MATHEMATICAL MODELS FOR ESTIMATE THE FINE AND DEAD FUEL MOISTURE CONTENT

Detalhes bibliográficos
Autor(a) principal: White, Benjamin Leonardo Alves
Data de Publicação: 2018
Tipo de documento: Artigo
Idioma: por
Título da fonte: Ciência Florestal (Online)
Texto Completo: https://periodicos.ufsm.br/cienciaflorestal/article/view/31622
Resumo: This article aims to describe, through a literature review, the main existing mathematical models to estimate the fine dead fuel moisture content (1-hr time lag class) based on meteorological parameters. The determination of these values is extremely important for forest fire prevention and suppression efforts, and for conducting prescribed burns, since they account for the ignition probability and fire behavior. Based on the analysis, it can be concluded that the Fine Fuel Moisture Code (FFMC) of the Canadian Fire Weather Index (FWI), is the most widely used model in the world. However, since some experimental works report limitations and imprecision for FFMC and for all the others models examined in this paper, it is essential to test their precision before using them in an operational way. In Brazil, due to the lack of studies in this area, it is recommended to validate or build new models in order to improve prevention programs and assist in the development of an efficient nationwide forest fire risk model.
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spelling MATHEMATICAL MODELS FOR ESTIMATE THE FINE AND DEAD FUEL MOISTURE CONTENTMODELOS MATEMÁTICOS DE PREVISÃO DO TEOR DE UMIDADE DOS MATERIAIS COMBUSTÍVEIS FLORESTAIS FINOS E MORTOSforest firefire riskvapor exchange.incêndios florestaisrisco de incêndiotroca de vapor.This article aims to describe, through a literature review, the main existing mathematical models to estimate the fine dead fuel moisture content (1-hr time lag class) based on meteorological parameters. The determination of these values is extremely important for forest fire prevention and suppression efforts, and for conducting prescribed burns, since they account for the ignition probability and fire behavior. Based on the analysis, it can be concluded that the Fine Fuel Moisture Code (FFMC) of the Canadian Fire Weather Index (FWI), is the most widely used model in the world. However, since some experimental works report limitations and imprecision for FFMC and for all the others models examined in this paper, it is essential to test their precision before using them in an operational way. In Brazil, due to the lack of studies in this area, it is recommended to validate or build new models in order to improve prevention programs and assist in the development of an efficient nationwide forest fire risk model.O presente artigo busca descrever, por meio de uma revisão da literatura, os principais modelos matemáticos existentes para estimar o teor de umidade dos materiais combustíveis florestais finos e mortos, ou seja, os materiais da classe de 1-h de timelag, com base em variáveis meteorológicas. A determinação desses valores compreende uma importante informação para o delineamento de ações de prevenção e combate a incêndios florestais, e de realização de queimadas controladas, já que respondem pela probabilidade de ignição e comportamento do fogo. Com base na análise realizada, percebe-se que o Fine Fuel Moisture Code (FFMC), um dos componentes do Fire Weather Index (FWI) canadense, constitui o modelo de previsão do teor de umidade mais utilizado no mundo. Porém, considerando-se que trabalhos na literatura relatam limitações e imprecisão tanto no FFMC quanto nos demais modelos analisados nesse artigo, é essencial a validação dos mesmos antes de serem utilizados de forma operacional. Em função da pequena quantidade de estudos envolvendo essa temática no Brasil, recomenda-se a validação ou desenvolvimento de novos modelos, a fim de se aprimorar os programas de prevenção e de delineamento de risco de incêndios florestais em nível nacional.Universidade Federal de Santa Maria2018-04-02info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://periodicos.ufsm.br/cienciaflorestal/article/view/3162210.5902/1980509831622Ciência Florestal; Vol. 28 No. 1 (2018); 432-445Ciência Florestal; v. 28 n. 1 (2018); 432-4451980-50980103-9954reponame:Ciência Florestal (Online)instname:Universidade Federal de Santa Maria (UFSM)instacron:UFSMporhttps://periodicos.ufsm.br/cienciaflorestal/article/view/31622/pdfCopyright (c) 2018 Ciência Florestalinfo:eu-repo/semantics/openAccessWhite, Benjamin Leonardo Alves2018-04-23T20:36:22Zoai:ojs.pkp.sfu.ca:article/31622Revistahttp://www.ufsm.br/cienciaflorestal/ONGhttps://old.scielo.br/oai/scielo-oai.php||cienciaflorestal@ufsm.br|| cienciaflorestal@gmail.com|| cf@smail.ufsm.br1980-50980103-9954opendoar:2018-04-23T20:36:22Ciência Florestal (Online) - Universidade Federal de Santa Maria (UFSM)false
dc.title.none.fl_str_mv MATHEMATICAL MODELS FOR ESTIMATE THE FINE AND DEAD FUEL MOISTURE CONTENT
MODELOS MATEMÁTICOS DE PREVISÃO DO TEOR DE UMIDADE DOS MATERIAIS COMBUSTÍVEIS FLORESTAIS FINOS E MORTOS
title MATHEMATICAL MODELS FOR ESTIMATE THE FINE AND DEAD FUEL MOISTURE CONTENT
spellingShingle MATHEMATICAL MODELS FOR ESTIMATE THE FINE AND DEAD FUEL MOISTURE CONTENT
White, Benjamin Leonardo Alves
forest fire
fire risk
vapor exchange.
