PREDICTIVE MODELS OF WATER APPLICATION AND DISTRIBUTION EFFICIENCY IN CONVENTIONAL SPRINKLING

Detalhes bibliográficos
Autor(a) principal: Araújo,Edcássio D.
Data de Publicação: 2020
Outros Autores: Santos,Dionei L., Alvino,Francisco C. G., Ferreira,Lucas B., Cunha,Fernando F. da
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Engenharia Agrícola
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162020000100024
Resumo: ABSTRACT Correct determinations of distribution (Ed) and application (EA) efficiencies allow adequate estimations of the gross irrigation depth. This study aimed: i) to determine the distribution efficiency using the Christiansen uniformity coefficient (CUC) in a sprinkler irrigation system under different weather conditions and working pressures; ii) to compare the mean, median, and cumulative CUC values; and iii) to evaluate the predictive capacity of four EA estimation models. CUC values were determined from 80 assessments, as well as the mean, median, and cumulative. The precipitated water depth accumulated in each collector was considered for the accumulated CUC. More uniform evaluations were used for EA (working pressure of 196 kPa), resulting in 20 samples. Besides being measured, EA was estimated by Keller & Bliesner, Playán, Tarjuelo, and Beskow methods. Statistical indicators were the root mean square error, mean bias error, Willmott agreement index, mean absolute error, and Pearson correlation coefficient. CUC values ranged from 66.51 to 92.04%, and the accumulated CUC provided an improvement over the isolated evaluations. The Beskow model had the best EA estimations in conventional spraying.
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spelling PREDICTIVE MODELS OF WATER APPLICATION AND DISTRIBUTION EFFICIENCY IN CONVENTIONAL SPRINKLINGuniformity coefficientirrigation efficiencyevaporation and wind driftABSTRACT Correct determinations of distribution (Ed) and application (EA) efficiencies allow adequate estimations of the gross irrigation depth. This study aimed: i) to determine the distribution efficiency using the Christiansen uniformity coefficient (CUC) in a sprinkler irrigation system under different weather conditions and working pressures; ii) to compare the mean, median, and cumulative CUC values; and iii) to evaluate the predictive capacity of four EA estimation models. CUC values were determined from 80 assessments, as well as the mean, median, and cumulative. The precipitated water depth accumulated in each collector was considered for the accumulated CUC. More uniform evaluations were used for EA (working pressure of 196 kPa), resulting in 20 samples. Besides being measured, EA was estimated by Keller & Bliesner, Playán, Tarjuelo, and Beskow methods. Statistical indicators were the root mean square error, mean bias error, Willmott agreement index, mean absolute error, and Pearson correlation coefficient. CUC values ranged from 66.51 to 92.04%, and the accumulated CUC provided an improvement over the isolated evaluations. The Beskow model had the best EA estimations in conventional spraying.Associação Brasileira de Engenharia Agrícola2020-02-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162020000100024Engenharia Agrícola v.40 n.1 2020reponame:Engenharia Agrícolainstname:Associação Brasileira de Engenharia Agrícola (SBEA)instacron:SBEA10.1590/1809-4430-eng.agric.v40n1p24-33/2020info:eu-repo/semantics/openAccessAraújo,Edcássio D.Santos,Dionei L.Alvino,Francisco C. G.Ferreira,Lucas B.Cunha,Fernando F. daeng2020-02-12T00:00:00Zoai:scielo:S0100-69162020000100024Revistahttp://www.engenhariaagricola.org.br/ORGhttps://old.scielo.br/oai/scielo-oai.phprevistasbea@sbea.org.br||sbea@sbea.org.br1809-44300100-6916opendoar:2020-02-12T00:00Engenharia Agrícola - Associação Brasileira de Engenharia Agrícola (SBEA)false
dc.title.none.fl_str_mv PREDICTIVE MODELS OF WATER APPLICATION AND DISTRIBUTION EFFICIENCY IN CONVENTIONAL SPRINKLING
title PREDICTIVE MODELS OF WATER APPLICATION AND DISTRIBUTION EFFICIENCY IN CONVENTIONAL SPRINKLING
spellingShingle PREDICTIVE MODELS OF WATER APPLICATION AND DISTRIBUTION EFFICIENCY IN CONVENTIONAL SPRINKLING
Araújo,Edcássio D.
uniformity coefficient
irrigation efficiency
evaporation and wind drift
title_short PREDICTIVE MODELS OF WATER APPLICATION AND DISTRIBUTION EFFICIENCY IN CONVENTIONAL SPRINKLING
title_full PREDICTIVE MODELS OF WATER APPLICATION AND DISTRIBUTION EFFICIENCY IN CONVENTIONAL SPRINKLING
title_fullStr PREDICTIVE MODELS OF WATER APPLICATION AND DISTRIBUTION EFFICIENCY IN CONVENTIONAL SPRINKLING
title_full_unstemmed PREDICTIVE MODELS OF WATER APPLICATION AND DISTRIBUTION EFFICIENCY IN CONVENTIONAL SPRINKLING
title_sort PREDICTIVE MODELS OF WATER APPLICATION AND DISTRIBUTION EFFICIENCY IN CONVENTIONAL SPRINKLING
author Araújo,Edcássio D.
author_facet Araújo,Edcássio D.
Santos,Dionei L.
Alvino,Francisco C. G.
Ferreira,Lucas B.
Cunha,Fernando F. da
author_role author
author2 Santos,Dionei L.
Alvino,Francisco C. G.
Ferreira,Lucas B.
Cunha,Fernando F. da
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Araújo,Edcássio D.
Santos,Dionei L.
Alvino,Francisco C. G.
Ferreira,Lucas B.
Cunha,Fernando F. da
dc.subject.por.fl_str_mv uniformity coefficient
irrigation efficiency
evaporation and wind drift
topic uniformity coefficient
irrigation efficiency
evaporation and wind drift
description ABSTRACT Correct determinations of distribution (Ed) and application (EA) efficiencies allow adequate estimations of the gross irrigation depth. This study aimed: i) to determine the distribution efficiency using the Christiansen uniformity coefficient (CUC) in a sprinkler irrigation system under different weather conditions and working pressures; ii) to compare the mean, median, and cumulative CUC values; and iii) to evaluate the predictive capacity of four EA estimation models. CUC values were determined from 80 assessments, as well as the mean, median, and cumulative. The precipitated water depth accumulated in each collector was considered for the accumulated CUC. More uniform evaluations were used for EA (working pressure of 196 kPa), resulting in 20 samples. Besides being measured, EA was estimated by Keller & Bliesner, Playán, Tarjuelo, and Beskow methods. Statistical indicators were the root mean square error, mean bias error, Willmott agreement index, mean absolute error, and Pearson correlation coefficient. CUC values ranged from 66.51 to 92.04%, and the accumulated CUC provided an improvement over the isolated evaluations. The Beskow model had the best EA estimations in conventional spraying.
publishDate 2020
dc.date.none.fl_str_mv 2020-02-01
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=S0100-69162020000100024
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162020000100024
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/1809-4430-eng.agric.v40n1p24-33/2020
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.40 n.1 2020
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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