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Lima,Cleene A. de; Palácio,Helba A. de Q.; Andrade,Eunice M. de; Santos,Julio C. N. dos; Brasil,Paulilo P.. |
The characteristics of rainfall can provide important information for management and land use may also minimize the water erosion problems. This study was carried out to evaluate soil and water loss in erosion plots with different coverage, and the interference of natural rainfall characteristics on these processes. The experiment was carried out during the rainy season in the years of 2009 and 2010, on three erosion plots, each of 20 m², and under different land use conditions: native 'caatinga', thinned 'caatinga' and natural herbaceous cover. The rainfall was classified into three different rainfall patterns, characterized as early, intermediate and late. The predominant rainfall pattern for the two years under study was early rainfall with 47.6%,... |
Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Rainfall intensity; Erosivity; Water erosion. |
Ano: 2013 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662013001100014 |
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Ribeiro Filho,Jacques C.; Lemos Filho,Luis C. de A.; Santos,Julio C. N. dos; Brasil,José B.; Palácio,Helba A. de Q.. |
ABSTRACT Information on hydrology, and vegetation distribution is essential for the development of techniques and strategies to cope with droughts in semi-arid environments. The objective of this study was to evaluate the partitioning of gross rainfall into throughfall, stemflow, and interception loss in the Brazilian Northeastern Atlantic Forest, and its correlations with rainfall characteristics. The study was conducted in the Bica watershed, in Portalegre, state of Rio Grande do Norte, Brazil. The work was carried out in 2017, with monitoring of the throughfall, stemflow, and interception loss in an area of 10 × 20 m. Total rainfall depths (TRD) and wind speed were measured, and the evapotranspiration (ET0) was estimated. Based on this information,... |
Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Caatinga; Hydrology; Semi-arid; Principal component analysis. |
Ano: 2019 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662019000100021 |
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