|
View: |
Part 1: Document Description
|
|
Citation |
|
|---|---|
|
Title: |
Using Long Short-Term Memory networks to connect water table depth anomalies to precipitation anomalies over Europe |
|
Identification Number: |
doi:10.26165/JUELICH-DATA/WPRA1F |
|
Distributor: |
Jülich DATA |
|
Date of Distribution: |
2021-05-31 |
|
Version: |
1 |
|
Bibliographic Citation: |
Ma, Yueling; Montzka, Carsten; Bayat, Bagher; Kollet, Stefan, 2021, "Using Long Short-Term Memory networks to connect water table depth anomalies to precipitation anomalies over Europe", https://doi.org/10.26165/JUELICH-DATA/WPRA1F, Jülich DATA, V1 |
|
Citation |
|
|
Title: |
Using Long Short-Term Memory networks to connect water table depth anomalies to precipitation anomalies over Europe |
|
Identification Number: |
doi:10.26165/JUELICH-DATA/WPRA1F |
|
Authoring Entity: |
Ma, Yueling (Forschungszentrum Jülich) |
|
Montzka, Carsten (Forschungszentrum Jülich) |
|
|
Bayat, Bagher (Forschungszentrum Jülich) |
|
|
Kollet, Stefan (Forschungszentrum Jülich) |
|
|
Distributor: |
Jülich DATA |
|
Access Authority: |
Ma, Yueling |
|
Depositor: |
Ma, Yueling |
|
Date of Deposit: |
2021-05-27 |
|
Study Scope |
|
|
Keywords: |
Earth and Environmental Sciences, Groundwater, Long Short-Term Memory (LSTM) networks, Anomalies, Europe |
|
Abstract: |
This study utilized spatiotemporally continuous precipitation anomaly (pr_a) and water table depth anomaly (wtd_a) from integrated hydrologic simulation results (i.e., the TSMP-G2A data set) over Europe in combination with Long Short-Term Memory (LSTM) networks to capture the time-varying and time-lagged relationship between pr_a and wtd_a in order to obtain reliable models to estimate wtd_a at the individual pixel level. The data files provide the TSMP-G2A pr_a, the TSMP-G2A wtd_a, and the LSTM wtd_a data from 1996 to 2016, with a spatial resolution of 0.11 degree. |
|
Methodology and Processing |
|
|
Sources Statement |
|
|
Data Access |
|
|
Notes: |
CC0 Waiver |
|
Other Study Description Materials |
|
|
Related Publications |
|
|
Citation |
|
|
Identification Number: |
10.5194/hess-25-3555-2021 |
|
Bibliographic Citation: |
Ma, Y., Montzka, C., Bayat, B. and Kollet, S.: Using Long Short-Term Memory networks to connect water table depth anomalies to precipitation anomalies over Europe, Hydrol. Earth Syst. Sci., 25(6), 3555–3575, 2021. |
|
Label: |
LSTM_monthly_groundwater_table_depth_anomaly_FZJ-IBG3_LSTM_0.1_degree_v1.1996_2016.nc |
|
Text: |
Monthly groundwater table depth anomalies generated from the proposed LSTM networks |
|
Notes: |
application/x-netcdf |
|
Label: |
TSMP_G2A_monthly_groundwater_table_depth_anomaly_FZJ-IBG3_TSMP_0.1_degree_v1.1996_2016.nc |
|
Text: |
Monthly groundwater table depth anomalies calculated from the TSMP-G2A data set |
|
Notes: |
application/x-netcdf |
|
Label: |
TSMP_G2A_monthly_precipitation_anomaly_FZJ-IBG3_TSMP_0.1_degree_v1.1996_2016.nc |
|
Text: |
Monthly precipitation anomalies calculated from the TSMP-G2A data set |
|
Notes: |
application/x-netcdf |