Estimate of reference evapotranspiration through continuous probability modelling

Detalhes bibliográficos
Autor(a) principal: Uliana, Eduardo M.
Data de Publicação: 2017
Outros Autores: Silva, Demetrius D. da, Silva, José G. F. da, Fraga, Micael de S., Lisboa, Luana
Tipo de documento: Artigo
Idioma: eng
Título da fonte: LOCUS Repositório Institucional da UFV
Texto Completo: http://dx.doi.org/10.1590/1809-4430-eng.agric.v37n2p257-267/2017
http://locus.ufv.br//handle/123456789/26062
Resumo: This study aimed at testing the fit of continuous probability distributions to a daily reference evapotranspiration dataset (ET0) at a 75% probability level for designing of irrigation systems. Reference evapotranspiration was estimated by the Penman-Monteith method (FAO-56-PM) for eight locations, within the state of Espírito Santo (Brazil), where there are automatic gauge stations. The assessed probability distributions were beta, gamma, generalized extreme value (GEV), generalized logistic (GLO), generalized normal (GN), Gumbel (G), normal (N), Pearson type 3 (P3), Weibull (W), two- and three-parameter lognormal (LN2 and LN3). The fitting of the probability distributions to the ET0 daily dataset was checked by the Kolmogorov-Smirnov's test. Among the studied distributions, GN was the only one to fit the ET0 data for all studied months and locations. We should also infer that continuous probability models have a good fit to the studied ET0 dataset, enabling its estimation at 75% probability through a Generalized Normal distribution (GN). Therefore, it can be used for the sizing of irrigation systems according to a given degree of risk.
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spelling Uliana, Eduardo M.Silva, Demetrius D. daSilva, José G. F. daFraga, Micael de S.Lisboa, Luana2019-07-03T14:21:42Z2019-07-03T14:21:42Z2017-031809-4430http://dx.doi.org/10.1590/1809-4430-eng.agric.v37n2p257-267/2017http://locus.ufv.br//handle/123456789/26062This study aimed at testing the fit of continuous probability distributions to a daily reference evapotranspiration dataset (ET0) at a 75% probability level for designing of irrigation systems. Reference evapotranspiration was estimated by the Penman-Monteith method (FAO-56-PM) for eight locations, within the state of Espírito Santo (Brazil), where there are automatic gauge stations. The assessed probability distributions were beta, gamma, generalized extreme value (GEV), generalized logistic (GLO), generalized normal (GN), Gumbel (G), normal (N), Pearson type 3 (P3), Weibull (W), two- and three-parameter lognormal (LN2 and LN3). The fitting of the probability distributions to the ET0 daily dataset was checked by the Kolmogorov-Smirnov's test. Among the studied distributions, GN was the only one to fit the ET0 data for all studied months and locations. We should also infer that continuous probability models have a good fit to the studied ET0 dataset, enabling its estimation at 75% probability through a Generalized Normal distribution (GN). Therefore, it can be used for the sizing of irrigation systems according to a given degree of risk.engEngenharia Agrícolav. 37, n. 2, p. 257- 267, mar./ abr. 2017EvapotranspirationProbabilityIrrigationEstimate of reference evapotranspiration through continuous probability modellinginfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfinfo:eu-repo/semantics/openAccessreponame:LOCUS Repositório Institucional da UFVinstname:Universidade Federal de Viçosa (UFV)instacron:UFVORIGINALartigo.pdfartigo.pdfartigoapplication/pdf888315https://locus.ufv.br//bitstream/123456789/26062/1/artigo.pdf1e35621336a988f46c58a3d5ebb99cacMD51LICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://locus.ufv.br//bitstream/123456789/26062/2/license.txt8a4605be74aa9ea9d79846c1fba20a33MD52123456789/260622019-07-03 11:56:49.263oai:locus.ufv.br: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Repositório InstitucionalPUBhttps://www.locus.ufv.br/oai/requestfabiojreis@ufv.bropendoar:21452019-07-03T14:56:49LOCUS Repositório Institucional da UFV - Universidade Federal de Viçosa (UFV)false
dc.title.en.fl_str_mv Estimate of reference evapotranspiration through continuous probability modelling
title Estimate of reference evapotranspiration through continuous probability modelling
spellingShingle Estimate of reference evapotranspiration through continuous probability modelling
Uliana, Eduardo M.
Evapotranspiration
Probability
Irrigation
title_short Estimate of reference evapotranspiration through continuous probability modelling
title_full Estimate of reference evapotranspiration through continuous probability modelling
title_fullStr Estimate of reference evapotranspiration through continuous probability modelling
title_full_unstemmed Estimate of reference evapotranspiration through continuous probability modelling
title_sort Estimate of reference evapotranspiration through continuous probability modelling
author Uliana, Eduardo M.
author_facet Uliana, Eduardo M.
Silva, Demetrius D. da
Silva, José G. F. da
Fraga, Micael de S.
Lisboa, Luana
author_role author
author2 Silva, Demetrius D. da
Silva, José G. F. da
Fraga, Micael de S.
Lisboa, Luana
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Uliana, Eduardo M.
Silva, Demetrius D. da
Silva, José G. F. da
Fraga, Micael de S.
Lisboa, Luana
dc.subject.pt-BR.fl_str_mv Evapotranspiration
Probability
Irrigation
topic Evapotranspiration
Probability
Irrigation
description This study aimed at testing the fit of continuous probability distributions to a daily reference evapotranspiration dataset (ET0) at a 75% probability level for designing of irrigation systems. Reference evapotranspiration was estimated by the Penman-Monteith method (FAO-56-PM) for eight locations, within the state of Espírito Santo (Brazil), where there are automatic gauge stations. The assessed probability distributions were beta, gamma, generalized extreme value (GEV), generalized logistic (GLO), generalized normal (GN), Gumbel (G), normal (N), Pearson type 3 (P3), Weibull (W), two- and three-parameter lognormal (LN2 and LN3). The fitting of the probability distributions to the ET0 daily dataset was checked by the Kolmogorov-Smirnov's test. Among the studied distributions, GN was the only one to fit the ET0 data for all studied months and locations. We should also infer that continuous probability models have a good fit to the studied ET0 dataset, enabling its estimation at 75% probability through a Generalized Normal distribution (GN). Therefore, it can be used for the sizing of irrigation systems according to a given degree of risk.
publishDate 2017
dc.date.issued.fl_str_mv 2017-03
dc.date.accessioned.fl_str_mv 2019-07-03T14:21:42Z
dc.date.available.fl_str_mv 2019-07-03T14:21:42Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
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status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1590/1809-4430-eng.agric.v37n2p257-267/2017
http://locus.ufv.br//handle/123456789/26062
dc.identifier.issn.none.fl_str_mv 1809-4430
identifier_str_mv 1809-4430
url http://dx.doi.org/10.1590/1809-4430-eng.agric.v37n2p257-267/2017
http://locus.ufv.br//handle/123456789/26062
dc.language.iso.fl_str_mv eng
language eng
dc.relation.ispartofseries.pt-BR.fl_str_mv v. 37, n. 2, p. 257- 267, mar./ abr. 2017
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
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dc.publisher.none.fl_str_mv Engenharia Agrícola
publisher.none.fl_str_mv Engenharia Agrícola
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