Geostatistical techniques applied to mapping limnological variables and quantify the uncertainty associated with estimates

Detalhes bibliográficos
Autor(a) principal: Cigagna,Cristiano
Data de Publicação: 2015
Outros Autores: Bonotto,Daniel Marcos, Sturaro,José Ricardo, Camargo,Antonio Fernando Monteiro
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Acta Limnologica Brasiliensia (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2179-975X2015000400421
Resumo: Abstract Aim: This study aimed to map the concentrations of limnological variables in a reservoir employing semivariogram geostatistical techniques and Kriging estimates for unsampled locations, as well as the uncertainty calculation associated with the estimates. Methods: We established twenty-seven points distributed in a regular mesh for sampling. Then it was determined the concentrations of chlorophyll-a, total nitrogen and total phosphorus. Subsequently, a spatial variability analysis was performed and the semivariogram function was modeled for all variables and the variographic mathematical models were established. The main geostatistical estimation technique was the ordinary Kriging. The work was developed with the estimate of a heavy grid points for each variables that formed the basis of the interpolated maps. Results: Through the semivariogram analysis was possible to identify the random component as not significant for the estimation process of chlorophyll-a, and as significant for total nitrogen and total phosphorus. Geostatistical maps were produced from the Kriging for each variable and the respective standard deviations of the estimates calculated. These measurements allowed us to map the concentrations of limnological variables throughout the reservoir. The calculation of standard deviations provided the quality of the estimates and, consequently, the reliability of the final product. Conclusions: The use of the Kriging statistical technique to estimate heavy mesh points associated with the error dispersion (standard deviation of the estimate), made it possible to make quality and reliable maps of the estimated variables. Concentrations of limnological variables in general were higher in the lacustrine zone and decreased towards the riverine zone. The chlorophyll-a and total nitrogen correlated comparing the grid generated by Kriging. Although the use of Kriging is more laborious compared to other interpolation methods, this technique is distinguished for its ability to minimize the variance of the estimate and provide the estimated value of the degree of uncertainty.
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spelling Geostatistical techniques applied to mapping limnological variables and quantify the uncertainty associated with estimatesgeostatisticsKrigingstandard deviation of the estimatereservoirslimnologyAbstract Aim: This study aimed to map the concentrations of limnological variables in a reservoir employing semivariogram geostatistical techniques and Kriging estimates for unsampled locations, as well as the uncertainty calculation associated with the estimates. Methods: We established twenty-seven points distributed in a regular mesh for sampling. Then it was determined the concentrations of chlorophyll-a, total nitrogen and total phosphorus. Subsequently, a spatial variability analysis was performed and the semivariogram function was modeled for all variables and the variographic mathematical models were established. The main geostatistical estimation technique was the ordinary Kriging. The work was developed with the estimate of a heavy grid points for each variables that formed the basis of the interpolated maps. Results: Through the semivariogram analysis was possible to identify the random component as not significant for the estimation process of chlorophyll-a, and as significant for total nitrogen and total phosphorus. Geostatistical maps were produced from the Kriging for each variable and the respective standard deviations of the estimates calculated. These measurements allowed us to map the concentrations of limnological variables throughout the reservoir. The calculation of standard deviations provided the quality of the estimates and, consequently, the reliability of the final product. Conclusions: The use of the Kriging statistical technique to estimate heavy mesh points associated with the error dispersion (standard deviation of the estimate), made it possible to make quality and reliable maps of the estimated variables. Concentrations of limnological variables in general were higher in the lacustrine zone and decreased towards the riverine zone. The chlorophyll-a and total nitrogen correlated comparing the grid generated by Kriging. Although the use of Kriging is more laborious compared to other interpolation methods, this technique is distinguished for its ability to minimize the variance of the estimate and provide the estimated value of the degree of uncertainty.Associação Brasileira de Limnologia2015-12-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S2179-975X2015000400421Acta Limnologica Brasiliensia v.27 n.4 2015reponame:Acta Limnologica Brasiliensia (Online)instname:Associação Brasileira de Limnologia (ABL)instacron:ABL10.1590/S2179-975X3315info:eu-repo/semantics/openAccessCigagna,CristianoBonotto,Daniel MarcosSturaro,José RicardoCamargo,Antonio Fernando Monteiroeng2016-04-18T00:00:00Zoai:scielo:S2179-975X2015000400421Revistahttp://www.ablimno.org.br/publiActa.phphttps://old.scielo.br/oai/scielo-oai.php||actalb@rc.unesp.br2179-975X0102-6712opendoar:2016-04-18T00:00Acta Limnologica Brasiliensia (Online) - Associação Brasileira de Limnologia (ABL)false
