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Analysis and forecasting flood risk mapping of the Medjerda River at Boussalem town, in Tunisia |
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| รหัสดีโอไอ | |
| Creator | 1. Saber Hammami 2. Amel Soualmia 3. Azeddine Kourta |
| Title | Analysis and forecasting flood risk mapping of the Medjerda River at Boussalem town, in Tunisia |
| Publisher | Faculty of Engineering, Khon Kaen University |
| Publication Year | 2566 |
| Journal Title | Engineering and Applied Science Research |
| Journal Vol. | 50 |
| Journal No. | 5 |
| Page no. | 449-457 |
| Keyword | Flooding, Bidimensional model, Hydraulic simulation, Medjerda River, TELEMAC-2D, Flood risk mapping |
| URL Website | https://ph01.tci-thaijo.org/index.php/easr/index |
| Website title | Engineering and Applied Science Research |
| ISSN | 2539-6161 |
| Abstract | This work aims to make a comprehensive analysis of the floods on the crossing part of Boussalem city (North Tunisia) in the framework of possible future scenarios for different return periods. A 2D hydrodynamic model based on TELEMAC-2D for flood simulation is developed taking into account the dynamics of the flows and the floodplains, after processing and analysing the available topographic and hydrological data. A lidar survey and an Ortophoto covering the project area (wadi beds and floodplain) were processed to define the different land use components. They are then converted to produce a bathymetric mesh. Five flood hydrographs corresponding to return periods of 5, 10, 20, 50 and 100 years were constructed based on an analysis of historical floods recorded in Boussalem. After calibration and validation of the model, the main conclusions of the study revealed five representative maps made from the results of the water level heights generated by Telemac2d for the events with different return periods. The final synthetic map presents the development of the spatial distribution of the flood risk over the urban area, it shows that the flooded areas in the city represent respectively 30%, 50% and 86% for the 20, 50 and 100 years return period events, which shows a strong risk for these events. |
