cff-version: 1.2.0
abstract: "<p>This dataset contains all necessary data to produce the output presented in the paper "Predicting Flood Inundation After a Dike Breach Using a Long Short-Term Memory (LSTM) Neural Network", by L.S. Besseling, A. Bomers and S.J.M.H. Hulscher, published in Hydrology (2024). Included are the code for creating the LSTM neural network, the dataset from a 1D2D hydrodynamic HEC-RAS model on which the network was trained and tested, and helper files for running the code and visualizing results. A more detailed description of the dataset is provided in the Readme. For any further questions on the data, please contact the authors.</p>"
authors:
  - family-names: Besseling
    given-names: L.S.
    orcid: "https://orcid.org/0009-0004-9730-9780"
  - family-names: Bomers
    given-names: A.
  - family-names: Hulscher
    given-names: S. J. M. H.
title: "Data accompanying the publication: Predicting Flood Inundation After a Dike Breach Using a Long Short-Term Memory (LSTM) Neural Network"
keywords:
version: 1
identifiers:
  - type: doi
    value: 10.4121/6fd289d8-ec0e-4dd9-94fd-4566783e9c3d.v1
license: CC BY 4.0
date-released: 2024-09-16