Articles | Volume 25, issue 3
https://doi.org/10.5194/hess-25-1671-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.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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- Final revised paper (published on 01 Apr 2021)
- Supplement to the final revised paper
- Preprint (discussion started on 23 Nov 2020)
- Supplement to the preprint
Interactive discussion
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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RC1: 'The Rabbit and the Turtle: Or, an LSTM, a CNN and a NARX.', Anonymous Referee #1, 23 Dec 2020
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AC1: 'Reply on RC1', Andreas Wunsch, 15 Jan 2021
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AC1: 'Reply on RC1', Andreas Wunsch, 15 Jan 2021
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RC2: 'Groundwater Level Forecasting with Artificial Neural Networks: A Comparison of LSTM, CNN and NARX', Anonymous Referee #2, 24 Dec 2020
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AC2: 'Reply on RC2', Andreas Wunsch, 15 Jan 2021
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AC2: 'Reply on RC2', Andreas Wunsch, 15 Jan 2021
Peer-review completion
AR: Author's response | RR: Referee report | ED: Editor decision
ED: Reconsider after major revisions (further review by editor and referees) (31 Jan 2021) by Mauro Giudici
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AR by Andreas Wunsch on behalf of the Authors (01 Feb 2021) 
Author's response
Author's tracked changes
Manuscript
ED: Referee Nomination & Report Request started (01 Feb 2021) by Mauro Giudici
RR by Anonymous Referee #2 (16 Feb 2021)
RR by Anonymous Referee #1 (01 Mar 2021)
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ED: Publish subject to technical corrections (02 Mar 2021) by Mauro Giudici
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