Abstract
This study explores flood anticipatory actions in data-scarce urban settings using a Bayesian Decision Framework, focusing on Alexandria, Egypt. Flood forecasts are generated using a coupled ensemble Weather Research and Forecasting (WRF) and a MIKE urban inundation model. Actions are guided by probability density functions of flood depth and loss functions. The framework enables decisions to be updated 12–72 hours before events by selecting the actions that minimise expected losses. Results show that such probabilistic approaches can improve decision-making under uncertainty compared to ensemble means, but consideration is needed for a suitable loss function, which represents the decision maker's preference.
| Original language | English |
|---|---|
| Title of host publication | Book of Extended Abstracts of the 41st IAHR World Congress, 2025 |
| Editors | Adrian Wing-Keung Law, Jenn Wei Er |
| Publisher | IAHR |
| Pages | 756-758 |
| Number of pages | 3 |
| ISBN (Print) | 9789083558950 |
| Publication status | Published - 2025 |
| Event | 41st IAHR World Congress, 2025 - Singapore EXPO, Singapore, Singapore Duration: 22 Jun 2025 → 27 Jun 2025 https://www.iahr.org/index/detail/1961 |
Publication series
| Name | Proceedings of the IAHR World Congress |
|---|---|
| ISSN (Print) | 2521-7119 |
| ISSN (Electronic) | 2521-716X |
Conference
| Conference | 41st IAHR World Congress, 2025 |
|---|---|
| Country/Territory | Singapore |
| City | Singapore |
| Period | 22/06/25 → 27/06/25 |
| Internet address |
Keywords
- Bayesian Decision Framework
- Disaster Risk Reduction
- Early Warning Systems
- Urban Flood Forecasting
