Code and data underlying the thesis "Evidence-Based Expert Judgment in Flood Risk"

DOI:10.4121/a6333b17-bab2-476f-a636-61244b5c6f9e.v2
The DOI displayed 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/a6333b17-bab2-476f-a636-61244b5c6f9e
Datacite citation style:
Rongen, Guus (2024): Code and data underlying the thesis "Evidence-Based Expert Judgment in Flood Risk". Version 2. 4TU.ResearchData. dataset. https://doi.org/10.4121/a6333b17-bab2-476f-a636-61244b5c6f9e.v2
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

Dataset

choose version:
version 2 - 2024-11-18 (latest)
version 1 - 2024-06-12

This repository contains and describes the data and code base used to generate and support the results of the dissertation "Evidence-Based Expert Judgment in Flood Risk" by Guus Rongen (2024). This thesis investigates the use of structured expert judgment in flood risk assessments through four studies. An overview of the studies, the supporting software, and the license is shown in the README file. Furthermore, separate README files are added to the subdirectories, to describe details on the code and data related to each of the topics.

History

  • 2024-06-12 first online
  • 2024-11-18 published, posted

Publisher

4TU.ResearchData

Format

zip-file containing a variety of python scripts (*.py, *.ipynb) and data files (predominantly: *.csv, *.xlsx, *.sqlite).

Associated peer-reviewed publication

Evidence-Based Expert Judgment in Flood Risk

Funding

  • TKI Deltatechnologie (grant code UTW01) TKI Deltatechnologie

Organizations

TU Delft, Faculty of Civil Engineering and Geosciences, Department of Hydraulic Engineering

DATA

Files (1)