Communicating uncertainty about groundwater scenarios using stochastic simulation of water table depths time series
Autor(a) principal: | |
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Data de Publicação: | 2012 |
Outros Autores: | |
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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Repositório Institucional da UNESP |
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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 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/conferenceObject |
format |
conferenceObject |
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) |
repository.mail.fl_str_mv |
|
_version_ |
1808129548623020032 |