Characterising the flash flood potential in thr arid Red Sea coast region of Egypt
Characterising the flash flood potential in thr arid Red Sea coast region of Egypt
This study presents an integrated approach to estimating the risk of flash floods in arid wadis. Flash floods impact seriously on the infrastructure and development of Egyptian desert towns, such as Marsa Alam, and their surrounding areas. The study developed a method using the example of the wadi El-Alam, which has an area of approximately 407 km2. The method has three stages. First, the construction of a Digital Elevation Model from which morphometric properties of the brain were calculated. In particular, representing the flat areas and the sharp junctions between badland slopes and the adjacent wadi system (which generally characterised arid landscapes), were among the major issues facing this study. Second, the derivation of land cover from satellite remote sensing data which were rigorously pre-processed with the aid of aerial photographs and fieldwork measurements. Third, the application of a hydrological model, incorporating the basin morphometry and land cover data, to transform rainfall into runoff and route the floodwater through the sub-catchments of the wadi.
The hydrological model system (HMS) was run to simulate discharge at the main wadi outlet (where the town of Marsa Alam is located) and at each sub-basin intersecting the Idfu-Alam highway that runs through the wadi. From these results, sites vulnerable to flash flood and their risk classes were identified. The sites judged to have the highest flood hazard along the highway were exactly the sites damaged in the 1991 flash flood. Thus, as an outcome of this study, the first digital database that includes information on land cover, geomorphology and hydrology of wadi El-Alam was developed. This database can be used to highlight regions vulnerable to flood damage.
University of Southampton
Ghoneim, Eman M
c3e8c1f7-304f-4c80-936b-2fae91e79398
2002
Ghoneim, Eman M
c3e8c1f7-304f-4c80-936b-2fae91e79398
Ghoneim, Eman M
(2002)
Characterising the flash flood potential in thr arid Red Sea coast region of Egypt.
University of Southampton, Doctoral Thesis.
Record type:
Thesis
(Doctoral)
Abstract
This study presents an integrated approach to estimating the risk of flash floods in arid wadis. Flash floods impact seriously on the infrastructure and development of Egyptian desert towns, such as Marsa Alam, and their surrounding areas. The study developed a method using the example of the wadi El-Alam, which has an area of approximately 407 km2. The method has three stages. First, the construction of a Digital Elevation Model from which morphometric properties of the brain were calculated. In particular, representing the flat areas and the sharp junctions between badland slopes and the adjacent wadi system (which generally characterised arid landscapes), were among the major issues facing this study. Second, the derivation of land cover from satellite remote sensing data which were rigorously pre-processed with the aid of aerial photographs and fieldwork measurements. Third, the application of a hydrological model, incorporating the basin morphometry and land cover data, to transform rainfall into runoff and route the floodwater through the sub-catchments of the wadi.
The hydrological model system (HMS) was run to simulate discharge at the main wadi outlet (where the town of Marsa Alam is located) and at each sub-basin intersecting the Idfu-Alam highway that runs through the wadi. From these results, sites vulnerable to flash flood and their risk classes were identified. The sites judged to have the highest flood hazard along the highway were exactly the sites damaged in the 1991 flash flood. Thus, as an outcome of this study, the first digital database that includes information on land cover, geomorphology and hydrology of wadi El-Alam was developed. This database can be used to highlight regions vulnerable to flood damage.
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Published date: 2002
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Local EPrints ID: 464705
URI: http://eprints.soton.ac.uk/id/eprint/464705
PURE UUID: 55e9d557-7345-4202-a0dc-a5d55d075642
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Date deposited: 04 Jul 2022 23:57
Last modified: 16 Mar 2024 19:42
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Author:
Eman M Ghoneim
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