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One of the most devastating and expensive natural hazards in the world today is flooding. Hence, several attempts have been made by different scholars and researchers across the globe and in Nigeria to study flood vulnerability. These studies focused on assessing either the physical or social components of vulnerability without a holistic assessment of all vulnerability components. A multi-dimensional approach to flood risk assessment is required to provide a holistic view of residents’ degree of vulnerability to flooding. However, where the multidimensional approach was adopted the result were aggregated and not localized to specific areas. Therefore, this study attempts to quantify the vulnerability indicators using the participatory approach and develop a multi-dimensional
approach for flood vulnerability assessment in Mokwa, Nigeria. Vulnerability was explored through the lens of four dimensions (economic, environmental, physical, and social) and eighteen indicators. The indicators were scrutinized and standardized for easy aggregation and comparability. The indicators were weighted unequally using Analytical Hierarchical Process (AHP). Nine communities and 382 households were selected purposively from the downstream
area of the Kainji dam for sampling. The data collected were subjected to descriptive and inferential statistics using XLSTAT (2014) and spatial analysis in ARCGIS 10.7 environment. The flood vulnerability index revealed that the communities experienced high flood vulnerability from all dimensions; economic (0.71), physical (0.66), social (0.62), and environmental (0.57). The study reported a multi-dimensional flood vulnerability index of 0.65, which implies a high level of vulnerability to flooding. This study has found significant variations in all dimensions of vulnerability among the communities. The study concludes that the multi-dimensional approach to flood vulnerability provides information on the vulnerable population as well as the factors driving vulnerability in the area. The study recommends the use of a multi-dimensional approach, sophisticated models, site-specific indicators, and fine-resolution satellite data for future vulnerability assessment.