摘要
Flash flood is a dangers natural disaster causes lots of structure damage, traffic collapse, economic defects and human life loss. An efficient way to reduce its effects is preparing flash flood mapping to identify zones at risk due to flood. Flash flood mapping is a powerful tool for urban planners, traffic and infrastructure engineers, emergency and rescue services. This article proposes an approach utilizes remote sensing (RS) and geographic information system (GIS) to prepare flood risk code (FRC) map for Jeddah city, Saudi Arabia. The proposed approach applied the Curve Number (CN) method of flood modelling and uses runoff depth, land use, soil hydrological parameters, surface slope, and longest flow path to generate FRC. SPOT satellite image of the study area was classified to generate land use map, Digital Elevation Model (DEM) was used for generating slope map and for hydrology analysis using HEC-GeoHMS tool, and soil properties were generated from scanned soil maps. All data were integrated in ArcGIS 10.4.1 to prepare the final flood risk map. The results show that a precipitation of 106.3 mm will generate 136.5 million m3 of flood water. The results according to the developed flood risk code show that due to this amount of precipitation, about 1 million people live in Jeddah are prone to extreme flood risk and about 2 million of population are at major risk, the rest of population (about 0.5 million) are vulnerable to moderate to minor fold risk. The approach was verified using ground truth data and proofed precision.
Flash flood is a dangers natural disaster causes lots of structure damage, traffic collapse, economic defects and human life loss. An efficient way to reduce its effects is preparing flash flood mapping to identify zones at risk due to flood. Flash flood mapping is a powerful tool for urban planners, traffic and infrastructure engineers, emergency and rescue services. This article proposes an approach utilizes remote sensing (RS) and geographic information system (GIS) to prepare flood risk code (FRC) map for Jeddah city, Saudi Arabia. The proposed approach applied the Curve Number (CN) method of flood modelling and uses runoff depth, land use, soil hydrological parameters, surface slope, and longest flow path to generate FRC. SPOT satellite image of the study area was classified to generate land use map, Digital Elevation Model (DEM) was used for generating slope map and for hydrology analysis using HEC-GeoHMS tool, and soil properties were generated from scanned soil maps. All data were integrated in ArcGIS 10.4.1 to prepare the final flood risk map. The results show that a precipitation of 106.3 mm will generate 136.5 million m3 of flood water. The results according to the developed flood risk code show that due to this amount of precipitation, about 1 million people live in Jeddah are prone to extreme flood risk and about 2 million of population are at major risk, the rest of population (about 0.5 million) are vulnerable to moderate to minor fold risk. The approach was verified using ground truth data and proofed precision.
