Flood risk assessment of slums in Dhaka city

Abstract

Slums are characterized as some of the most impoverished and vulnerable communities within urban areas. They often face a multitude of challenges, including extreme poverty, social marginalization, and inadequate infrastructure. The poor quality of buildings and the lack of adequate infrastructure further exacerbate the vulnerability of slum dwellers to the impacts of flooding. This study focuses on accurate assessment of flood risk in slum area of the Dhaka metropolitan area, the capital of Bangladesh. The man-machine interactive method was utilized to extract slum information from Sentinel-2A satellite imagery. Thirteen evaluation indicators were selected from the aspects of hazard, sensitivity, exposure, and prevention and mitigation capacity. The fuzzy analytic hierarchy process (FAHP) was employed to determine the relative weights of these indicators. A comprehensive evaluation model for flood disaster risk was established, enabling the determination of the spatial distribution of flood risk in slums of Dhaka city. The results indicate that the flood risk distribution in the slums of Dhaka city exhibits an overall high flood risk. The slums with very high flood risk constitute about 22.035% of the total area and are concentrated in Badda, Khilkhet, and Dakshinkhan districts. Slums with high-risk constitute 41.600% of the total area and are located mainly in Turag, Pallabi, Badda, and Gulshan districts. Those areas with abundant rainfall, dense river networks, and flat topography have higher flood risk in slums compared to other regions. These research findings can be a reference for regional flood risk zoning, prevention, and sustainable development planning.

Keywords:

• Dhaka city
• slums
• fuzzy analytic hierarchy process
• flood risk assessment

Author contributions

Chunlin Pu: Conceptualization, Data curation, Writing – review & editing. Fei Yang: Conceptualization, Validation, Writing – review & editing. Xiuli Wang: Conceptualization, Review & editing.

Data availability statement

The 2006 and 2010 slum datasets used in this study are openly available at https://doi.org/10.1155/2014/172182/dataset.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This research was funded by the National Natural Science Foundation of China (Grant No. 42171079), and the Construction Project of China Knowledge Center for Engineering Sciences and Technology (Grant NO. CKCEST-2023-1-5-1).