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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Latest update: 20 Sep 2021
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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.