Methodology for spatialization of intense rainfall equation parameters

Bibliographic Details
Main Author: Xavier,Alexandre C.
Publication Date: 2014
Other Authors: Cecílio,Roberto A., Pruski,Fernando F., Lima,Julião S. de S.
Format: Article
Language: eng
Source: Engenharia Agrícola
Download full: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162014000300012
Summary: The aim of this study was to generate maps of intense rainfall equation parameters using interpolated maximum intense rainfall data. The study area comprised Espírito Santo State, Brazil. A total of 59 intense rainfall equations were used to interpolate maximum intense rainfall, with a 1 x 1 km spatial resolution. Maximum intense rainfall was interpolated considering recurrence of 2; 5; 10; 20; 50 and 100 years, and duration of 10; 20; 30; 40; 50; 60; 120; 240; 360; 420; 660; 720; 900; 1,140; 1,380 and 1,440 minutes, resulting in 96 maps of maximum intense rainfall. The used interpolators were inverse distance weighting and ordinary kriging, for which significance level (p-value) and coefficient of determination (R²) were evaluated for the cross-validation data, choosing the method that presented better R² to generate maps. Finally, maps of maximum intense precipitation were used to estimate, cell by cell, the intense rainfall equation parameters. In comparison with literature data, the mean percentage error of estimated intense rainfall equations was 13.8%. Maps of spatialized parameters, obtained in this study, are of simple use; once they are georeferenced, they may be imported into any geographic information system to be used for a specific area of interest.
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spelling Methodology for spatialization of intense rainfall equation parametersintensity-duration-frequency equationgeostatisticshydrologyThe aim of this study was to generate maps of intense rainfall equation parameters using interpolated maximum intense rainfall data. The study area comprised Espírito Santo State, Brazil. A total of 59 intense rainfall equations were used to interpolate maximum intense rainfall, with a 1 x 1 km spatial resolution. Maximum intense rainfall was interpolated considering recurrence of 2; 5; 10; 20; 50 and 100 years, and duration of 10; 20; 30; 40; 50; 60; 120; 240; 360; 420; 660; 720; 900; 1,140; 1,380 and 1,440 minutes, resulting in 96 maps of maximum intense rainfall. The used interpolators were inverse distance weighting and ordinary kriging, for which significance level (p-value) and coefficient of determination (R²) were evaluated for the cross-validation data, choosing the method that presented better R² to generate maps. Finally, maps of maximum intense precipitation were used to estimate, cell by cell, the intense rainfall equation parameters. In comparison with literature data, the mean percentage error of estimated intense rainfall equations was 13.8%. Maps of spatialized parameters, obtained in this study, are of simple use; once they are georeferenced, they may be imported into any geographic information system to be used for a specific area of interest.Associação Brasileira de Engenharia Agrícola2014-06-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162014000300012Engenharia Agrícola v.34 n.3 2014reponame:Engenharia Agrícolainstname:Associação Brasileira de Engenharia Agrícola (SBEA)instacron:SBEA10.1590/S0100-69162014000300012info:eu-repo/semantics/openAccessXavier,Alexandre C.Cecílio,Roberto A.Pruski,Fernando F.Lima,Julião S. de S.eng2014-08-05T00:00:00Zoai:scielo:S0100-69162014000300012Revistahttp://www.engenhariaagricola.org.br/ORGhttps://old.scielo.br/oai/scielo-oai.phprevistasbea@sbea.org.br||sbea@sbea.org.br1809-44300100-6916opendoar:2014-08-05T00:00Engenharia Agrícola - Associação Brasileira de Engenharia Agrícola (SBEA)false
dc.title.none.fl_str_mv Methodology for spatialization of intense rainfall equation parameters
title Methodology for spatialization of intense rainfall equation parameters
spellingShingle Methodology for spatialization of intense rainfall equation parameters
Xavier,Alexandre C.
intensity-duration-frequency equation
geostatistics
hydrology
title_short Methodology for spatialization of intense rainfall equation parameters
title_full Methodology for spatialization of intense rainfall equation parameters
title_fullStr Methodology for spatialization of intense rainfall equation parameters
title_full_unstemmed Methodology for spatialization of intense rainfall equation parameters
title_sort Methodology for spatialization of intense rainfall equation parameters
author Xavier,Alexandre C.
author_facet Xavier,Alexandre C.
Cecílio,Roberto A.
Pruski,Fernando F.
Lima,Julião S. de S.
author_role author
author2 Cecílio,Roberto A.
Pruski,Fernando F.
Lima,Julião S. de S.
author2_role author
author
author
dc.contributor.author.fl_str_mv Xavier,Alexandre C.
Cecílio,Roberto A.
Pruski,Fernando F.
Lima,Julião S. de S.
dc.subject.por.fl_str_mv intensity-duration-frequency equation
geostatistics
hydrology
topic intensity-duration-frequency equation
geostatistics
hydrology
description The aim of this study was to generate maps of intense rainfall equation parameters using interpolated maximum intense rainfall data. The study area comprised Espírito Santo State, Brazil. A total of 59 intense rainfall equations were used to interpolate maximum intense rainfall, with a 1 x 1 km spatial resolution. Maximum intense rainfall was interpolated considering recurrence of 2; 5; 10; 20; 50 and 100 years, and duration of 10; 20; 30; 40; 50; 60; 120; 240; 360; 420; 660; 720; 900; 1,140; 1,380 and 1,440 minutes, resulting in 96 maps of maximum intense rainfall. The used interpolators were inverse distance weighting and ordinary kriging, for which significance level (p-value) and coefficient of determination (R²) were evaluated for the cross-validation data, choosing the method that presented better R² to generate maps. Finally, maps of maximum intense precipitation were used to estimate, cell by cell, the intense rainfall equation parameters. In comparison with literature data, the mean percentage error of estimated intense rainfall equations was 13.8%. Maps of spatialized parameters, obtained in this study, are of simple use; once they are georeferenced, they may be imported into any geographic information system to be used for a specific area of interest.
publishDate 2014
dc.date.none.fl_str_mv 2014-06-01
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=S0100-69162014000300012
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162014000300012
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/S0100-69162014000300012
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.34 n.3 2014
reponame:Engenharia Agrícola
instname:Associação Brasileira de Engenharia Agrícola (SBEA)
instacron:SBEA
instname_str Associação Brasileira de Engenharia Agrícola (SBEA)
instacron_str SBEA
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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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