Geostatistical techniques applied to mapping limnological variables and quantify the uncertainty associated with estimates
Autor(a) principal: | |
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Data de Publicação: | 2015 |
Outros Autores: | , , |
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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Acta Limnologica Brasiliensia (Online) |
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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 |
_version_ |
1754212636836233216 |