Urban flood susceptibility zonation mapping using evidential belief function, frequency ratio and fuzzy gamma operator models in GIS: a case study of Greater Mumbai, Maharashtra, India

Abstract

Greater Mumbai is one of the major sufferers of urban flood in India. In the present study, flood susceptibility zonation (FSZ) mapping of Greater Mumbai were performed using Geographical Information Systems (GIS) based models, evidential belief function (EBF), frequency ratio (FR), fuzzy gamma operator (FGO). For FSZ mapping, 12 conditioning factors were considered which included elevation, slope, plan curvature, topographic wetness index, stream power index, built-up index, geology, soil type, land use land cover, modified Fournier index, proximity to natural drainage and proximity to sewers and storm water drainage. The flood inventory database was divided into training and test data. The factor maps were integrated using GIS. The FSZ map was validated using area under curve (AUC) method. The AUC values of prediction rate using test data for FR, FGO, and EBF models were 0.7400, 0.7231 and 0.7268 respectively. The accuracy assessment of all three models shows fair prediction accuracy.

Keywords:

• Urban flood susceptibility zonation
• frequency ratio
• fuzzy gamma operator
• evidential belief function
• geographical information systems
• Greater Mumbai

Subject classification codes:

• Remote sensing
• geographical information systems (GIS)
• natural disaster mapping
• statistical models

Acknowledgements

The authors acknowledge the Storm Water Drainage Planning Cell, Municipal Corporation of Greater Mumbai (MCGM), Engineers Hub, Worli, Mumbai, for providing inventory of ward-wise urban flood vulnerable sites in Greater Mumbai. We sincerely thank the anonymous reviewer’s for their valuable and comments and suggestions, which help us to improve the quality of the manuscript.

Disclosure statement

No potential conflict of interest was reported by the author(s).