This research addresses agricultural vulnerability in the Brahmaputra Basin by proposing a hybridized framework that integrates Indigenous Knowledge (IK) with Geographic Information Systems (GIS). Historically, top-down, techno-centric interventions have failed to account for micro-topographical complexities and local hydrological behaviors. To bridge this gap, this study employs Participatory GIS (PGIS) to formalize tacit community expertise—such as flood-adaptive cropping and soil management—into quantifiable spatial data layers. By synthesizing longitudinal ethnographic insights with digital elevation models, the framework enhances the accuracy of inundation mapping and agricultural zoning. A critical finding is the necessity of “co-production,” wherein high-resolution technical projections are validated through continuous community-led ground-truthing. This iterative feedback loop transforms static hydrological modeling into a dynamic, adaptive system responsive to intensifying monsoon volatility. Ultimately, the research provides a scalable, transdisciplinary model for climate adaptation, demonstrating that systemic food security is best achieved when technological tools serve as vessels for ancestral ecological wisdom. By centering marginalized smallholder farmers as active stewards of geospatial data, this study offers a robust blueprint for equitable disaster risk reduction and resilient land-use planning in climate-vulnerable riverine ecosystems globally.