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Long-term, non-anthropogenic groundwater storage changes simulated by three global-scale hydrological models
This study examined long-term, natural (i.e., excluding anthropogenic impacts) variability of groundwater storage worldwide. Groundwater storage changes were estimated by forcing three global-scale hydrological models with three 50+ year meteorological datasets. Evaluation using in situ groundwater...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6656779/ https://www.ncbi.nlm.nih.gov/pubmed/31341252 http://dx.doi.org/10.1038/s41598-019-47219-z |
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author | Li, Bailing Rodell, Matthew Sheffield, Justin Wood, Eric Sutanudjaja, Edwin |
author_facet | Li, Bailing Rodell, Matthew Sheffield, Justin Wood, Eric Sutanudjaja, Edwin |
author_sort | Li, Bailing |
collection | PubMed |
description | This study examined long-term, natural (i.e., excluding anthropogenic impacts) variability of groundwater storage worldwide. Groundwater storage changes were estimated by forcing three global-scale hydrological models with three 50+ year meteorological datasets. Evaluation using in situ groundwater observations from the U.S. and terrestrial water storage derived from the Gravity Recovery and Climate Experiment (GRACE) satellites showed that these models reasonably represented inter-annual variability of water storage, as indicated by correlations greater than 0.5 in most regions. Empirical orthogonal function analysis revealed influences of the El Niño Southern Oscillation (ENSO) on global groundwater storage. Simulated groundwater storage, including its global average, exhibited trends generally consistent with that of precipitation. Global total (natural) groundwater storage decreased over the past 5–7 decades with modeled rates ranging from 0.01 to 2.18 mm year(−1). This large range can be attributed in part to groundwater’s low frequency (inter-decadal) variability, which complicates identification of real long-term trends even within a 50+ year time series. Results indicate that non-anthropogenic variability in groundwater storage is substantial, making knowledge of it fundamental to quantifying direct human impacts on groundwater storage. |
format | Online Article Text |
id | pubmed-6656779 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-66567792019-07-29 Long-term, non-anthropogenic groundwater storage changes simulated by three global-scale hydrological models Li, Bailing Rodell, Matthew Sheffield, Justin Wood, Eric Sutanudjaja, Edwin Sci Rep Article This study examined long-term, natural (i.e., excluding anthropogenic impacts) variability of groundwater storage worldwide. Groundwater storage changes were estimated by forcing three global-scale hydrological models with three 50+ year meteorological datasets. Evaluation using in situ groundwater observations from the U.S. and terrestrial water storage derived from the Gravity Recovery and Climate Experiment (GRACE) satellites showed that these models reasonably represented inter-annual variability of water storage, as indicated by correlations greater than 0.5 in most regions. Empirical orthogonal function analysis revealed influences of the El Niño Southern Oscillation (ENSO) on global groundwater storage. Simulated groundwater storage, including its global average, exhibited trends generally consistent with that of precipitation. Global total (natural) groundwater storage decreased over the past 5–7 decades with modeled rates ranging from 0.01 to 2.18 mm year(−1). This large range can be attributed in part to groundwater’s low frequency (inter-decadal) variability, which complicates identification of real long-term trends even within a 50+ year time series. Results indicate that non-anthropogenic variability in groundwater storage is substantial, making knowledge of it fundamental to quantifying direct human impacts on groundwater storage. Nature Publishing Group UK 2019-07-24 /pmc/articles/PMC6656779/ /pubmed/31341252 http://dx.doi.org/10.1038/s41598-019-47219-z Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Li, Bailing Rodell, Matthew Sheffield, Justin Wood, Eric Sutanudjaja, Edwin Long-term, non-anthropogenic groundwater storage changes simulated by three global-scale hydrological models |
title | Long-term, non-anthropogenic groundwater storage changes simulated by three global-scale hydrological models |
title_full | Long-term, non-anthropogenic groundwater storage changes simulated by three global-scale hydrological models |
title_fullStr | Long-term, non-anthropogenic groundwater storage changes simulated by three global-scale hydrological models |
title_full_unstemmed | Long-term, non-anthropogenic groundwater storage changes simulated by three global-scale hydrological models |
title_short | Long-term, non-anthropogenic groundwater storage changes simulated by three global-scale hydrological models |
title_sort | long-term, non-anthropogenic groundwater storage changes simulated by three global-scale hydrological models |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6656779/ https://www.ncbi.nlm.nih.gov/pubmed/31341252 http://dx.doi.org/10.1038/s41598-019-47219-z |
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