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Photo of Amir Naghibi

Amir Naghibi

Researcher

Photo of Amir Naghibi

Development of novel hybridized models for urban flood susceptibility mapping

Author

  • Omid Rahmati
  • Hamid Darabi
  • Mahdi Panahi
  • Zahra Kalantari
  • Seyed Amir Naghibi
  • Carla Sofia Santos Ferreira
  • Aiding Kornejady
  • Zahra Karimidastenaei
  • Farnoush Mohammadi
  • Stefanos Stefanidis
  • Dieu Tien Bui
  • Ali Torabi Haghighi
Show all

Summary, in English

Floods in urban environments often result in loss of life and destruction of property, with many negative socio-economic effects. However, the application of most flood prediction models still remains challenging due to data scarcity. This creates a need to develop novel hybridized models based on historical urban flood events, using, e.g., metaheuristic optimization algorithms and wavelet analysis. The hybridized models examined in this study (Wavelet-SVR-Bat and Wavelet-SVR-GWO), designed as intelligent systems, consist of a support vector regression (SVR), integrated with a combination of wavelet transform and metaheuristic optimization algorithms, including the grey wolf optimizer (GWO), and the bat optimizer (Bat). The efficiency of the novel hybridized and standalone SVR models for spatial modeling of urban flood inundation was evaluated using different cutoff-dependent and cutoff-independent evaluation criteria, including area under the receiver operating characteristic curve (AUC), Accuracy (A), Matthews Correlation Coefficient (MCC), Misclassification Rate (MR), and F-score. The results demonstrated that both hybridized models had very high performance (Wavelet-SVR-GWO: AUC = 0.981, A = 0.92, MCC = 0.86, MR = 0.07; Wavelet-SVR-Bat: AUC = 0.972, A = 0.88, MCC = 0.76, MR = 0.11) compared with the standalone SVR (AUC = 0.917, A = 0.85, MCC = 0.7, MR = 0.15). Therefore, these hybridized models are a promising, cost-effective method for spatial modeling of urban flood susceptibility and for providing in-depth insights to guide flood preparedness and emergency response services.

Department/s

  • Division of Water Resources Engineering
  • Centre for Advanced Middle Eastern Studies (CMES)
  • MECW: The Middle East in the Contemporary World

Publishing year

2020

Language

English

Publication/Series

Scientific Reports

Volume

10

Issue

1

Document type

Journal article

Publisher

Nature Publishing Group

Topic

  • Water Engineering

Status

Published

ISBN/ISSN/Other

  • ISSN: 2045-2322