Rainfall erosivity estimation: Comparison and statistical assessment among methods using data from Southeastern Brazil

Detalhes bibliográficos
Autor(a) principal: Cardoso,Dione Pereira
Data de Publicação: 2022
Outros Autores: Avanzi,Junior Cesar, Ferreira,Daniel Furtado, Acuña-Guzman,Salvador Francisco, Silva,Marx Leandro Naves, Pires,Fábio Ribeiro, Curi,Nilton
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Revista Brasileira de Ciência do Solo (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-06832022000100504
Resumo: ABSTRACT Rainfall erosivity (R factor) is one of the six factors of the Universal Soil Loss Equation, being calculated based on the product of rainfall kinetic energy multiplied by its 30-minute maximum intensity. However, the lack of detailed and reliable rainfall data in many parts of the world has driven the use of other methods to estimate rainfall erosivity based on daily, monthly or annual data. These methods still need to be assessed to determine if their estimates are consistent with the standard method for calculating rainfall erosivity. This study aimed to select a consistent method for such replacement in Brazilian conditions without access the rainfall intensity data. The tested methods included: modified Fournier, MF; modified Fournier by Zhang, MF-Z; modified Fournier by Men, MF-M; Rainfall Disaggregation, RD; TRMM Satellite with modified Fournier coefficient, TRMM-F; and TRMM Satellite with monthly rainfall, TRMM-M. The rainfall data were obtained from the USP Meteorological Station, referring to the period from 2009 to 2015. The analyses were performed according to the Additive Main effects and Multiplicative Interaction (AMMI) model and Scott-Knott statistical tests. Considering the 1:1 line, all methods had a good adjustment, presenting similar behavior in relation to the standard method. The methods behaved differently for monthly and annual periods. The MF method proved to be capable of consistently replacing the standard method in all aforementioned situations. Considering the driest period, any method can be used. For annual rainfall erosivity estimation, the RD, MF, TRMM-F and TRMM-M methods can be applied; highlighting that the TRMM-based methods are optimal for locations without on-site rain gauges. Additionally, it was computed that the modified Fournier by Men and the modified Fournier by Zhang underestimated and overestimated the rainfall erosivity, respectively.
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spelling Rainfall erosivity estimation: Comparison and statistical assessment among methods using data from Southeastern Brazilmodified Fournierrainfall disaggregationTRMMABSTRACT Rainfall erosivity (R factor) is one of the six factors of the Universal Soil Loss Equation, being calculated based on the product of rainfall kinetic energy multiplied by its 30-minute maximum intensity. However, the lack of detailed and reliable rainfall data in many parts of the world has driven the use of other methods to estimate rainfall erosivity based on daily, monthly or annual data. These methods still need to be assessed to determine if their estimates are consistent with the standard method for calculating rainfall erosivity. This study aimed to select a consistent method for such replacement in Brazilian conditions without access the rainfall intensity data. The tested methods included: modified Fournier, MF; modified Fournier by Zhang, MF-Z; modified Fournier by Men, MF-M; Rainfall Disaggregation, RD; TRMM Satellite with modified Fournier coefficient, TRMM-F; and TRMM Satellite with monthly rainfall, TRMM-M. The rainfall data were obtained from the USP Meteorological Station, referring to the period from 2009 to 2015. The analyses were performed according to the Additive Main effects and Multiplicative Interaction (AMMI) model and Scott-Knott statistical tests. Considering the 1:1 line, all methods had a good adjustment, presenting similar behavior in relation to the standard method. The methods behaved differently for monthly and annual periods. The MF method proved to be capable of consistently replacing the standard method in all aforementioned situations. Considering the driest period, any method can be used. For annual rainfall erosivity estimation, the RD, MF, TRMM-F and TRMM-M methods can be applied; highlighting that the TRMM-based methods are optimal for locations without on-site rain gauges. Additionally, it was computed that the modified Fournier by Men and the modified Fournier by Zhang underestimated and overestimated the rainfall erosivity, respectively.Sociedade Brasileira de Ciência do Solo2022-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-06832022000100504Revista Brasileira de Ciência do Solo v.46 2022reponame:Revista Brasileira de Ciência do Solo (Online)instname:Sociedade Brasileira de Ciência do Solo (SBCS)instacron:SBCS10.36783/18069657rbcs20210122info:eu-repo/semantics/openAccessCardoso,Dione PereiraAvanzi,Junior CesarFerreira,Daniel FurtadoAcuña-Guzman,Salvador FranciscoSilva,Marx Leandro NavesPires,Fábio RibeiroCuri,Niltoneng2022-03-18T00:00:00Zoai:scielo:S0100-06832022000100504Revistahttp://www.scielo.br/scielo.php?script=sci_serial&pid=0100-0683&lng=es&nrm=isohttps://old.scielo.br/oai/scielo-oai.php||sbcs@ufv.br1806-96570100-0683opendoar:2022-03-18T00:00Revista Brasileira de Ciência do Solo (Online) - Sociedade Brasileira de Ciência do Solo (SBCS)false
