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Household relocation intentions in riverine flood-prone urban areas: evidence from Srinagar, India

Oct 2026 · Environmental Research Communications · Vol 8 · 0 citations · 30 references
Physics

Abstract

Riverine flooding poses a significant challenge for rapidly urbanizing cities, where residential expansion into vulnerable waterways has increased exposure to environmental risk. In this context, relocation is widely discussed as a long-term flood mitigation strategy, yet little is known about how residents evaluate such options in the absence of formal programmes. This study examines household relocation intentions in flood-prone areas of Srinagar, India, focusing on the sociodemographic, economic, and psychological factors shaping willingness to relocate. A sequential mixed-methods design was used, combining semi-structured interviews with a structured household survey (n = 400), to integrate lived experiences with population-level patterns. The findings reveal an age-related pattern across the study-defined age groups: willingness to relocate is highest among middle-aged residents (24%) and moderate among younger adults (15%), but declines sharply among older residents, who exhibit the strongest reluctance (23% unwilling). No statistically detectable association between gender and relocation intention was observed in the survey. Qualitative insights indicate that relocation decisions are shaped by expectations of adequate compensation, livelihood security, uncertainty about future outcomes, and strong place attachment. Relocation is therefore not evaluated solely as a risk-reduction strategy but as a trade-off between environmental safety and socioeconomic stability. By framing relocation as a forward-looking adaptation decision, this study contributes to debates on environmental mobility, voluntary immobility, and managed retreat in the Global South. The findings highlight the need for relocation programmes that integrate livelihood continuity, community participation, and the social realities of flood-exposed populations.

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