PREDICTIVE MODELS OF WATER APPLICATION AND DISTRIBUTION EFFICIENCY IN CONVENTIONAL SPRINKLING
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , , |
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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Engenharia Agrícola |
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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 |
_version_ |
1752126274508161024 |