Community-led spring rejuvenation in the Indian Himalayas: Toward an AI-supported scaling framework

Springs are the primary source of freshwater for millions of people in the Indian Himalayan Region (IHR), sustaining domestic, agricultural, and ecological needs. Climate change, deforestation, and unregulated land-use transformation have accelerated the drying of these vital sources. This paper presents the societal impacts of a National Mission on Himalayan Studies (NMHS) pilot project on spring rejuvenation conducted in the Darjeeling hills, India, between 2019 and 2024. The project mapped 300 springs using GIS-based spatial analysis and implemented ecological and community-based rejuvenation of two critical sources, resulting in measurable recovery in spring discharge and improved water access for approximately 200 households. The work advances Sustainable Development Goals 5, 6, 10, 13, and 15, with particular attention to gender equity and reduced inequality through documented participation of women and marginalised communities. This paper is a field study with a prospective AI agenda, not a report of implemented AI deployment. While AI-based tools were not used during the project intervention, the rich empirical record provides a strong basis for proposing AI-enabled approaches, predictive mapping, real-time discharge monitoring, and decision-support systems, to scale spring management ethically and sustainably. The paper discusses both the potential and the risks of such integration, including digital exclusion, algorithmic bias, and data governance. This integration of community engagement, traditional knowledge, and prospective technological innovation offers a replicable model for equitable water security in vulnerable mountain regions of the Global South.