Analysis Of Rainfall Homogeneous Areas In Time Series Of Precipitation In The State Of Bahia, Brazil [análise De Zonas Homogêneas Em Séries Temporais De Precipitação No Estado Da Bahia]

The aim of this study was to identify rainfall homogeneous areas in the State of Bahia, Brazil and analyze the climatic conditions of each area for the period between 1981 and 2010. It was applied a data mining technique, clustering (grouping of data), by using the k-means algorithm for transforming time series of precipitation in five rainfall homogeneous areas, in response to topography, maritime dimension, and weather systems operating in the region of study. Data of average monthly rainfall of 92 meteorological stations were used. The results indicate that the driest areas are situated in the central part of the state, from north to south, mainly in the north with the lowest annual volumes, around 480 mm. The area located in the north of the state contrasts with that one located on the coast, where the largest volumes of annual rainfall of the study were observed (approximately 1.380 mm). The high rainfall variability occurs in almost all areas, especially in two of those of semiarid ones with Coefficients of Variation (CV) reaching 42 and 28%. This characteristic differs from the area belonging to the coastal area, which presents regular rainfall during all the year and a CV of 15%. The rainy and dry seasons are well defined. Precipitation values of the rainy season accounts for about 81% of the annual total, with emphasis on the zones located in the central-west and west of the state with 95 and 96% of the annual total.722192198(2011) ANA-Agência Nacional das Águas, , http://hidroweb.ana.gov.br, Disponível em, Acesso em: agoAndré, R.G.B., Marques, V.S., Pinheiro, F.M.A., Ferraudo, A.S., Identificação de regiões pluviometricamente homogêneas no estado do Rio de Janeiro, utilizando valores mensais (2008) Revista Brasileira de Meteorologia, 23, pp. 501-509. , DOI: 10.1590/S0102-77862008000400009Bhaktikul, K., Anujit, R., Toim, J., Estimation of crop coefficient of corn (Kccorn) under climate change scenarios using data mining technique (2012) Environment Asia, 5, pp. 56-62Boschi, R.S., Oliveira, S.R.M., Assad, E.D., Técnicas de mineração de dados para análise pluvial decenal do Rio Grande do Sul (2011) Engenharia Agrícola, 31, pp. 1189-1201. , DOI: 10.1590/S0100-69162011000600016(1984) Departamento Nacional de Águas e Energia Elétrica-DNAEE, , BRASIL, Divisão de Controle de Recursos Hídricos. Sistemática para análise de consistência e homogeneização de dados pluviométricos, BrasíliaCavalcanti, I.F.A., Ferreira, N.J., Dias, M.A.F., Justi, M.G.A., (2009) Terra e clima no Brasil, p. 464. , São Paulo: Editora Oficina de TextosChapman, P., Clinton, J., Kerber, R., Khabaza, T., Reinartz, T., Shearer, C., Wirth, R., (2000) CRISP-DM 1.0: Step-by-step data mining guide, p. 78. , Illinois: SPSSFayyad, U., Piatetsky-Shapiro, G., Smyth, P., From data mining to knowledge discovery: An overview (1996) Advances in knowledge discovery and data mining, pp. 1-34. , eds. U. M. Fayyad et al., AAAI/MIT Press. Menlo Park: American Association for Artificial Intelligence, CalifFechine, J.A.L., Galvincio, J.D., Agrupamento da precipitação mensal da bacia hidrográfica do rio Brígida-PE, através da multivariada (2008) Revista Brasileira de Geografia Física, 1, pp. 39-46Han, J., Kamber, M., (2011) Data mining: Concepts and techniques, p. 770. , San Francisco: Morgan Kaufmann Publishers(2012) Clima da Bahia, , www.ibge.gov.br, IBGE-Instituto Brasileiro de Geografia e Estatística, Disponível em, Acesso em: julKousky, V.E., (1979) Frontal influences on northeast Brazil, p. 16. , São Paulo: INPE, DOI: 10.1175/1520-0493(1979)1072.0.CO;2Kumar, D.N., Dhanya, M.C.T., Data mining and its applications for modeling rainfall extremes (2009) Journal of Hydraulic Engineering, 15, pp. 25-51. , DOI: 10.1080/09715010.2009.10514967Marcuzzo, F.F.N., Andrade, L.R., Melo, D.C.R., Métodos de interpolação matemática no mapeamento de chuvas no estado do Mato Grosso (2011) Revista Brasileira de Geografia Física, 4, pp. 793-804Molion, L.C.B., Bernardo, S.O., Uma revisão da dinâmica das chuvas no nordeste brasileiro (2002) Revista Brasileira de Meteorologia, 17, pp. 1-10Rezende, S.O., Pugliesi, J., Melanda, E.A., Paula, M.F., Mineração de dados (2005) Sistemas inteligentes, p. 527. , Fundamentos e aplicações. Barueri: Manole LtdaRomani, L.A.S., Ávila, A.M.H., Zullo, J.J., Traina, C.J., Traina, A.J.M., Mining relevant and extreme patterns on climate time series with CLIPSMiner (2010) Journal of Information and Data Management, 1, pp. 245-260Silva, V.P.R., Pereira, E.R.R., Almeida, R.S.R., Estudo da variabilidade anual e intra-anual da precipitação na região nordeste do Brasil (2012) Revista Brasileira de Meteorologia, 27, pp. 163-172. , DOI: 10.1590/S0102-77862012000200005Souza, J.L., Amorim, R.F.C., Carvalho, S.M.R., Pereira, J.O., Curi, P.R.C., Agrupamento de estações pluviométricas do estado de Alagoas, utilizando-se análise multivariada (1992) Revista Brasileira de Meteorologia, 7, pp. 603-612(2011) Sistemas de dados estatísticos, , http://www.sei.ba.gov.br/side/consulta, SUPERINTENDÊNCIA DE ESTUDOS ECONÔMICOS E SOCIAIS DA BAHIA (SEI), 2000. Disponível em, Acesso em: maioTanajura, C.A.S., Genz, F., Araújo, H.A., Mudanças climáticas e recursos hídricos na Bahia: Validação da simulação do clima presente do HADRM3P e comparação com os cenários A2 e B2 para 2070-2100 (2010) Revista Brasileira de Meteorologia, 25, pp. 345-358. , DOI: 10.1590/S0102-77862010000300006Teixeira, A.H.C., Moura, M.S.B., Angelotti, F., (2010) Cultivo da mangueira, 2. , EMBRAPA SEMIÁRIDO-Sistema de ProduçãoThornthwaite, C.W., Mather, J.R., The water balance (1955) Climatology, 8, pp. 1-40. , DOI: 10.1097/00010694-195904000-00024Witten, I.H., Frank, E., Hall, M.A., (2011) Data mining: Practical machine learning tools and techniques, p. 629. , 3rd ed. San Francisco: Morgan Kaufmann, DOI: 10.1145/507338.50735

