SoftwareApplication
identifier: 10.4121/21946724
name: Code underlying the publication: Forecasting estuarine salt intrusion in the Rhine-Meuse delta using an LSTM model
description: Code underlying the publication: Forecasting estuarine salt intrusion in the Rhine-Meuse delta using an LSTM model
description: 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'.
author: Person
  given name: Bas
  family name: Wullems
  name: Bas Wullems
author: https://orcid.org/0000-0002-6459-9230
author: https://orcid.org/0000-0002-3249-8363
author: 0000-0001-8231-094X
keywords: Machine learning
keywords: chloride
keywords: Water Management
keywords: estuary
keywords: Forecasting
keywords: salt intrusion
keywords: hydrology
keywords: Delta
keywords: LSTM
keywords: river
license:
  creative work: creativeWork
    name: CC0-1.0
reference publication: hess-27-3823-2023

https://orcid.org/0000-0002-6459-9230
type: Person
given name: Claudia
family name: Brauer
name: Claudia Brauer

https://orcid.org/0000-0002-3249-8363
type: Person
given name: Albrecht
family name: Weerts
name: Albrecht Weerts

0000-0001-8231-094X
type: Person
given name: Fedor
family name: Baart
name: Fedor Baart

hess-27-3823-2023
type: ScholarlyArticle
name: Forecasting estuarine salt intrusion in the Rhine–Meuse delta using an LSTM model
pagination: 3823-3850
url: https://doi.org/10.5194%2Fhess-27-3823-2023