Frequency Ratio Model as Tools for Flood Susceptibility Mapping in Urbanized Areas: A Case Study from Egypt

Author:

Megahed Hanaa A.1,Abdo Amira M.1ORCID,AbdelRahman Mohamed A. E.23ORCID,Scopa Antonio4ORCID,Hegazy Mohammed N.1

Affiliation:

1. Division of Geological Applications and Mineral Resources, National Authority for Remote Sensing and Space Sciences (NARSS), Cairo 1564, Egypt

2. Division of Environmental Studies and Land Use, National Authority for Remote Sensing and Space Sciences (NARSS), Cairo 1564, Egypt

3. State Key Laboratory of Efficient Utilization of Arid and Semi-Arid Arable Land in Northern China, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China

4. Scuola di Scienze Agrarie, Forestali, Alimentari ed Ambientali (SAFE), Università degli Studi della Basilicata, Via dell’Ateneo Lucano 10, 85100 Potenza, Italy

Abstract

The occurrence of flash floods is a natural yet unavoidable occurrence over time. In addition to harming people, property, and resources, it also undermines a country’s economy. This paper attempts to identify areas of flood vulnerability using a frequency ratio approach. The frequency ratio (FR) model was used to produce flood prediction maps for New Cairo City, Egypt. Using field data and remote sensing data, 143 spatial flooded point sites were mapped to build a flood inventory map. The primary driving criteria for flash floods were determined to be elevation, slope, aspect, Land Use Land Cover (LULC), lithology, stream distance, stream density, topographic wetness index (TWI), surface runoff, and terrain ruggedness index (TRI), in that order of importance. A flood susceptibility map (FSM) has been created using the FR model, which combines geographical flooded sites and environmental variables. Our findings from FSM, roughly a fifth of the city is very highly susceptible to flooding (19.32%), while the remaining 40.09% and 13.14% of the study area rank very low and low risk, respectively. The receiver operating characteristic curve (ROC) technique was also used to validate the FSM, and the resulting results showed an area under the curve (AUC) of 90.11%. In conclusion, decision makers can employ models to extract and generate flood risk maps in order to better understand the effects of flash floods and to create alternative measures to prevent this hazard in similar regions. The results of this study will aid planners and decision makers in developing some likely actions to reduce floods vulnerability in this area.

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

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