Mapping of use and occupation of the soil and irrigation water quality in the city of Salto do Lontra-Paraná, Brazil

Detalhes bibliográficos
Autor(a) principal: Wrublack,Suzana C.
Data de Publicação: 2013
Outros Autores: Mercante,Erivelto, Vilas Boas,Marcio A.
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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spelling 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
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