Participatory flood vulnerability assessment in the Teesta floodplain of Bangladesh using GIS-based AHP and frequency ratio models

Flooding in the Teesta River floodplain of northern Bangladesh poses significant socio-economic and environmental challenges due to monsoonal rainfall, low-lying topography, and dynamic riverine processes. This study presents a participatory flood vulnerability assessment integrating GIS-based Analytical Hierarchy Process (AHP) and Frequency Ratio (FR) models with community-level insights to delineate flood-prone areas and evaluate local adaptive capacity. Topographical, hydrological, and environmental datasets, including Landsat 8 imagery, Digital Elevation Model (DEM), land use and land cover (LULC), drainage density, soil texture, and rainfall, were compiled and analyzed to generate flood vulnerability maps for 2000, 2010, and 2022. Flood vulnerability increased between 2000 and 2022, with low vulnerability areas decreasing (2809.87 → 2476.45 km²) and high to very high zones expanding (607.76 → 761.22 km² and 441.30 → 654.87 km²), while river areas declined (922.09 → 823.81 km²). Validation using field data showed 85 % agreement, confirming model reliability. Participatory assessment of community adaptive capacity highlighted variations in resilience across four dimensions: Built Environment, Organization and Institution, Socioeconomic Status, and Science and Technology, with technological enhancement and social engagement identified as key strategies for improving flood preparedness. This integrated approach highlights the value of merging geospatial modeling with community insights to strengthen local disaster risk reduction efforts and guide effective policy-making in highly flood-prone deltaic areas.