dc.title.none.fl_str_mv Rainfall erosivity estimation: Comparison and statistical assessment among methods using data from Southeastern Brazil
title Rainfall erosivity estimation: Comparison and statistical assessment among methods using data from Southeastern Brazil
spellingShingle Rainfall erosivity estimation: Comparison and statistical assessment among methods using data from Southeastern Brazil
Cardoso,Dione Pereira
modified Fournier
rainfall disaggregation
TRMM
title_short Rainfall erosivity estimation: Comparison and statistical assessment among methods using data from Southeastern Brazil
title_full Rainfall erosivity estimation: Comparison and statistical assessment among methods using data from Southeastern Brazil
title_fullStr Rainfall erosivity estimation: Comparison and statistical assessment among methods using data from Southeastern Brazil
title_full_unstemmed Rainfall erosivity estimation: Comparison and statistical assessment among methods using data from Southeastern Brazil
title_sort Rainfall erosivity estimation: Comparison and statistical assessment among methods using data from Southeastern Brazil
author Cardoso,Dione Pereira
author_facet Cardoso,Dione Pereira
Avanzi,Junior Cesar
Ferreira,Daniel Furtado
Acuña-Guzman,Salvador Francisco
Silva,Marx Leandro Naves
Pires,Fábio Ribeiro
Curi,Nilton
author_role author
author2 Avanzi,Junior Cesar
Ferreira,Daniel Furtado
Acuña-Guzman,Salvador Francisco
Silva,Marx Leandro Naves
Pires,Fábio Ribeiro
Curi,Nilton
author2_role author
author
author
author
author
author
dc.contributor.author.fl_str_mv Cardoso,Dione Pereira
Avanzi,Junior Cesar
Ferreira,Daniel Furtado
Acuña-Guzman,Salvador Francisco
Silva,Marx Leandro Naves
Pires,Fábio Ribeiro
Curi,Nilton
dc.subject.por.fl_str_mv modified Fournier
rainfall disaggregation
TRMM
topic modified Fournier
rainfall disaggregation
TRMM
description ABSTRACT Rainfall erosivity (R factor) is one of the six factors of the Universal Soil Loss Equation, being calculated based on the product of rainfall kinetic energy multiplied by its 30-minute maximum intensity. However, the lack of detailed and reliable rainfall data in many parts of the world has driven the use of other methods to estimate rainfall erosivity based on daily, monthly or annual data. These methods still need to be assessed to determine if their estimates are consistent with the standard method for calculating rainfall erosivity. This study aimed to select a consistent method for such replacement in Brazilian conditions without access the rainfall intensity data. The tested methods included: modified Fournier, MF; modified Fournier by Zhang, MF-Z; modified Fournier by Men, MF-M; Rainfall Disaggregation, RD; TRMM Satellite with modified Fournier coefficient, TRMM-F; and TRMM Satellite with monthly rainfall, TRMM-M. The rainfall data were obtained from the USP Meteorological Station, referring to the period from 2009 to 2015. The analyses were performed according to the Additive Main effects and Multiplicative Interaction (AMMI) model and Scott-Knott statistical tests. Considering the 1:1 line, all methods had a good adjustment, presenting similar behavior in relation to the standard method. The methods behaved differently for monthly and annual periods. The MF method proved to be capable of consistently replacing the standard method in all aforementioned situations. Considering the driest period, any method can be used. For annual rainfall erosivity estimation, the RD, MF, TRMM-F and TRMM-M methods can be applied; highlighting that the TRMM-based methods are optimal for locations without on-site rain gauges. Additionally, it was computed that the modified Fournier by Men and the modified Fournier by Zhang underestimated and overestimated the rainfall erosivity, respectively.
publishDate 2022
dc.date.none.fl_str_mv 2022-01-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
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dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-06832022000100504
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dc.language.iso.fl_str_mv eng
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dc.relation.none.fl_str_mv 10.36783/18069657rbcs20210122
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dc.publisher.none.fl_str_mv Sociedade Brasileira de Ciência do Solo
publisher.none.fl_str_mv Sociedade Brasileira de Ciência do Solo
dc.source.none.fl_str_mv Revista Brasileira de Ciência do Solo v.46 2022
reponame:Revista Brasileira de Ciência do Solo (Online)
instname:Sociedade Brasileira de Ciência do Solo (SBCS)
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instname_str Sociedade Brasileira de Ciência do Solo (SBCS)
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institution SBCS
reponame_str Revista Brasileira de Ciência do Solo (Online)
collection Revista Brasileira de Ciência do Solo (Online)
repository.name.fl_str_mv Revista Brasileira de Ciência do Solo (Online) - Sociedade Brasileira de Ciência do Solo (SBCS)
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