Neutron probe calibration correction by temporal stability parameters of soil water content probability distribution Correção da calibração de sondas de nêutrons por meio de parâmetros de estabilidade temporal da distribuição de probabilidade do conteúdo de água no solo

A neutron probe calibration correction is proposed in order to reduce soil water content variability, assumed to be a consequence of improper calibrations relations. The time stability of spatially measured soil water content data is used to correct the intercepts of linear calibration relations. This procedure reduced the coefficients of variation of soil water content data from 4 to less than 2% in a Rhodic Kanhapludalf.<br>É proposta uma correção para a calibração de sondas de nêutrons para reduzir a variabilidade de dados do conteúdo de água no solo, suposta como conseqüência de relações de calibração impróprias. A estabilidade temporal de dados espaciais de conteúdo de água no solo é usada para corrigir os coeficientes lineares de curvas de calibração. Esse procedimento reduziu coeficientes de variação de medidas de umidade do solo de 4 para valores menores que 2% em uma Terra Roxa Estruturada

Implementation of a Brazilian Cardioprotective Nutritional (BALANCE) Program for improvement on quality of diet and secondary prevention of cardiovascular events: A randomized, multicenter trial

Background: Appropriate dietary recommendations represent a key part of secondary prevention in cardiovascular disease (CVD). We evaluated the effectiveness of the implementation of a nutritional program on quality of diet, cardiovascular events, and death in patients with established CVD. Methods: In this open-label, multicenter trial conducted in 35 sites in Brazil, we randomly assigned (1:1) patients aged 45 years or older to receive either the BALANCE Program (experimental group) or conventional nutrition advice (control group). The BALANCE Program included a unique nutritional education strategy to implement recommendations from guidelines, adapted to the use of affordable and regional foods. Adherence to diet was evaluated by the modified Alternative Healthy Eating Index. The primary end point was a composite of all-cause mortality, cardiovascular death, cardiac arrest, myocardial infarction, stroke, myocardial revascularization, amputation, or hospitalization for unstable angina. Secondary end points included biochemical and anthropometric data, and blood pressure levels. Results: From March 5, 2013, to Abril 7, 2015, a total of 2534 eligible patients were randomly assigned to either the BALANCE Program group (n = 1,266) or the control group (n = 1,268) and were followed up for a median of 3.5 years. In total, 235 (9.3%) participants had been lost to follow-up. After 3 years of follow-up, mean modified Alternative Healthy Eating Index (scale 0-70) was only slightly higher in the BALANCE group versus the control group (26.2 ± 8.4 vs 24.7 ± 8.6, P <.01), mainly due to a 0.5-serving/d greater intake of fruits and of vegetables in the BALANCE group. Primary end point events occurred in 236 participants (18.8%) in the BALANCE group and in 207 participants (16.4%) in the control group (hazard ratio, 1.15; 95% CI 0.95-1.38; P =.15). Secondary end points did not differ between groups after follow-up. Conclusions: The BALANCE Program only slightly improved adherence to a healthy diet in patients with established CVD and had no significant effect on the incidence of cardiovascular events or death. © 2019 The Author