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Novel utilization of simulated runoff as causative parameter to predict the hazard of flash floods

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Abstract

Climate change represents an intractable problem which urges a prompt intervention to be resolved. One of climate change's most destructive calamities is flash flooding. On that caveat, this study tries to identify the zones most susceptible to flash floods by utilizing machine learning technique. Initially, a digital elevation model (DEM) has been utilized to delineate a basin located in the city of New Cairo, Egypt, where the flash floods occur frequently. Subsequentially, 12 flood causative factors were calculated and mapped via ArcMap. Furthermore, the depth of runoff was calculated via HEC-RAS and employed as a flood causative factor. Additionally, both flooded points and flood causative factors have been employed by utilizing the “GARP”* approach to produce the Flood Hazard Map (FHM). The state-of-art in this study is to predict the hazard degree of flash floods by utilizing the simulated runoff depth which has been used as flood causative factor in the selected machine learning technique. The FHM anticipated approximately 20% of the total area to have a very high hazard of floods, whereas, more than two-thirds of the study area has expected to have low and very low flood hazard. In addition, the receiver operating characteristic “ROC” approach has been applied to examine the FHM, which estimated the area under curve as 96.88%. Finally, decision-makers can utilize the generated map to better comprehend repercussion of flooding and make adequate preparations to alleviate this risk. *GARP: “Genetic Algorithm for Rule-set Prediction”.

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Data availability

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

The first author would like to seize the opportunity to thank the Egyptian Ministry of Higher Education (MoHE) for giving him the PhD scholarship. Furthermore, he would like to acknowledge E-JUST, Tokyo Institute of Technology, and JICA for providing the required facilities and software for this research.

Funding

This research has been funded by Egyptian Missions and JICA.

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Authors and Affiliations

  1. Environmental Engineering Department, School of Energy Resources, Environment, Chemical and Petrochemical Engineering, Egypt-Japan University of Science and Technology, E-JUST, Alexandria, 21934, Egypt

    Mohamed Wahba, H. Shokry Hassan & Mahmoud Sharaan

  2. Civil Engineering Department, Faculty of Engineering, Mansoura University, Mansoura, Egypt

    Mohamed Wahba

  3. Electronic Materials Researches Department, Advanced Technology and New Materials Research Institute, City of Scientific Researches and Technological Applications (SRTA-City), New Borg El-Arab City, Alexandria, 21934, Egypt

    H. Shokry Hassan

  4. Civil Engineering Department, Faculty of Engineering, South Valley University, Qena, Egypt

    Wael M. Elsadek

  5. Department of Civil and Environmental Engineering, Tokyo Institute of Technology, Tokyo, Japan

    Mohamed Wahba, Wael M. Elsadek & Shinjiro Kanae

  6. Civil Engineering Department, Faculty of Engineering, Suez Canal University, Ismailia, Egypt

    Mahmoud Sharaan

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  1. Mohamed Wahba
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  2. H. Shokry Hassan
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  3. Wael M. Elsadek
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  4. Shinjiro Kanae
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All authors have contributed in this research during all the scientific steps, starting from laying the research framework, data gathering, modelling, mapping the results, and ending with analysis and discussions.

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Correspondence to Mohamed Wahba.

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Wahba, M., Hassan, H.S., Elsadek, W.M. et al. Novel utilization of simulated runoff as causative parameter to predict the hazard of flash floods. Environ Earth Sci 82, 333 (2023). https://doi.org/10.1007/s12665-023-11007-w

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