Spatial variability of the rainfall erosive potential in the State of Mato Grosso do Sul, Brazil
Information about rainfall erosivity is important during soil and water conservation planning. Thus, the spatial variability of rainfall erosivity of the state Mato Grosso do Sul was analyzed using ordinary kriging interpolation. For this, three pluviograph stations were used to obtain the regression equations between the erosivity index and the rainfall coefficient EI30. The equations obtained were applied to 109 pluviometric stations, resulting in EI30 values. These values were analyzed from geostatistical technique, which can be divided into: descriptive statistics, adjust to semivariogram, cross-validation process and implementation of ordinary kriging to generate the erosivity map.Highest erosivity values were found in central and northeast regions of the State, while the lowest values were observed in the southern region. In addition, high annual precipitation values not necessarily produce higher erosivity values.
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Associação Brasileira de Engenharia Agrícola
2012
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oai:scielo:S0100-691620120001000082012-04-18Spatial variability of the rainfall erosive potential in the State of Mato Grosso do Sul, BrazilOliveira,Paulo T. S.Rodrigues,Dulce B. B.Sobrinho,Teodorico A.Carvalho,Daniel F. dePanachuki,Elói water erosion rainfall erosivity index geostatistics Information about rainfall erosivity is important during soil and water conservation planning. Thus, the spatial variability of rainfall erosivity of the state Mato Grosso do Sul was analyzed using ordinary kriging interpolation. For this, three pluviograph stations were used to obtain the regression equations between the erosivity index and the rainfall coefficient EI30. The equations obtained were applied to 109 pluviometric stations, resulting in EI30 values. These values were analyzed from geostatistical technique, which can be divided into: descriptive statistics, adjust to semivariogram, cross-validation process and implementation of ordinary kriging to generate the erosivity map.Highest erosivity values were found in central and northeast regions of the State, while the lowest values were observed in the southern region. In addition, high annual precipitation values not necessarily produce higher erosivity values.info:eu-repo/semantics/openAccessAssociação Brasileira de Engenharia AgrícolaEngenharia Agrícola v.32 n.1 20122012-02-01info:eu-repo/semantics/articletext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162012000100008en10.1590/S0100-69162012000100008 |
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Oliveira,Paulo T. S. Rodrigues,Dulce B. B. Sobrinho,Teodorico A. Carvalho,Daniel F. de Panachuki,Elói |
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Oliveira,Paulo T. S. Rodrigues,Dulce B. B. Sobrinho,Teodorico A. Carvalho,Daniel F. de Panachuki,Elói Spatial variability of the rainfall erosive potential in the State of Mato Grosso do Sul, Brazil |
author_facet |
Oliveira,Paulo T. S. Rodrigues,Dulce B. B. Sobrinho,Teodorico A. Carvalho,Daniel F. de Panachuki,Elói |
author_sort |
Oliveira,Paulo T. S. |
title |
Spatial variability of the rainfall erosive potential in the State of Mato Grosso do Sul, Brazil |
title_short |
Spatial variability of the rainfall erosive potential in the State of Mato Grosso do Sul, Brazil |
title_full |
Spatial variability of the rainfall erosive potential in the State of Mato Grosso do Sul, Brazil |
title_fullStr |
Spatial variability of the rainfall erosive potential in the State of Mato Grosso do Sul, Brazil |
title_full_unstemmed |
Spatial variability of the rainfall erosive potential in the State of Mato Grosso do Sul, Brazil |
title_sort |
spatial variability of the rainfall erosive potential in the state of mato grosso do sul, brazil |
description |
Information about rainfall erosivity is important during soil and water conservation planning. Thus, the spatial variability of rainfall erosivity of the state Mato Grosso do Sul was analyzed using ordinary kriging interpolation. For this, three pluviograph stations were used to obtain the regression equations between the erosivity index and the rainfall coefficient EI30. The equations obtained were applied to 109 pluviometric stations, resulting in EI30 values. These values were analyzed from geostatistical technique, which can be divided into: descriptive statistics, adjust to semivariogram, cross-validation process and implementation of ordinary kriging to generate the erosivity map.Highest erosivity values were found in central and northeast regions of the State, while the lowest values were observed in the southern region. In addition, high annual precipitation values not necessarily produce higher erosivity values. |
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Associação Brasileira de Engenharia Agrícola |
publishDate |
2012 |
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http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162012000100008 |
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1756388948138000384 |