Communicating uncertainty about groundwater scenarios using stochastic simulation of water table depths time series

Detalhes bibliográficos
Autor(a) principal: Manzione, Rodrigo Lilla [UNESP]
Data de Publicação: 2012
Outros Autores: Wendland, Edson
Tipo de documento: Artigo de conferência
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://hdl.handle.net/11449/228171
Resumo: Time series modeling provides an empirical stochastic method to model monitoring data from observation wells, without the complexity of physical mechanistic models. In the same direction, geostatiscal methods are used to make probabilistic statements about quantities of interest at non-measured locations. The aim of this work was to present water-table levels scenarios results of a combination of time series modeling and geostatistics to predict and discuss the communication via probability maps. The study case was held in a watershed located in an outcrop of the Guarani Aquifer System (GAS). The Onça Creek watershed has a monitoring scheme with 23 wells spatially distributed over the area. The water heads are measured with a semi-monthly frequency. First, the time series are inspected and modeled with a special type of Transfer-function noise model, the so called PIRFICT-model and then the model outputs are interpolated spatially using geostatistics. How communicate this results is discussed via the resulted maps that contain probabilistic measures about model uncertainty. Understand uncertainty and communicate it to practitioners, decision makers and stakeholders in a clear and simple form is a key element for efficient water resources planning.
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spelling Communicating uncertainty about groundwater scenarios using stochastic simulation of water table depths time seriesGeostatisticsGroundwaterLand use planningTime seriesTime series modeling provides an empirical stochastic method to model monitoring data from observation wells, without the complexity of physical mechanistic models. In the same direction, geostatiscal methods are used to make probabilistic statements about quantities of interest at non-measured locations. The aim of this work was to present water-table levels scenarios results of a combination of time series modeling and geostatistics to predict and discuss the communication via probability maps. The study case was held in a watershed located in an outcrop of the Guarani Aquifer System (GAS). The Onça Creek watershed has a monitoring scheme with 23 wells spatially distributed over the area. The water heads are measured with a semi-monthly frequency. First, the time series are inspected and modeled with a special type of Transfer-function noise model, the so called PIRFICT-model and then the model outputs are interpolated spatially using geostatistics. How communicate this results is discussed via the resulted maps that contain probabilistic measures about model uncertainty. Understand uncertainty and communicate it to practitioners, decision makers and stakeholders in a clear and simple form is a key element for efficient water resources planning.UNESP/Campus of Ourinhos, Av. Vitalina Marcusso 1500USP EESC SHS, Av. Trabalhador Sãocarlence 400UNESP/Campus of Ourinhos, Av. Vitalina Marcusso 1500Universidade Estadual Paulista (UNESP)Universidade de São Paulo (USP)Manzione, Rodrigo Lilla [UNESP]Wendland, Edson2022-04-29T07:43:53Z2022-04-29T07:43:53Z2012-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject400-405Accuracy 2012 - Proceedings of the 10th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences, p. 400-405.http://hdl.handle.net/11449/2281712-s2.0-84975701840Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengAccuracy 2012 - Proceedings of the 10th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciencesinfo:eu-repo/semantics/openAccess2024-06-26T20:11:09Zoai:repositorio.unesp.br:11449/228171Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T23:45:07.230455Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Communicating uncertainty about groundwater scenarios using stochastic simulation of water table depths time series
title Communicating uncertainty about groundwater scenarios using stochastic simulation of water table depths time series
spellingShingle Communicating uncertainty about groundwater scenarios using stochastic simulation of water table depths time series
Manzione, Rodrigo Lilla [UNESP]
Geostatistics
Groundwater
Land use planning
Time series
title_short Communicating uncertainty about groundwater scenarios using stochastic simulation of water table depths time series
title_full Communicating uncertainty about groundwater scenarios using stochastic simulation of water table depths time series
title_fullStr Communicating uncertainty about groundwater scenarios using stochastic simulation of water table depths time series
title_full_unstemmed Communicating uncertainty about groundwater scenarios using stochastic simulation of water table depths time series
title_sort Communicating uncertainty about groundwater scenarios using stochastic simulation of water table depths time series
author Manzione, Rodrigo Lilla [UNESP]
author_facet Manzione, Rodrigo Lilla [UNESP]
Wendland, Edson
author_role author
author2 Wendland, Edson
author2_role author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (UNESP)
Universidade de São Paulo (USP)
dc.contributor.author.fl_str_mv Manzione, Rodrigo Lilla [UNESP]
Wendland, Edson
dc.subject.por.fl_str_mv Geostatistics
Groundwater
Land use planning
Time series
topic Geostatistics
Groundwater
Land use planning
Time series
description Time series modeling provides an empirical stochastic method to model monitoring data from observation wells, without the complexity of physical mechanistic models. In the same direction, geostatiscal methods are used to make probabilistic statements about quantities of interest at non-measured locations. The aim of this work was to present water-table levels scenarios results of a combination of time series modeling and geostatistics to predict and discuss the communication via probability maps. The study case was held in a watershed located in an outcrop of the Guarani Aquifer System (GAS). The Onça Creek watershed has a monitoring scheme with 23 wells spatially distributed over the area. The water heads are measured with a semi-monthly frequency. First, the time series are inspected and modeled with a special type of Transfer-function noise model, the so called PIRFICT-model and then the model outputs are interpolated spatially using geostatistics. How communicate this results is discussed via the resulted maps that contain probabilistic measures about model uncertainty. Understand uncertainty and communicate it to practitioners, decision makers and stakeholders in a clear and simple form is a key element for efficient water resources planning.
publishDate 2012
dc.date.none.fl_str_mv 2012-01-01
2022-04-29T07:43:53Z
2022-04-29T07:43:53Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
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status_str publishedVersion
dc.identifier.uri.fl_str_mv Accuracy 2012 - Proceedings of the 10th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences, p. 400-405.
http://hdl.handle.net/11449/228171
2-s2.0-84975701840
identifier_str_mv Accuracy 2012 - Proceedings of the 10th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences, p. 400-405.
2-s2.0-84975701840
url http://hdl.handle.net/11449/228171
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Accuracy 2012 - Proceedings of the 10th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 400-405
dc.source.none.fl_str_mv Scopus
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)
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