Physical-based time series model applied on water table depths dynamics characteristics simulation
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1590/2318-0331.0318170071 http://hdl.handle.net/11449/164421 |
Resumo: | Time series modelling applied to study water table depths monitoring data is an elegant way to model irregular and continuous data. When successive observations are dependent, future values may be predicted from past observations, and target parameters can be estimated. These may include expected values of groundwater levels, or probabilities that critical levels are exceeded at certain times or during certain periods. These target parameters are estimated with the purpose of obtaining characteristics of the development of a certain domain in time and such characteristics can, for instance, be extrapolated to future situations. In a system identification approach, is it possible to establish the dynamic relationship between water table perturbations and climatological events, vegetation, hydrogeological local conditions, management and groundwater abstraction. The aim of this work was demonstrate the use of a physical-based time series model to stablish the relationship between precipitation and water table depths from hydrogeological monitoring data. The results enabled to infer about water table dynamics even when it is affected by different climatological patterns, simulating mean, maximum and minimum states. |
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Physical-based time series model applied on water table depths dynamics characteristics simulationModellingGroundwaterMonitoringPIRFICT modelTime series modelling applied to study water table depths monitoring data is an elegant way to model irregular and continuous data. When successive observations are dependent, future values may be predicted from past observations, and target parameters can be estimated. These may include expected values of groundwater levels, or probabilities that critical levels are exceeded at certain times or during certain periods. These target parameters are estimated with the purpose of obtaining characteristics of the development of a certain domain in time and such characteristics can, for instance, be extrapolated to future situations. In a system identification approach, is it possible to establish the dynamic relationship between water table perturbations and climatological events, vegetation, hydrogeological local conditions, management and groundwater abstraction. The aim of this work was demonstrate the use of a physical-based time series model to stablish the relationship between precipitation and water table depths from hydrogeological monitoring data. The results enabled to infer about water table dynamics even when it is affected by different climatological patterns, simulating mean, maximum and minimum states.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Univ Estadual Paulista, Ourinhos, SP, BrazilUniv Estadual Paulista, Ourinhos, SP, BrazilFAPESP: 2014/04524-7FAPESP: 2016/09737-4Assoc Brasileira Recursos Hidricos-abrhUniversidade Estadual Paulista (Unesp)Manzione, Rodrigo Lilla [UNESP]2018-11-26T17:54:29Z2018-11-26T17:54:29Z2017-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article11application/pdfhttp://dx.doi.org/10.1590/2318-0331.0318170071Rbrh-revista Brasileira De Recursos Hidricos. Porte Alegre: Assoc Brasileira Recursos Hidricos-abrh, v. 23, 11 p., 2017.1414-381Xhttp://hdl.handle.net/11449/16442110.1590/2318-0331.0318170071S2318-03312018000100224WOS:000438515500007S2318-03312018000100224.pdfWeb of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengRbrh-revista Brasileira De Recursos Hidricosinfo:eu-repo/semantics/openAccess2024-06-26T20:10:56Zoai:repositorio.unesp.br:11449/164421Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T22:35:01.592839Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Physical-based time series model applied on water table depths dynamics characteristics simulation |
title |
Physical-based time series model applied on water table depths dynamics characteristics simulation |
spellingShingle |
Physical-based time series model applied on water table depths dynamics characteristics simulation Manzione, Rodrigo Lilla [UNESP] Modelling Groundwater Monitoring PIRFICT model |
title_short |
Physical-based time series model applied on water table depths dynamics characteristics simulation |
title_full |
Physical-based time series model applied on water table depths dynamics characteristics simulation |
title_fullStr |
Physical-based time series model applied on water table depths dynamics characteristics simulation |
title_full_unstemmed |
Physical-based time series model applied on water table depths dynamics characteristics simulation |
title_sort |
Physical-based time series model applied on water table depths dynamics characteristics simulation |
author |
Manzione, Rodrigo Lilla [UNESP] |
author_facet |
Manzione, Rodrigo Lilla [UNESP] |
author_role |
author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (Unesp) |
dc.contributor.author.fl_str_mv |
Manzione, Rodrigo Lilla [UNESP] |
dc.subject.por.fl_str_mv |
Modelling Groundwater Monitoring PIRFICT model |
topic |
Modelling Groundwater Monitoring PIRFICT model |
description |
Time series modelling applied to study water table depths monitoring data is an elegant way to model irregular and continuous data. When successive observations are dependent, future values may be predicted from past observations, and target parameters can be estimated. These may include expected values of groundwater levels, or probabilities that critical levels are exceeded at certain times or during certain periods. These target parameters are estimated with the purpose of obtaining characteristics of the development of a certain domain in time and such characteristics can, for instance, be extrapolated to future situations. In a system identification approach, is it possible to establish the dynamic relationship between water table perturbations and climatological events, vegetation, hydrogeological local conditions, management and groundwater abstraction. The aim of this work was demonstrate the use of a physical-based time series model to stablish the relationship between precipitation and water table depths from hydrogeological monitoring data. The results enabled to infer about water table dynamics even when it is affected by different climatological patterns, simulating mean, maximum and minimum states. |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017-01-01 2018-11-26T17:54:29Z 2018-11-26T17:54:29Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1590/2318-0331.0318170071 Rbrh-revista Brasileira De Recursos Hidricos. Porte Alegre: Assoc Brasileira Recursos Hidricos-abrh, v. 23, 11 p., 2017. 1414-381X http://hdl.handle.net/11449/164421 10.1590/2318-0331.0318170071 S2318-03312018000100224 WOS:000438515500007 S2318-03312018000100224.pdf |
url |
http://dx.doi.org/10.1590/2318-0331.0318170071 http://hdl.handle.net/11449/164421 |
identifier_str_mv |
Rbrh-revista Brasileira De Recursos Hidricos. Porte Alegre: Assoc Brasileira Recursos Hidricos-abrh, v. 23, 11 p., 2017. 1414-381X 10.1590/2318-0331.0318170071 S2318-03312018000100224 WOS:000438515500007 S2318-03312018000100224.pdf |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Rbrh-revista Brasileira De Recursos Hidricos |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
11 application/pdf |
dc.publisher.none.fl_str_mv |
Assoc Brasileira Recursos Hidricos-abrh |
publisher.none.fl_str_mv |
Assoc Brasileira Recursos Hidricos-abrh |
dc.source.none.fl_str_mv |
Web of Science reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
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1808129440273661952 |