Data underlying the publication: Forecasting estuarine salt intrusion in the Rhine-Meuse delta using an LSTM model

doi: 10.4121/21944249.v3
The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/21944249
Datacite citation style:
Wullems, Bas; Brauer, Claudia; Baart, Fedor; Weerts, Albrecht (2023): Data underlying the publication: Forecasting estuarine salt intrusion in the Rhine-Meuse delta using an LSTM model. Version 3. 4TU.ResearchData. dataset. https://doi.org/10.4121/21944249.v3
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Dataset
choose version:
version 3 - 2023-12-05 (latest)
version 2 - 2023-09-25 version 1 - 2023-09-08

Raw and processed data used to build an LSTM model for salt intrusion at Krimpen aan den IJssel in the Rhine-Meuse delta.


Raw water data names are in all capitals and are formatted as VARIABLE_LOCATION_FIRSTYEAR_LASTYEAR_IDENTIFIER.csv


Variables used are:

chloride concentration (CONCTTE)

discharge (Q)

water level (WATHTE)


Locations used are:

Krimpen aan den IJssel (KRIMPADIJSL)

Lekhaven(LEKHVRTOVER)

Hagestein(HAGSBVN)

Lobith(LOBH)

Tiel(TIELWL)

Dordrecht(DORDT)

Hoek van Holland (HOEKVHLD)

Vlaardingen(VLAARDGN)


All these data can also be downloaded from https://waterinfo.rws.nl/#!/nav/expert/. This can be done efficiently with the ddlpy software: https://github.com/openearth/ddlpy.


The file etmgeg_344.txt contains meteorological data mesured in Rotterdam by KNMI (https://www.knmi.nl/nederland-nu/klimatologie/daggegevens)


Features.csv contains daily minimum, mean and maximum values of the water data from Rijkswaterstaat and the wind data from KNMI.



history
  • 2023-09-08 first online
  • 2023-12-05 published, posted
publisher
4TU.ResearchData
format
csv and txt tables
funding
  • NWO perspectief P18-32
organizations
Wageningen University and Research, Hydrology and Quantitative Water Management Group
Deltares, Department of Operational Water Management & Early Warning, Unit of Inland Water Systems

DATA

files (12)