2017
DOI: 10.1590/0102-77863220006
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Padrões de Variabilidade de Vazão de Rios nas Principais Bacias Brasileiras e Associação com Índices Climáticos

Abstract: Resumo O objetivo deste estudo é caracterizar os principais padrões de variabilidade espaço-temporal de vazões e relacioná-los com padrões climáticos que podem afetar tal variável. Para tanto, foi aplicada a Análise de Componentes Principais sobre o conjunto de dados de vazão de rios brasileiros, onde cada Componente Principal encontrado se associa a um modo de variabilidade de vazão. A variabilidade temporal dos seis primeiros modos (que explicam mais de 80% da variabilidade total de vazão) foi comparada com … Show more

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Cited by 20 publications
(12 citation statements)
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“…The PCA is a well-established linear statistical method frequently employed to analyze hydroclimatological data, such as streamflows and rainfall [5,67,70,71]. Its objective is to reduce the size of the time series to some main orthogonal principal components (PCs) that explain most of the variability of the original variables [72] with minimum loss of information [73].…”
Section: Principal Component Analysismentioning
confidence: 99%
See 1 more Smart Citation
“…The PCA is a well-established linear statistical method frequently employed to analyze hydroclimatological data, such as streamflows and rainfall [5,67,70,71]. Its objective is to reduce the size of the time series to some main orthogonal principal components (PCs) that explain most of the variability of the original variables [72] with minimum loss of information [73].…”
Section: Principal Component Analysismentioning
confidence: 99%
“…The coherence between the PC1 for ARB (PRB) and PRP was significant on the 2-8-year time scale from 1985 to 2011 with a phase difference from 0 • to 10 • (0 • to 45 • ) (Figure 10a,c). For this scale, the 10 • (45 • ) difference indicated that the influence of PRP on streamflows was recorded with 1-3 (3)(4)(5)(6)(7)(8)(9)(10)(11)(12) month lags, whereas 0 • indicated that both time series were simultaneously related. On the 10-14 (8)(9)(10)(11)(12)(13)(14) year decadal scale, the indices presented −45 • (0 • and 10 • ) phase difference, which implies that the influence of PRP on streamflows of ARB (PRB) was reflected within a 15-21 (3-5) month time interval.…”
Section: Wavelet Coherence and Phase Differencementioning
confidence: 99%
“…ITCZ is the main large-scale atmospheric phenomenon influencing the rains in the equatorial Atlantic region, with an important role in the short rainy season in Northeastern Brazil, especially from December to May, when it is positioned further south (Reboita et al, 2010); as a consequence, it is possible to observe that the highest values of NEA are presented in this period, according to Figure 2c. The ITCZ also influences the Northern region of Brazil, where the humid air brought by it undergoes orographic lifting on the Andes, supporting convective activity and precipitation with maxims in summer and austral autumn (Capozzoli et al, 2017;Reboita et al, 2010), when the NEA values are higher (see Figure 2d). The Southeast and Midwest regions have a well-defined rainfall system from October to February -a Silva et al…”
Section: Study Areasmentioning
confidence: 88%
“…Por meio de consultas em sites governamentais obtiveram-se os dados necessários para a realização da pesquisa. Os dados hidrológicos da Usina de Sobradinho - (Capozzoli, et al, 2017). Os dados de velocidade de vento foram obtidos no Instituto Nacional de Pesquisas Espaciais (INPE), no Sistema de Organização Nacional de Dados Ambientais (SONDA) que dispõe de uma base de dados dos recursos de energia solar e eólica para algumas regiões no Brasil.…”
Section: Metodologia E Dadosunclassified