incêndios florestais
risco de incêndio
troca de vapor.
title_short MATHEMATICAL MODELS FOR ESTIMATE THE FINE AND DEAD FUEL MOISTURE CONTENT
title_full MATHEMATICAL MODELS FOR ESTIMATE THE FINE AND DEAD FUEL MOISTURE CONTENT
title_fullStr MATHEMATICAL MODELS FOR ESTIMATE THE FINE AND DEAD FUEL MOISTURE CONTENT
title_full_unstemmed MATHEMATICAL MODELS FOR ESTIMATE THE FINE AND DEAD FUEL MOISTURE CONTENT
title_sort MATHEMATICAL MODELS FOR ESTIMATE THE FINE AND DEAD FUEL MOISTURE CONTENT
author White, Benjamin Leonardo Alves
author_facet White, Benjamin Leonardo Alves
author_role author
dc.contributor.author.fl_str_mv White, Benjamin Leonardo Alves
dc.subject.por.fl_str_mv forest fire
fire risk
vapor exchange.
incêndios florestais
risco de incêndio
troca de vapor.
topic forest fire
fire risk
vapor exchange.
incêndios florestais
risco de incêndio
troca de vapor.
description This article aims to describe, through a literature review, the main existing mathematical models to estimate the fine dead fuel moisture content (1-hr time lag class) based on meteorological parameters. The determination of these values is extremely important for forest fire prevention and suppression efforts, and for conducting prescribed burns, since they account for the ignition probability and fire behavior. Based on the analysis, it can be concluded that the Fine Fuel Moisture Code (FFMC) of the Canadian Fire Weather Index (FWI), is the most widely used model in the world. However, since some experimental works report limitations and imprecision for FFMC and for all the others models examined in this paper, it is essential to test their precision before using them in an operational way. In Brazil, due to the lack of studies in this area, it is recommended to validate or build new models in order to improve prevention programs and assist in the development of an efficient nationwide forest fire risk model.
publishDate 2018
dc.date.none.fl_str_mv 2018-04-02
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://periodicos.ufsm.br/cienciaflorestal/article/view/31622
10.5902/1980509831622
url https://periodicos.ufsm.br/cienciaflorestal/article/view/31622
identifier_str_mv 10.5902/1980509831622
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://periodicos.ufsm.br/cienciaflorestal/article/view/31622/pdf
dc.rights.driver.fl_str_mv Copyright (c) 2018 Ciência Florestal
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2018 Ciência Florestal
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Federal de Santa Maria
publisher.none.fl_str_mv Universidade Federal de Santa Maria
dc.source.none.fl_str_mv Ciência Florestal; Vol. 28 No. 1 (2018); 432-445
Ciência Florestal; v. 28 n. 1 (2018); 432-445
1980-5098
0103-9954
reponame:Ciência Florestal (Online)
instname:Universidade Federal de Santa Maria (UFSM)
instacron:UFSM
instname_str Universidade Federal de Santa Maria (UFSM)
instacron_str UFSM
institution UFSM
reponame_str Ciência Florestal (Online)
collection Ciência Florestal (Online)
repository.name.fl_str_mv Ciência Florestal (Online) - Universidade Federal de Santa Maria (UFSM)
repository.mail.fl_str_mv ||cienciaflorestal@ufsm.br|| cienciaflorestal@gmail.com|| cf@smail.ufsm.br
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