Code underlying the MSc thesis: Risk-based Decision Framework for Optimizing Temporary Flood Protection Measures

This repository contains the Python source code developed for an MSc thesis on the evaluation of temporary flood protection measures under uncertainty.

The code implements a probabilistic, risk-based decision framework to assess whether temporary flood protection measures are economically and safely justified when permanent reinforcement is planned but not yet implemented. The framework integrates cost–benefit analysis with probabilistic flood risk modelling over a finite planning horizon.

Key input parameters (e.g. flood probability, effectiveness of temporary measures, damage estimates, and time to reinforcement) is addressed using cost-benefit analysis. The scripts generate effectiveness–cost decision maps for a given expected damage, as well as sensitivity indicators that support comparative analysis across scenarios.

The repository includes model implementation scripts and example input data sufficient to reproduce the main analytical results presented in the thesis.

No personal data are used. The research does not involve human subjects or field data collection requiring ethical approval. The code is provided for research and reproducibility purposes and reflects a decision-support framework rather than a prescriptive or operational tool.