%0 Generic
%A Wullems, Bas
%A Brauer, Claudia
%A Baart, Fedor
%A Weerts, Albrecht
%D 2023
%T Data underlying the publication: Forecasting estuarine salt intrusion in the Rhine-Meuse delta using an LSTM model
%U 
%R 10.4121/21944249.v2
%K Hydrology
%K Salt Intrusion
%K LSTM
%K Machine learning
%K estuary
%K Delta
%K water management
%K forecasting
%K Water level
%K Discharge
%X <p>Raw and processed data used to build an LSTM model for salt intrusion at Krimpen aan den IJssel in the Rhine-Meuse delta.</p><p><br></p><p>Raw water data names are in all capitals and are formatted as VARIABLE_LOCATION_FIRSTYEAR_LASTYEAR_IDENTIFIER.csv</p><p><br></p><p>Variables used are:</p><p>chloride concentration (CONCTTE)</p><p>discharge (Q)</p><p>water level (WATHTE)</p><p><br></p><p>Locations used are:</p><p>Krimpen aan den IJssel (KRIMPADIJSL)</p><p>Lekhaven(LEKHVRTOVER)</p><p>Hagestein(HAGSBVN)</p><p>Lobith(LOBH)</p><p>Tiel(TIELWL)</p><p>Dordrecht(DORDT)</p><p>Hoek van Holland (HOEKVHLD)</p><p>Vlaardingen(VLAARDGN)</p><p><br></p><p>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.</p><p><br></p><p>The file etmgeg_344.txt contains meteorological data mesured in Rotterdam by KNMI (https://www.knmi.nl/nederland-nu/klimatologie/daggegevens)</p><p><br></p><p>Features.csv contains daily minimum, mean and maximum values of the water data from Rijkswaterstaat and the wind data from KNMI.</p><p><br></p><p><br></p>
%I 4TU.ResearchData