the correlation coefficient over the CER biome (R median: 0.75). In terms of the root mean square error (RMSE), it exhibits better performance in the CAAT biome (RMSE median: 12.57 mm). In terms of bias (B), the MSWEP, SM2RAIN-CCI, and CHIRPS datasets show the best performance in MAT (B median: −8.50%), AMZ (B median: −0.65%), and CER (B median: 0.30%), respectively. Conversely, CMORPH poorly represents the rainfall variability in all biomes, particularly in the MAT biome (R median: 0.43; B median: −67.50%). In terms of detection of rainfall events, all products show good performance (Probability of detection (POD) median > 0.90). The performance of SM2RAIN-CCI suggests that the SM2RAIN algorithm fails to estimate the amount of rainfall under very dry or very wet conditions. Overall, results highlight the feasibility of SM2RAIN-CCI in those poorly gauged regions in the semiarid region of NEB.

Severe droughts have caused serious impact on water supply and agriculture in Sao Francisco River Basin (SFRB), Brazil, especially during the rainy season. Observational evidence suggests that droughts in this region could be driven by some large-scale ocean-atmospheric patterns. This study provides a general description of linkage between the ocean-atmospheric circulation patterns and the droughts during the rainy season (November–December), in the SFRB's upper sub-basins. The NCEP reanalysis I and monthly gridded precipitation dataset of the Global Precipitation Climatology Centre from 1948 to 2010 were used. SPI was used as drought index. All analyses were performed in a domain that covered South America and southern-tropical portions of the Atlantic and Pacific Oceans. Both the wind speed and vertical velocity fields at 200 hPa and specific humidity at 700 hPa were analysed. Results indicate that more extensive short-duration droughts are linked to: (1) El Nino conditions highly concentrated inside the Nino 3.4 region; (2) ITCZ with a northernmost-than-normal position; (3) weaker-than-normal convective activity over the SFRB coupled to a weaker-than-normal upper-level westerly jet stream. For decadal scale, the atmospheric anomalies patterns are best correlated to long-duration extensive droughts than the oceanic anomalies patterns (r = −0.84 and −0.14, respectively). This suggests that droughts in SFRB are strongly dependent on large-scale moisture transport and upper-level atmospheric circulation.

La cuenca del lago de Valencia (CELV) es la cuenca endorreica de mayor tamaño en Venezuela. Por su elevada densidad poblacional e industrial es susceptible a los extremos pluviométricos. Se sabe que el fenómeno ENOA (El Niño-Oscilación Austral) modula las lluvias en el territorio venezolano, pero no se ha explorado su incidencia en detalle en la CELV. En este estudio se analiza la tendencia espacial y temporal de la precipitación estacional y se explora la asociación entre la ocurrencia de meses con extremos pluviométricos y las fases de ENOA (El Niño, La Niña, neutro) en la CELV. Se seleccionaron ocho estaciones climáticas con buena calidad de registros. Los periodos 1934-2005 y 1966- 1992 se adoptan para los análisis a escalas local y regional. Se identificaron los meses de la temporada seca y húmeda. En cada estación se calculó la precipitación acumulada estacional y se evaluó su tendencia de largo plazo utilizando la prueba de Mann-Kendall. Se categorizó la precipitación mensual local y estacional en extrema seca (ES), no extrema (NE) y extrema húmeda (EH), usando como umbrales los percentiles 10 y 90. Se analizó la ocurrencia probabilística espacial y simultaneidad de un mes ES, NE y EH, según la temporada y fases de ENOA. La asociación entre ENOA y la precipitación estacional se explora con una prueba Chi-Cuadrado. Se encontró lo siguiente: no existen tendencias locales de largo plazo en la precipitación total estacional; la ocurrencia de extremos pluviométricos estacionales está parcialmente asociada con los eventos El Niño/La Niña; la incidencia de extremos pluviométricos podría estar vinculada con factores climáticos locales.

Northeast Brazil (NEB) has recently experienced one of its worst droughts in the last decades, with large losses on rainfed agriculture. Soil moisture is the main variable to monitor agricultural drought. The remote sensing approach for drought monitoring has been enriched with the launch of the Soil Moisture and Ocean Salinity (SMOS) in November 2009 by European Space Agency (ESA). In this work, the Soil Water Deficit Index (SWDI) was calculated using the SMOS L2 soil moisture in the NEB. The SMOS-derived SWDI data (SWDIS) were evaluated against the atmospheric water deficit (AWD) calculated from in situ observations. Comparisons were made at seven-day and 0.25° scales, over the time-span of June 2010 to December 2013. It was found that the SWDIS has a reasonably good overall performance in terms of the drought-weeks detection (skill = 0.986) and capture of the upper soil moisture temporal dynamic (r = 0.652), implying that the SWDIS could be used to track agricultural droughts. Furthermore, SWDIS shows poor performance at sites located in mountains regions affected by severe droughts (−0.10 ≤ r ≤ 0.10). It is also noted that the vegetal cover/use, climate regime, and soil texture have little influence on the AWD-SWDIS coupling.

Baccharis trimera (Less.) DC (E1) and Baccharis crispa Spreng. (E2) possess potential antimicrobial and anti-inflammatory properties. Qualitative and quantitative information on seed germination on these species is scarce. The objective of this investigation was to establish a protocol for evaluating seed germination of E1 and E2 and to analice the scoring and curve fitting by the Germinator package, for different periods of germination were between 0.93 and 0.99. Both species showed differences in germinability and mean germination time, 27 days for E1 and 20 days for E2. The germination dispersion showed that E1 germination was homogeneous, with differences in growth pattern, whereas the results on germination of E2. The mean speed of germination determined with the experimental data was close to the values obtained by the Germinator package, with a maximum germination of more than 34%, proving that the software was efficient for evaluating germination.