Mixed-methods study reveals wide disparities in livelihood resilience across flood-displaced households, highlighting the need for multidimensional asset support to mitigate ongoing vulnerability.
Flood-induced displacement represents one of the most pressing challenges for vulnerable communities in developing countries, particularly in regions where livelihoods are closely tied to climate-sensitive agriculture. Assam, located in the Brahmaputra Valley, experiences recurrent high-magnitude floods that disrupt livelihoods, erode riverbanks, and force repeated displacement. This study applies the Sustainable Livelihood Framework (SLF) to examine the vulnerability of displaced households across five flood-prone districts—Morigaon, Dhemaji, Lakhimpur, Nalbari, and Barpeta. Using a mixed-methods approach, primary data were collected through household surveys and focus group discussions, complemented by secondary sources including government reports and scholarly literature. The SLF asset pentagon was operationalized through context-specific indicators covering human, social, natural, physical, and financial capital. Composite scores reveal significant inter-district variation in livelihood resilience. Nalbari recorded the highest composite score (2.06), reflecting relatively stronger access to social and physical capital, while Barpeta exhibited the lowest (1.417), marked by fragile human and financial capital. Across districts, households reported recurrent loss of cultivable land, crop damage, poor housing quality, and limited disaster preparedness training. Social capital, supported by kinship ties and relief aid, emerged as a partial buffer, though institutional support remained inadequate. The findings highlight that displacement is not merely a physical relocation but a multidimensional livelihood crisis, reinforcing cycles of vulnerability. By situating household experiences within the SLF, this study underscores the need for integrated resilience-building strategies that strengthen capital assets, reduce exposure, and enhance adaptive capacity in flood-prone regions of Assam.
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Hazarika et al. (2026) studied this question.
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