Estimating soil loss by laminar erosion using precision agriculture computational tools
ABSTRACT The study aimed to identify and evaluate the spatial variability in laminar erosion in areas using precision agriculture tools. Soil data from three properties in the western region of Paraná state, Brazil, were used: one in the municipality of Céu Azul (area A) and two in Serranópolis do Iguaçu (areas B and C). To identify discrepant data (outliers), analysis of the dispersion of quartiles was performed using a box-plot graph. Data normality was verified using the Kolmogorov-Smirnov test. A spatial analysis was performed using AgDataBox-Map software. The parameters of the universal soil loss equation were estimated and used with map algebra to produce a model to identify areas susceptible to erosion. Area A (soil loss estimate = 0-200 t ha-1 per year) presented greater susceptibility to erosion than areas B and C (soil loss estimate = 0-150 t ha-1 per year); however, all areas had a low susceptibility to erosion.
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Departamento de Engenharia Agrícola - UFCG
2022
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oai:scielo:S1415-436620220012009072022-08-03Estimating soil loss by laminar erosion using precision agriculture computational toolsKrug,Evelin T. S.Gomes,Glaucio J.Souza,Eduardo G. deGebler,LucianoSobjak,RicardoBazzi,Claudio L. precision agriculture thematic maps geostatistics universal soil loss equation kriging ABSTRACT The study aimed to identify and evaluate the spatial variability in laminar erosion in areas using precision agriculture tools. Soil data from three properties in the western region of Paraná state, Brazil, were used: one in the municipality of Céu Azul (area A) and two in Serranópolis do Iguaçu (areas B and C). To identify discrepant data (outliers), analysis of the dispersion of quartiles was performed using a box-plot graph. Data normality was verified using the Kolmogorov-Smirnov test. A spatial analysis was performed using AgDataBox-Map software. The parameters of the universal soil loss equation were estimated and used with map algebra to produce a model to identify areas susceptible to erosion. Area A (soil loss estimate = 0-200 t ha-1 per year) presented greater susceptibility to erosion than areas B and C (soil loss estimate = 0-150 t ha-1 per year); however, all areas had a low susceptibility to erosion.info:eu-repo/semantics/openAccessDepartamento de Engenharia Agrícola - UFCGRevista Brasileira de Engenharia Agrícola e Ambiental v.26 n.12 20222022-12-01info:eu-repo/semantics/articletext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662022001200907en10.1590/1807-1929/agriambi.v26n12p907-914 |
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Krug,Evelin T. S. Gomes,Glaucio J. Souza,Eduardo G. de Gebler,Luciano Sobjak,Ricardo Bazzi,Claudio L. |
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Krug,Evelin T. S. Gomes,Glaucio J. Souza,Eduardo G. de Gebler,Luciano Sobjak,Ricardo Bazzi,Claudio L. Estimating soil loss by laminar erosion using precision agriculture computational tools |
author_facet |
Krug,Evelin T. S. Gomes,Glaucio J. Souza,Eduardo G. de Gebler,Luciano Sobjak,Ricardo Bazzi,Claudio L. |
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Krug,Evelin T. S. |
title |
Estimating soil loss by laminar erosion using precision agriculture computational tools |
title_short |
Estimating soil loss by laminar erosion using precision agriculture computational tools |
title_full |
Estimating soil loss by laminar erosion using precision agriculture computational tools |
title_fullStr |
Estimating soil loss by laminar erosion using precision agriculture computational tools |
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Estimating soil loss by laminar erosion using precision agriculture computational tools |
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estimating soil loss by laminar erosion using precision agriculture computational tools |
description |
ABSTRACT The study aimed to identify and evaluate the spatial variability in laminar erosion in areas using precision agriculture tools. Soil data from three properties in the western region of Paraná state, Brazil, were used: one in the municipality of Céu Azul (area A) and two in Serranópolis do Iguaçu (areas B and C). To identify discrepant data (outliers), analysis of the dispersion of quartiles was performed using a box-plot graph. Data normality was verified using the Kolmogorov-Smirnov test. A spatial analysis was performed using AgDataBox-Map software. The parameters of the universal soil loss equation were estimated and used with map algebra to produce a model to identify areas susceptible to erosion. Area A (soil loss estimate = 0-200 t ha-1 per year) presented greater susceptibility to erosion than areas B and C (soil loss estimate = 0-150 t ha-1 per year); however, all areas had a low susceptibility to erosion. |
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Departamento de Engenharia Agrícola - UFCG |
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2022 |
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http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662022001200907 |
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