EGU22-2418, updated on 09 May 2022
EGU General Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Flood risk mapping using multi-criteria analysis (TOPSIS) model through geospatial techniques- A case study of the Navsari city, Gujarat, India

Azazkhan Ibrahimkhan Pathan1, Dr. Prasit Girish Agnihotri1, Dr. Saif Said2, Dr. Dhruvesh Patel3, Dr. Cristina Prieto4, Usman Mohsini1, Nilesh Patidar1, Dr.Pankaj Gandhi5, Khushboo Jariwala1, Bojan Đurin6, Mohammad Yasin Azimi1, Juma Rasuli7, Kalyan Dummu1, Saran Raaj1, Arbaaz A. Shaikh8, and Muqadar Salihi1
Azazkhan Ibrahimkhan Pathan et al.
  • 1Department of Civil Engineering, Sardar Vallabhbhai National Institute of Technology, Surat, Gujarat, India
  • 2Department of Civil Engineering, Aligarh Muslim University, Aligarh, Uttar Pradesh, India
  • 3Department of Civil Engineering, School of Technology, Pandit Deendayal Energy University, Gandhinagar, Gujarat, India
  • 4IHCantabria – Instituto de Hidráulica Ambiental de la Universidad de Cantabria, Santander, Spain
  • 5Research Dean, Bhagvan Mahavir University, Surat, Gujarat, india
  • 6University North, Department of Civil Engineering, Varaždin, Croatia
  • 7Ph.D Scholar at Veer Narmad South Gujarat University.
  • 8Dr. S. & S.S. Ghandhy Government Engineering College,Surat, Gujarat, India

Flood is one of the most devastating natural disasters that cause enormous socioeconomic and environmental destruction. The severity of flood losses has evoked emphasis on more comprehensive and vigorous flood modeling techniques for alleviating flood damages. Flood vulnerability in Navsari is intensifying due to urbanization, industrialization, and population growth. Although there has been a significant increase in research on flood assessment at a local scale in Navsari, there remains a lack of tools developed which utilize the risk map of the city. In response to this prerequisite, in this study we have employed a GIS-based Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) multi-criteria analysis model to develop a flood risk map for Navsari city in Gujarat, India, to determine the vulnerable areas that are more susceptible to flooding. To estimate the extent of flood hazard, vulnerability, and risk intensities in terms of area covered, the city was divided into ten zones (i.e. NC1 to NC10) and classified into five classes: very high, high, moderate, low, and very low. A total of seven hazard forming spatial layers (i.e. slope, elevation, soil, rainfall, flow accumulation, distance to a river, and drainage density) and seven vulnerability forming spatial layers (i.e. female population, population density, land use, household, distance to hospital, road network density, and literacy rate) were appraised for evaluating the risk of flooding. The generated flood risk map has been compared with the extent of flood calculated based on field data collected from thirty-six random places. The outcome of the model unveiled the capability of the TOPSIS model since it capitulate low RMSE value varied between 0.95 to 0.43 and high R square value ranged from 0.78 to 0.95. The zones indicated under ‘high’ and ‘very high’ categories (i.e. NC8, NC6, NC4, NC1, NC7, and NC10) demand abrupt flood control action to alleviate the severity of flood risk and subsequent damages. The approach implemented in the study can be applied to any flood-sensitive region around the globe to accurately evaluate the risk of flood. Lastly, flood risk mapping using TOPSIS based geospatial techniques divulge the novel and efficacious approach, especially for data-sparse regions.

How to cite: Pathan, A. I., Agnihotri, Dr. P. G., Said, Dr. S., Patel, Dr. D., Prieto, Dr. C., Mohsini, U., Patidar, N., Gandhi, Dr. P., Jariwala, K., Đurin, B., Azimi, M. Y., Rasuli, J., Dummu, K., Raaj, S., Shaikh, A. A., and Salihi, M.: Flood risk mapping using multi-criteria analysis (TOPSIS) model through geospatial techniques- A case study of the Navsari city, Gujarat, India, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2418,, 2022.


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