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Automated Time Series Modeling for Piezometers in the National Database of the Netherlands
The Geological Survey of the Netherlands (TNO‐GSN) maintains a public national database of groundwater head observations. Transfer function‐noise modeling has been applied to the time series in order to extract the impulse response functions for precipitation and evaporation for each piezometer. An...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Blackwell Publishing Ltd
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7379626/ https://www.ncbi.nlm.nih.gov/pubmed/30105748 http://dx.doi.org/10.1111/gwat.12819 |
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author | Zaadnoordijk, Willem J. Bus, Stefanie A.R. Lourens, Aris Berendrecht, Wilbert L. |
author_facet | Zaadnoordijk, Willem J. Bus, Stefanie A.R. Lourens, Aris Berendrecht, Wilbert L. |
author_sort | Zaadnoordijk, Willem J. |
collection | PubMed |
description | The Geological Survey of the Netherlands (TNO‐GSN) maintains a public national database of groundwater head observations. Transfer function‐noise modeling has been applied to the time series in order to extract the impulse response functions for precipitation and evaporation for each piezometer. An automated procedure has been developed to assess the quality of the time series and of the models. The time series models of sufficient quality offer far more homogeneous data on the piezometric head than the original measurements. This allows for improved mapping of the head at a specific date or of characteristics of the head like average summer or winter levels. Also, the separation of precipitation and evaporation from other influences is useful for groundwater management and policy. The individual time series models are available online with interactive graphics (https://www.grondwatertools.nl/grondwatertools‐viewer). The spatial patterns of the impulse response function characteristics can support analyses of the groundwater system. |
format | Online Article Text |
id | pubmed-7379626 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Blackwell Publishing Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-73796262020-07-24 Automated Time Series Modeling for Piezometers in the National Database of the Netherlands Zaadnoordijk, Willem J. Bus, Stefanie A.R. Lourens, Aris Berendrecht, Wilbert L. Ground Water Special Section: Time Series Analysis Guest Editor: Mark Bakker, Ph.D./ The Geological Survey of the Netherlands (TNO‐GSN) maintains a public national database of groundwater head observations. Transfer function‐noise modeling has been applied to the time series in order to extract the impulse response functions for precipitation and evaporation for each piezometer. An automated procedure has been developed to assess the quality of the time series and of the models. The time series models of sufficient quality offer far more homogeneous data on the piezometric head than the original measurements. This allows for improved mapping of the head at a specific date or of characteristics of the head like average summer or winter levels. Also, the separation of precipitation and evaporation from other influences is useful for groundwater management and policy. The individual time series models are available online with interactive graphics (https://www.grondwatertools.nl/grondwatertools‐viewer). The spatial patterns of the impulse response function characteristics can support analyses of the groundwater system. Blackwell Publishing Ltd 2018-09-11 2019 /pmc/articles/PMC7379626/ /pubmed/30105748 http://dx.doi.org/10.1111/gwat.12819 Text en © 2018 The Authors. Groundwater published by Wiley Periodicals, Inc. on behalf of National Ground Water Association. This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. |
spellingShingle | Special Section: Time Series Analysis Guest Editor: Mark Bakker, Ph.D./ Zaadnoordijk, Willem J. Bus, Stefanie A.R. Lourens, Aris Berendrecht, Wilbert L. Automated Time Series Modeling for Piezometers in the National Database of the Netherlands |
title | Automated Time Series Modeling for Piezometers in the National Database of the Netherlands |
title_full | Automated Time Series Modeling for Piezometers in the National Database of the Netherlands |
title_fullStr | Automated Time Series Modeling for Piezometers in the National Database of the Netherlands |
title_full_unstemmed | Automated Time Series Modeling for Piezometers in the National Database of the Netherlands |
title_short | Automated Time Series Modeling for Piezometers in the National Database of the Netherlands |
title_sort | automated time series modeling for piezometers in the national database of the netherlands |
topic | Special Section: Time Series Analysis Guest Editor: Mark Bakker, Ph.D./ |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7379626/ https://www.ncbi.nlm.nih.gov/pubmed/30105748 http://dx.doi.org/10.1111/gwat.12819 |
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