Mapping of use and occupation of the soil and irrigation water quality in the city of Salto do Lontra-Paraná, Brazil
Autor(a) principal: | |
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Data de Publicação: | 2013 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Engenharia Agrícola |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162013000500014 |
Resumo: | The objective of this study consisted on mapping the use and soil occupation and evaluation of the quality of irrigation water used in Salto do Lontra, in the state of Paraná, Brazil. Images of the satellite SPOT-5 were used to perform the supervised classification of the Maximum Likelihood algorithm - MAXVER, and the water quality parameters analyzed were pH, EC, HCO3-, Cl-, PO4(3-), NO3-, turbidity, temperature and thermotolerant coliforms in two distinct rainfall periods. The water quality data were subjected to statistical analysis by the techniques of PCA and FA, to identify the most relevant variables in assessing the quality of irrigation water. The characterization of soil use and occupation by the classifier MAXVER allowed the identification of the following classes: crops, bare soil/stubble, forests and urban area. The PCA technique applied to irrigation water quality data explained 53.27% of the variation in water quality among the sampled points. Nitrate, thermotolerant coliforms, temperature, electrical conductivity and bicarbonate were the parameters that best explained the spatial variation of water quality. |
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Engenharia Agrícola |
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Mapping of use and occupation of the soil and irrigation water quality in the city of Salto do Lontra-Paraná, BrazilGlobal Navigation Satellite Systems - GNSSGeographic Information Systems - GISirrigationThe objective of this study consisted on mapping the use and soil occupation and evaluation of the quality of irrigation water used in Salto do Lontra, in the state of Paraná, Brazil. Images of the satellite SPOT-5 were used to perform the supervised classification of the Maximum Likelihood algorithm - MAXVER, and the water quality parameters analyzed were pH, EC, HCO3-, Cl-, PO4(3-), NO3-, turbidity, temperature and thermotolerant coliforms in two distinct rainfall periods. The water quality data were subjected to statistical analysis by the techniques of PCA and FA, to identify the most relevant variables in assessing the quality of irrigation water. The characterization of soil use and occupation by the classifier MAXVER allowed the identification of the following classes: crops, bare soil/stubble, forests and urban area. The PCA technique applied to irrigation water quality data explained 53.27% of the variation in water quality among the sampled points. Nitrate, thermotolerant coliforms, temperature, electrical conductivity and bicarbonate were the parameters that best explained the spatial variation of water quality.Associação Brasileira de Engenharia Agrícola2013-10-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162013000500014Engenharia Agrícola v.33 n.5 2013reponame:Engenharia Agrícolainstname:Associação Brasileira de Engenharia Agrícola (SBEA)instacron:SBEA10.1590/S0100-69162013000500014info:eu-repo/semantics/openAccessWrublack,Suzana C.Mercante,EriveltoVilas Boas,Marcio A.eng2013-11-21T00:00:00Zoai:scielo:S0100-69162013000500014Revistahttp://www.engenhariaagricola.org.br/ORGhttps://old.scielo.br/oai/scielo-oai.phprevistasbea@sbea.org.br||sbea@sbea.org.br1809-44300100-6916opendoar:2013-11-21T00:00Engenharia Agrícola - Associação Brasileira de Engenharia Agrícola (SBEA)false |
dc.title.none.fl_str_mv |
Mapping of use and occupation of the soil and irrigation water quality in the city of Salto do Lontra-Paraná, Brazil |
title |
Mapping of use and occupation of the soil and irrigation water quality in the city of Salto do Lontra-Paraná, Brazil |
spellingShingle |
Mapping of use and occupation of the soil and irrigation water quality in the city of Salto do Lontra-Paraná, Brazil Wrublack,Suzana C. Global Navigation Satellite Systems - GNSS Geographic Information Systems - GIS irrigation |
title_short |
Mapping of use and occupation of the soil and irrigation water quality in the city of Salto do Lontra-Paraná, Brazil |
title_full |
Mapping of use and occupation of the soil and irrigation water quality in the city of Salto do Lontra-Paraná, Brazil |
title_fullStr |
Mapping of use and occupation of the soil and irrigation water quality in the city of Salto do Lontra-Paraná, Brazil |
title_full_unstemmed |
Mapping of use and occupation of the soil and irrigation water quality in the city of Salto do Lontra-Paraná, Brazil |
title_sort |
Mapping of use and occupation of the soil and irrigation water quality in the city of Salto do Lontra-Paraná, Brazil |
author |
Wrublack,Suzana C. |
author_facet |
Wrublack,Suzana C. Mercante,Erivelto Vilas Boas,Marcio A. |
author_role |
author |
author2 |
Mercante,Erivelto Vilas Boas,Marcio A. |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Wrublack,Suzana C. Mercante,Erivelto Vilas Boas,Marcio A. |
dc.subject.por.fl_str_mv |
Global Navigation Satellite Systems - GNSS Geographic Information Systems - GIS irrigation |
topic |
Global Navigation Satellite Systems - GNSS Geographic Information Systems - GIS irrigation |
description |
The objective of this study consisted on mapping the use and soil occupation and evaluation of the quality of irrigation water used in Salto do Lontra, in the state of Paraná, Brazil. Images of the satellite SPOT-5 were used to perform the supervised classification of the Maximum Likelihood algorithm - MAXVER, and the water quality parameters analyzed were pH, EC, HCO3-, Cl-, PO4(3-), NO3-, turbidity, temperature and thermotolerant coliforms in two distinct rainfall periods. The water quality data were subjected to statistical analysis by the techniques of PCA and FA, to identify the most relevant variables in assessing the quality of irrigation water. The characterization of soil use and occupation by the classifier MAXVER allowed the identification of the following classes: crops, bare soil/stubble, forests and urban area. The PCA technique applied to irrigation water quality data explained 53.27% of the variation in water quality among the sampled points. Nitrate, thermotolerant coliforms, temperature, electrical conductivity and bicarbonate were the parameters that best explained the spatial variation of water quality. |
publishDate |
2013 |
dc.date.none.fl_str_mv |
2013-10-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162013000500014 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162013000500014 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/S0100-69162013000500014 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Associação Brasileira de Engenharia Agrícola |
publisher.none.fl_str_mv |
Associação Brasileira de Engenharia Agrícola |
dc.source.none.fl_str_mv |
Engenharia Agrícola v.33 n.5 2013 reponame:Engenharia Agrícola instname:Associação Brasileira de Engenharia Agrícola (SBEA) instacron:SBEA |
instname_str |
Associação Brasileira de Engenharia Agrícola (SBEA) |
instacron_str |
SBEA |
institution |
SBEA |
reponame_str |
Engenharia Agrícola |
collection |
Engenharia Agrícola |
repository.name.fl_str_mv |
Engenharia Agrícola - Associação Brasileira de Engenharia Agrícola (SBEA) |
repository.mail.fl_str_mv |
revistasbea@sbea.org.br||sbea@sbea.org.br |
_version_ |
1752126271524962304 |