Developing community resilience index for flood (CRIF): evidence from extreme flood-prone Jamalpur district of Bangladesh

Floods pose a serious threat to human life, property, homes, agriculture, and other vital infrastructure. Recently, there has been a growing emphasis on resilience rather than vulnerability. Therefore, this study initially proposed an approach to develop a Community Resilience Index for Floods (CRIF). Resilience indicators were identified through a literature review and field surveys, and data were collected via a questionnaire administered to 333 purposively selected households in two flood-prone zones of Islampur upazila, Jamalpur district. All variables were weighted on a percentage scale from 0 to 1. The CRIF was created using primary data from a household survey, with percentage scores derived from household responses, and the average % score of experts’ opinions was then used to calculate the Resilience Factor Index (RFI) for each variable. The study found that the overall composite community resilience score indicates moderately high resilience in the Islampur Union across four dimensions. At the same time, all aspects were found to be unsatisfactory in the Noarpara Union. It also revealed that, among 17 resilience variables identified by respondents, lower age dependency, lower disability, employment status, income above the poverty line, housing proximity to riverside, pucca road network, knowledge, and early warning systems ranked highest in Islampur Union. Based on these findings, the study recommends improving the community’s socio-economic, physical, and institutional conditions by raising community awareness, strengthening structural and non-structural mitigation plans, and providing multiple income-generating activities to boost resilience to future floods. Consequently, the study’s findings, along with the identified community flood resilience indicators and CRIF framework, will help academics, policymakers, and planners assess resilience levels, enable better resource allocation and intervention prioritization, and support the goals of the Sendai Framework for Disaster Risk Reduction (2015–2030).