Wullems, Bas; Brauer, Claudia; Albrecht Weerts; Baart, Fedor (2023): Code underlying the publication: Forecasting estuarine salt intrusion in the Rhine-Meuse delta using an LSTM model. Version 1. 4TU.ResearchData. software. https://doi.org/10.4121/21946724.v1

Software

x choose version: version 3 - 2023-12-05 (latest) version 2 - 2023-09-25

• Land and Water Management
• Other Environmental Sciences
• Physical and Chemical Conditions of Water
• Other Earth Sciences
• Earth Sciences
• Environmental Sciences
• Environment

chloride, Delta, Estuary, Forecasting, Hydrology, LSTM, Machine learning, river, Salt intrusion, Water management

2011-2020

CC0

RefWorks, BibTeX, Reference Manager, Endnote, DataCite, NLM, DC, CFF

by Bas Wullems , Claudia Brauer , Albrecht Weerts , Fedor Baart

 

Machine learning model for predicting salt concentrations in the Rhine-Meuse delta.

The folder 'Data' contains processed data, identical to 'Features.csv' in the raw dataset.

The folder 'Models' contains an ensemble of LSTM models created with the script 'LSTMv1.py'.

The script 'preprocessing.py' was used to convert the raw data to the daily data in 'Features.csv'.

• 2023-09-08 first online, published, posted

4TU.ResearchData

Python scripts, models created in python, csv and txt data files

Predicting estuarine salt intrusion in the Rhine-Meuse delta using an LSTM model

• https://github.com/BasWullems/salt_intrusion_lstm
• https://waterinfo.rws.nl/#!/nav/expert/
• https://www.knmi.nl/nederland-nu/klimatologie/daggegevens

• https://waterinfo.rws.nl/#!/nav/expert/

https://github.com/BasWullems/salt_intrusion_lstm

• NWO perspectief P18-32

Wageningen University and Research, Hydrology and Quantitative Water Management Group
Deltares, Department of Operational Water Management & Early Warning, Unit of Inland Water Systems
TU Delft, Faculty of Civil Engineering and Geosciences, Department of Hydraulic Engineering