Assessing economic and livelihood impacts of water hyacinth utilisation in rural India: A mixed-methods study

Abstract

Water hyacinth (Eichhornia crassipes), an invasive aquatic plant, poses a persistent challenge to freshwater ecosystems in India, contributing to clogged waterways, reduced biodiversity, and economic strain on rural populations. This study examines a community-based intervention in Meerut, supported by the Uttar Pradesh State Rural Livelihood Mission (UPSRLM) and the Meerut Institute of Engineering and Technology (MIET), which aimed to address these issues by repurposing water hyacinth into value-added products. Employing a mixed-methods research design, which included field surveys, focus group discussions, structured interviews, and socio-economic impact assessments, the study examined the environmental, economic, and social dimensions of the initiative. Preliminary findings suggest ecological improvements such as localized enhancements in water quality and reports of increased aquatic biodiversity; however, these observations require further longitudinal data to establish causality. Economically, participating women artisans reported an average income increase of approximately 35%, and profit margins for handicraft products ranged from 50% to 60%, although these figures varied based on market access and product demand. Socially, participants reported perceived gains in self-confidence, economic autonomy, and community cohesion, with 75% noting an increase in collective participation. Nonetheless, challenges persisted in areas such as scaling production, maintaining product quality, and ensuring a consistent market presence. The initiative demonstrates potential in aligning ecological management with rural livelihoods through women-led self-help groups (SHGs), contributing to broader discussions on the circular economy and community-driven development. However, sustained success will likely depend on continued policy backing, technical training, and adaptive support systems. The findings suggest a promising but context-sensitive model that warrants further study before wider replication.