Articles | Volume 25, issue 6
Hydrol. Earth Syst. Sci., 25, 3555–3575, 2021
https://doi.org/10.5194/hess-25-3555-2021
Hydrol. Earth Syst. Sci., 25, 3555–3575, 2021
https://doi.org/10.5194/hess-25-3555-2021

Research article 23 Jun 2021

Research article | 23 Jun 2021

Using Long Short-Term Memory networks to connect water table depth anomalies to precipitation anomalies over Europe

Yueling Ma et al.

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Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Publish subject to revisions (further review by editor and referees) (18 Nov 2020) by Zhongbo Yu
AR by Yueling Ma on behalf of the Authors (22 Dec 2020)  Author's response    Author's tracked changes    Manuscript
ED: Referee Nomination & Report Request started (28 Dec 2020) by Zhongbo Yu
RR by Anonymous Referee #1 (02 Jan 2021)
RR by Anonymous Referee #3 (09 Feb 2021)
ED: Publish subject to revisions (further review by editor and referees) (14 Feb 2021) by Zhongbo Yu
AR by Yueling Ma on behalf of the Authors (10 Mar 2021)  Author's response    Author's tracked changes    Manuscript
ED: Referee Nomination & Report Request started (11 Mar 2021) by Zhongbo Yu
RR by Anonymous Referee #1 (16 Mar 2021)
RR by Anonymous Referee #4 (16 May 2021)
ED: Publish subject to minor revisions (review by editor) (20 May 2021) by Zhongbo Yu
AR by Yueling Ma on behalf of the Authors (21 May 2021)  Author's response    Author's tracked changes    Manuscript
ED: Publish as is (22 May 2021) by Zhongbo Yu
AR by Yueling Ma on behalf of the Authors (31 May 2021)  Author's response    Manuscript
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Short summary
This study utilized spatiotemporally continuous precipitation anomaly (pra) and water table depth anomaly (wtda) data from integrated hydrologic simulation results over Europe in combination with Long Short-Term Memory (LSTM) networks to capture the time-varying and time-lagged relationship between pra and wtda in order to obtain reliable models to estimate wtda at the individual pixel level.