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Quantification and possible causes of declining groundwater resources in the Euro-Mediterranean region from 2003 to 2020
Quantification and possible causes of declining groundwater resources in the Euro-Mediterranean region from 2003 to 2020
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Artículo 		Añadir a Mi Portal

Quantification and possible causes of declining groundwater resources in the Euro-Mediterranean region from 2003 to 2020

Xanke, Julian ; Liesch, Tanja

Hydrogeology journal, 2022-03, Vol.30 (2), p.379-400 [Revista revisada por pares]

Berlin/Heidelberg: Springer Berlin Heidelberg

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2
Field Screening Europe 2001
Field Screening Europe 2001
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Libro 		Añadir a Mi Portal

Field Screening Europe 2001

Wolfgang Breh Johannes Gottlieb; Heinz Hötzl; Frieder Kern; Tanja Liesch; Reinhard Niessner

Springer Netherlands 2002

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3
Feature-based Groundwater Hydrograph Clustering Using Unsupervised Self-Organizing Map-Ensembles
Feature-based Groundwater Hydrograph Clustering Using Unsupervised Self-Organizing Map-Ensembles
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Feature-based Groundwater Hydrograph Clustering Using Unsupervised Self-Organizing Map-Ensembles

Wunsch, Andreas ; Liesch, Tanja ; Broda, Stefan

Water resources management, 2022, Vol.36 (1), p.39-54 [Revista revisada por pares]

Dordrecht: Springer Netherlands

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4
Deep learning shows declining groundwater levels in Germany until 2100 due to climate change
Deep learning shows declining groundwater levels in Germany until 2100 due to climate change
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Deep learning shows declining groundwater levels in Germany until 2100 due to climate change

Wunsch, Andreas ; Liesch, Tanja ; Broda, Stefan

Nature communications, 2022-03, Vol.13 (1), p.1221-1221, Article 1221 [Revista revisada por pares]

England: Nature Publishing Group

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5
Comparison of GRACE data and groundwater levels for the assessment of groundwater depletion in Jordan
Comparison of GRACE data and groundwater levels for the assessment of groundwater depletion in Jordan
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Comparison of GRACE data and groundwater levels for the assessment of groundwater depletion in Jordan

Liesch, Tanja ; Ohmer, Marc

Hydrogeology journal, 2016-09, Vol.24 (6), p.1547-1563 [Revista revisada por pares]

Berlin/Heidelberg: Springer Berlin Heidelberg

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6
Karst spring discharge modeling based on deep learning using spatially distributed input data
Karst spring discharge modeling based on deep learning using spatially distributed input data
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Karst spring discharge modeling based on deep learning using spatially distributed input data

Wunsch, Andreas ; Liesch, Tanja ; Cinkus, Guillaume ; Ravbar, NataÅ¡a ; Chen, Zhao ; Mazzilli, Naomi ; Jourde, Hervé ; Goldscheider, Nico

Hydrology and earth system sciences, 2022-05, Vol.26 (9), p.2405-2430 [Revista revisada por pares]

Katlenburg-Lindau: Copernicus GmbH

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7
Forecasting groundwater levels using nonlinear autoregressive networks with exogenous input (NARX)
Forecasting groundwater levels using nonlinear autoregressive networks with exogenous input (NARX)
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Forecasting groundwater levels using nonlinear autoregressive networks with exogenous input (NARX)

Wunsch, Andreas ; Liesch, Tanja ; Broda, Stefan

Journal of hydrology (Amsterdam), 2018-12, Vol.567, p.743-758 [Revista revisada por pares]

Elsevier B.V

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8
Aquifer responses to long-term climatic periodicities
Aquifer responses to long-term climatic periodicities
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Aquifer responses to long-term climatic periodicities

Liesch, Tanja ; Wunsch, Andreas

Journal of hydrology (Amsterdam), 2019-05, Vol.572, p.226-242 [Revista revisada por pares]

Elsevier B.V

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9
Application of machine learning and deep neural networks for spatial prediction of groundwater nitrate concentration to improve land use management practices
Application of machine learning and deep neural networks for spatial prediction of groundwater nitrate concentration to improve land use management practices
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Application of machine learning and deep neural networks for spatial prediction of groundwater nitrate concentration to improve land use management practices

Karimanzira, Divas ; Weis, Jonas ; Wunsch, Andreas ; Ritzau, Linda ; Liesch, Tanja ; Ohmer, Marc

Frontiers in water, 2023-07, Vol.5 [Revista revisada por pares]

Frontiers Media S.A

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10
Groundwater level forecasting with artificial neural networks: a comparison of long short-term memory (LSTM), convolutional neural networks (CNNs), and non-linear autoregressive networks with exogenous input (NARX)
Groundwater level forecasting with artificial neural networks: a comparison of long short-term memory (LSTM), convolutional neural networks (CNNs), and non-linear autoregressive networks with exogenous input (NARX)
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Groundwater level forecasting with artificial neural networks: a comparison of long short-term memory (LSTM), convolutional neural networks (CNNs), and non-linear autoregressive networks with exogenous input (NARX)

Wunsch, Andreas ; Liesch, Tanja ; Broda, Stefan

Hydrology and earth system sciences, 2021-04, Vol.25 (3), p.1671-1687 [Revista revisada por pares]

Katlenburg-Lindau: Copernicus GmbH

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por este autor/creador:

  1. Gottlieb, J
  2. Kern, F
  3. Liesch, T
  4. Hötzl, H
  5. Breh, W

con este tema:

  1. Science & Technology
  2. Hydrogeology
  3. Physical Sciences
  4. Water Resources
  5. Groundwater

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