Estimation of the upper bound of seismic hazard curve by using the generalised extreme value distribution

Flash floods are the most common type of natural hazards that cause loss of life and massive damage to economic activities. During the last few decades, their impact increased due to rapid urbanization and settlement in downstream areas, which are desirable place for development. Wadi Asyuti, much like other wadis in the Eastern Desert of Egypt, is prone to flash flood problems. Analysis and interpretation of microwave remotely sensed data obtained from the Shuttle Radar Topography Mission (SRTM) and Tropical Rainfall Measuring Mission (TRMM) data using GIS techniques provided information on physical characteristics of catchments and rainfall zones. These data play a crucial role in mapping flash flood potentials and predicting hydrologic conditions in space and time. In order to delineate flash flood potentials in Wadi Asyuti basin, several morphometric parameters that tend to promote higher flood peak and runoff, including drainage characteristics, basin relief, texture, and geometry were computed, ranked, and combined using several approaches. The resulting flash flood potential maps, categorized the sub-basins into five classes, ranging from very low to very high flood potentials. In addition, integrating the spatially distributed drainage density, rainfall intensity, and slope gradient further highlighted areas of potential flooding within the Wadi Asyuti basin. Processing of recent Landsat-8 imagery acquired on March 15, 2014, validated the flood potential maps and offered an opportunity to measure the extent (200–900 m in width) of the flooding zone within the flash flood event on March 9, 2014, as well as revealed vulnerable areas of social and economic activities. These results demonstrated that excessive rainfall intensity in areas of higher topographic relief, steep slope, and drainage density are the major causes of flash floods. Furthermore, integration of remote sensing data and GIS techniques allowed mapping flood-prone areas in a fast and cost-effective to help decision makers in preventing flood hazards in the future.