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

x choose version: version 2 - 2024-11-18 (latest)

• 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