Skip to main content

Advertisement

Log in

Flood susceptibility assessment and mapping in a monsoon-dominated tropical river basin using GIS-based data-driven bivariate and multivariate statistical models and their ensemble techniques

  • Original Article
  • Published:
Environmental Earth Sciences Aims and scope Submit manuscript

Abstract

Floods constitute the most frequent and damaging natural hazard in monsoon dominated Indian subcontinent. Therefore, flood susceptibility modeling and mapping at basin scale is necessary for implementing management projects to reduce the adverse impact of flood hazards. This study evaluates the efficiency of bivariate frequency ratio (FR), and Dempster-Shafer based evidential belief function (EBF) models in flood susceptibility mapping of the tropical lower Dwarakeswar river basin of India, both individually and in combination with the multivariate logistic regression (LR) model. For this purpose, a flood inventory map (FIM), containing 162 past flood locations was prepared. After multicollinearity testing, the spatial data layers were created for 11 flood-related conditioning factors (FCFs): elevation, slope, sediment transport index (STI), topographic wetness index (TWI), stream power index (SPI), distance from streams, plan curvature, terrain ruggedness index (TRI), lithology, Land use/ cover (LU/LC), and normalized difference vegetation index (NDVI). A total of 113 flood locations (70%) were used for training the models and preparing flood susceptibility maps. The remaining 49 flood points (30%) were used for validating the models and comparing their efficiency using the area under the curve (RoC-AUC) and modified seed cell area index (mSCAI) methods. The validation result indicated that the FR model had the highest predictability (72.26%), and the FR-LR ensemble model had the lowest efficiency (58.65%). All the models showed that the southeastern parts of the study area are most susceptible due to lower elevation and gentle slopes.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

Data availability

All the relevant data have been provided in the tables. Sources of all the data have been described properly. The discharge and gauge data have been collected from Irrigation and Waterways department, Govt. of West Bengal. The DEMs and Landsat imageries used in the present study were freely downloaded from the USGS Earth Explorer website. The District resource maps were available in the Geological Survey of India, Kolkata. The discharge and gauge data were available in the Irrigation and Waterways department of the government of West Bengal.

Code availability

Not applicable.

References

Download references

Acknowledgements

The author is grateful to the Irrigation and Waterways department, Government of West Bengal, for providing necessary data free of cost. The author would also like to thank Mr. Mithun Ray, Assistant Professor, Malda college, for assisting in the fieldwork.

Funding

The work has been carried out under the financial assistance of University Grant commission, New Delhi. University Grants Commission, NO.F.15-9(JULY 2016)/2016(NET).

Author information

Authors and Affiliations

Authors

Contributions

Not applicable.

Corresponding author

Correspondence to Biman Ghosh.

Ethics declarations

Conflict of interest

The authors declare that there is no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ghosh, B. Flood susceptibility assessment and mapping in a monsoon-dominated tropical river basin using GIS-based data-driven bivariate and multivariate statistical models and their ensemble techniques. Environ Earth Sci 82, 28 (2023). https://doi.org/10.1007/s12665-022-10696-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s12665-022-10696-z

Keywords

Navigation