dc.title.none.fl_str_mv Geostatistical techniques applied to mapping limnological variables and quantify the uncertainty associated with estimates
title Geostatistical techniques applied to mapping limnological variables and quantify the uncertainty associated with estimates
spellingShingle Geostatistical techniques applied to mapping limnological variables and quantify the uncertainty associated with estimates
Cigagna,Cristiano
geostatistics
Kriging
standard deviation of the estimate
reservoirs
limnology
title_short Geostatistical techniques applied to mapping limnological variables and quantify the uncertainty associated with estimates
title_full Geostatistical techniques applied to mapping limnological variables and quantify the uncertainty associated with estimates
title_fullStr Geostatistical techniques applied to mapping limnological variables and quantify the uncertainty associated with estimates
title_full_unstemmed Geostatistical techniques applied to mapping limnological variables and quantify the uncertainty associated with estimates
title_sort Geostatistical techniques applied to mapping limnological variables and quantify the uncertainty associated with estimates
author Cigagna,Cristiano
author_facet Cigagna,Cristiano
Bonotto,Daniel Marcos
Sturaro,José Ricardo
Camargo,Antonio Fernando Monteiro
author_role author
author2 Bonotto,Daniel Marcos
Sturaro,José Ricardo
Camargo,Antonio Fernando Monteiro
author2_role author
author
author
dc.contributor.author.fl_str_mv Cigagna,Cristiano
Bonotto,Daniel Marcos
Sturaro,José Ricardo
Camargo,Antonio Fernando Monteiro
dc.subject.por.fl_str_mv geostatistics
Kriging
standard deviation of the estimate
reservoirs
limnology
topic geostatistics
Kriging
standard deviation of the estimate
reservoirs
limnology
description Abstract Aim: This study aimed to map the concentrations of limnological variables in a reservoir employing semivariogram geostatistical techniques and Kriging estimates for unsampled locations, as well as the uncertainty calculation associated with the estimates. Methods: We established twenty-seven points distributed in a regular mesh for sampling. Then it was determined the concentrations of chlorophyll-a, total nitrogen and total phosphorus. Subsequently, a spatial variability analysis was performed and the semivariogram function was modeled for all variables and the variographic mathematical models were established. The main geostatistical estimation technique was the ordinary Kriging. The work was developed with the estimate of a heavy grid points for each variables that formed the basis of the interpolated maps. Results: Through the semivariogram analysis was possible to identify the random component as not significant for the estimation process of chlorophyll-a, and as significant for total nitrogen and total phosphorus. Geostatistical maps were produced from the Kriging for each variable and the respective standard deviations of the estimates calculated. These measurements allowed us to map the concentrations of limnological variables throughout the reservoir. The calculation of standard deviations provided the quality of the estimates and, consequently, the reliability of the final product. Conclusions: The use of the Kriging statistical technique to estimate heavy mesh points associated with the error dispersion (standard deviation of the estimate), made it possible to make quality and reliable maps of the estimated variables. Concentrations of limnological variables in general were higher in the lacustrine zone and decreased towards the riverine zone. The chlorophyll-a and total nitrogen correlated comparing the grid generated by Kriging. Although the use of Kriging is more laborious compared to other interpolation methods, this technique is distinguished for its ability to minimize the variance of the estimate and provide the estimated value of the degree of uncertainty.
publishDate 2015
dc.date.none.fl_str_mv 2015-12-01
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=S2179-975X2015000400421
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2179-975X2015000400421
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/S2179-975X3315
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 Limnologia
publisher.none.fl_str_mv Associação Brasileira de Limnologia
dc.source.none.fl_str_mv Acta Limnologica Brasiliensia v.27 n.4 2015
reponame:Acta Limnologica Brasiliensia (Online)
instname:Associação Brasileira de Limnologia (ABL)
instacron:ABL
instname_str Associação Brasileira de Limnologia (ABL)
instacron_str ABL
institution ABL
reponame_str Acta Limnologica Brasiliensia (Online)
collection Acta Limnologica Brasiliensia (Online)
repository.name.fl_str_mv Acta Limnologica Brasiliensia (Online) - Associação Brasileira de Limnologia (ABL)
repository.mail.fl_str_mv ||actalb@rc.unesp.br
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