The objective of this study was to evaluate the annual standardized precipitation index (SPI) obtained from the DrinC software based on multivariate analysis in the identification of rainfall and drought extremes in the State of Alagoas and its relationship with El Niño-Southern Oscillation. Monthly rainfall data from 1960 to 2016 from National Water Agency were analysed. Annual SPI (SPI-12) has been designed for comparison with ENSO phases via Oceanic Niño Index for 3.4 region and in identifying climate extremes in the State of Alagoas. The principal component analysis and cluster analysis techniques were applied to the rainfall series of SPI-12. Extreme events were identified in both rainy and drought periods according to SPI-12, and were associated with the ENSO phases (El Niño, La Niña, and Neutral). The first four principal components explained 46.68% of the variance. Our findings are crucial for agriculture and civil defence since northeastern Brazil has several areas of risk and social vulnerability.

Resumo A escassez de dados pluviográficos em Alagoas, similar em muitas regiões do país, faz com que utilizem equações de regressão obtidas em outras regiões do Brasil para calcular o fator R da Equação Universal de Perda de Solo. O estudo tem por objetivos: i) definir uma equação para estimar a erosividade das chuvas baseada no índice EI30 e no coeficiente de chuva Rc, ii) validar o método de imputação de dados para a chuva e erosividade e iii) estimar espacialmente a erosividade nos períodos chuvoso, seco e transição para Alagoas. Utilizaram-se dados pluviométricos mensais de 54 estações no período (1960-2016). A equação utilizada apresentou correlação significativa entre os dados observados e estimados, de acordo com os coeficientes r (93%), R2 (87%) e RMSE (775,2 MJ.mm.ha−1.h−1.ano−1). A Krigagem Ordinária foi o melhor interpolador espacial. A isoerosividade mensal mostrou que os maiores índices de EI30 ocorreram entre abril e julho, período coincidente com a quadra chuvosa do estado. Na erosividade anual, os maiores registros estão situados no Leste Alagoano, próximas ao litoral. Destaque para as estações Satuba, Maceió, São Luiz do Quitunde e Flexeiras, categorizadas entre moderada e forte. Estes resultados auxiliarão no planejamento de práticas conservacionistas, principalmente em áreas de vulnerabilidade.

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The objectives of the study are: i) to evaluate the climatology of rain in Maceió based on observed data, with emphasis on climatic and environmental aspects and ii) to validate the precipitation product for the municipality. Data from 1979 to 2013 of the precipitation product CHELSA (Climatologies at High Resolution for the Earth's Land Surface Areas) were validated by rainfall data from the National Water Agency (NWA) from 1960 to 2016. Statistical indicators showed a high coefficient of determination and linear correlation between CHELSA and observed data (R2 = 0.80; r = 0.89) and the smallest errors (SEE = 6.58 mm and RMSE = 18.76 mm), therefore the CHELSA product can be applied in the region. The time series presented a period 1 (P1) - (1960 to 1989) with rainfall above the historical average and a period 2 (P2) - (1990 to 2016) with a significant reduction in rainfall. Observed data versus climatological normals showed a significant decrease in normal 1 (1961-1990) in the rainy season, while in relation to normal 2 (1981-2010) there was an increase in the months of February, March and April (between 10 to 20%) and October and December (between 5 to 15%). The spatial distribution of monthly rainfall via the CHELSA product showed the formation of a pluviometric gradient between the coast and the upper part of Maceió. The topography influences the rainfall regime in neighborhoods belonging to the administrative regions (AR) - (R4, R5 and R6) with the highest rainfall records. The ENOS phases are directly responsible for the variability of interannual rain, while the decadal variability corresponded to the PDO phase change and changes in land use and occupation in Maceió.

The aim of the study was to evaluate the reported cases of dengue in the State of Alagoas via applied statistics and geospatialization.Dengue data were obtained from the DATASUS system between 2000 and 2015. The time series was submitted to descriptive and exploratory statistics and the Pettitt test. In the dengue case maps, the Spline method via QGis version 3.4 was used. In descriptive statistics, only 10 municipalities were evaluated based on the largest case records. All municipalities were above the average of dengue cases in 2010, the year of the biggest recent flood in the state. The boxplot pointed out that all 10 municipalities were positive asymmetric in a few months for dengue cases, the exception was Delmiro Gouveia. The Pettitt test identified biannual cycles (2006/2007 and 2009/2010) associated with the phases of ENSO (El Niño and La Niña) in the moderate category, followed by the months of January, February, April and December, corresponding to the performance of some systems synoptics. In the mapping of annual cases of dengue, the highest records occurred in the Agreste and East Alagoas. Geospatialization and applied statistics are efficient in the spatiotemporal evaluation of dengue cases in Alagoas.