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Deep learning shows declining groundwater levels in Germany until 2100 due to climate change

In this study we investigate how climate change will directly influence the groundwater resources in Germany during the 21(st) century. We apply a machine learning groundwater level prediction approach based on convolutional neural networks to 118 sites well distributed over Germany to assess the gr...

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Detalles Bibliográficos
Autores principales: Wunsch, Andreas, Liesch, Tanja, Broda, Stefan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8907324/
https://www.ncbi.nlm.nih.gov/pubmed/35264569
http://dx.doi.org/10.1038/s41467-022-28770-2
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author Wunsch, Andreas
Liesch, Tanja
Broda, Stefan
author_facet Wunsch, Andreas
Liesch, Tanja
Broda, Stefan
author_sort Wunsch, Andreas
collection PubMed
description In this study we investigate how climate change will directly influence the groundwater resources in Germany during the 21(st) century. We apply a machine learning groundwater level prediction approach based on convolutional neural networks to 118 sites well distributed over Germany to assess the groundwater level development under different RCP scenarios (2.6, 4.5, 8.5). We consider only direct meteorological inputs, while highly uncertain anthropogenic factors such as groundwater extractions are excluded. While less pronounced and fewer significant trends can be found under RCP2.6 and RCP4.5, we detect significantly declining trends of groundwater levels for most of the sites under RCP8.5, revealing a spatial pattern of stronger decreases, especially in the northern and eastern part of Germany, emphasizing already existing decreasing trends in these regions. We can further show an increased variability and longer periods of low groundwater levels during the annual cycle towards the end of the century.
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spelling pubmed-89073242022-03-23 Deep learning shows declining groundwater levels in Germany until 2100 due to climate change Wunsch, Andreas Liesch, Tanja Broda, Stefan Nat Commun Article In this study we investigate how climate change will directly influence the groundwater resources in Germany during the 21(st) century. We apply a machine learning groundwater level prediction approach based on convolutional neural networks to 118 sites well distributed over Germany to assess the groundwater level development under different RCP scenarios (2.6, 4.5, 8.5). We consider only direct meteorological inputs, while highly uncertain anthropogenic factors such as groundwater extractions are excluded. While less pronounced and fewer significant trends can be found under RCP2.6 and RCP4.5, we detect significantly declining trends of groundwater levels for most of the sites under RCP8.5, revealing a spatial pattern of stronger decreases, especially in the northern and eastern part of Germany, emphasizing already existing decreasing trends in these regions. We can further show an increased variability and longer periods of low groundwater levels during the annual cycle towards the end of the century. Nature Publishing Group UK 2022-03-09 /pmc/articles/PMC8907324/ /pubmed/35264569 http://dx.doi.org/10.1038/s41467-022-28770-2 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Wunsch, Andreas
Liesch, Tanja
Broda, Stefan
Deep learning shows declining groundwater levels in Germany until 2100 due to climate change
title Deep learning shows declining groundwater levels in Germany until 2100 due to climate change
title_full Deep learning shows declining groundwater levels in Germany until 2100 due to climate change
title_fullStr Deep learning shows declining groundwater levels in Germany until 2100 due to climate change
title_full_unstemmed Deep learning shows declining groundwater levels in Germany until 2100 due to climate change
title_short Deep learning shows declining groundwater levels in Germany until 2100 due to climate change
title_sort deep learning shows declining groundwater levels in germany until 2100 due to climate change
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8907324/
https://www.ncbi.nlm.nih.gov/pubmed/35264569
http://dx.doi.org/10.1038/s41467-022-28770-2
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