The doi 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

Rongen, Guus (2024): Code and data underlying the thesis "Evidence based expert judgment in flood risk". Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/a6333b17-bab2-476f-a636-61244b5c6f9e.v1

Dataset

• Civil Engineering
• Statistics
• Natural Hazards
• Applied Mathematics
• Engineering
• Mathematical Sciences
• Environment

Bayesian Network, Bayesian Statistics, Classical Model, Cooke's Method, Dependence, Dike Safety, Expert Judgment, Extreme Value Analysis, Flood Risk, Hydrology

GPL-3.0

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

by Guus Rongen

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.

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

4TU.ResearchData

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

• https://github.com/grongen/anduryl
• https://github.com/grongen/Matlatzinca
• https://doi.org/10.1016/j.ress.2022.108535
• https://doi.org/10.1016/j.softx.2024.101693
• https://doi.org/10.1016/j.softx.2020.100497

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