10 - Flood-Hazard Assessment Modeling Using Multicriteria Analysis and GIS: A Case Study—Ras Gharib Area, Egypt

Abstract

Nowadays, the use of Geographic Information Systems (GIS) is emerging as a powerful tool for assessment of different types of natural hazards. Flash floods are among the most severe natural hazards, and have disastrous socioeconomic impacts. Therefore, it is urgent for flash flood susceptibility maps to be developed to delineate flood-prone areas. These maps would help the authorities, planners, and decision makers to make rapid assessments and take appropriate actions to reduce and minimize the consequences of potential impacts from flash floods. This study addresses the characterization of flash flood susceptibility along some watersheds that drain their water towards the Ras Gharib area, located along the west coast of the Gulf of Suez, Egypt. The Ras Gharib area is frequently affected by flash floods, causing death, and damage to buildings, infrastructures, and vehicles. One of these flash floods happened on October 18, 2016, when the area was impacted by a disastrous flash flood causing a death toll of 22 people and enormous damage to infrastructure and residential areas. In the current study, multicriteria analysis, using the Analytical Hierarchy Process (AHP) and GIS techniques, was carried out to establish a flood susceptibility map for the study area, through the combination of different flood-related factors. Different methods were applied to assess the reliability and credibility of the proposed model. The validation datasets extracted from high-resolution images acquired after the catastrophic flood event on October 18, 2016, using a slicing technique were used to evaluate the flood susceptibility map using the prediction rate method. The results of the accuracy assessment showed a prediction rate of 83.3% for the AHP model. In addition, another verification method was used by comparing the historical records of flash flood events with the susceptibility of flash flood zones. The results indicated that 76% of the historical data plotted into high and very high susceptible zones, 19.1% appearing in the moderately susceptible zone, and 4.7% falling in the low and very low susceptibility zones. Our findings state that the proposed model is very suitable for flash flood susceptibility analysis and could be useful for engineers, planners, and decision makers in spatial planning and flash flood-hazard management.