People’s Water Data: Design and Validation of a Scalable Decentralized Framework for Monitoring Drinking Water Safety

Abstract

Water, the mother of all resources, must be managed sustainably for global prosperity. Equitable access to clean drinking water depends on effective water-quality monitoring. Centralized drinking-water monitoring systems are essential for public health protection, yet in many regions, they lack spatial resolution and household-level coverage, allowing localized contamination risks to remain undetected between routine assessments. In this study, we present and validate a decentralized, quality-controlled drinking-water surveillance architecture at scale. In a pilot implementation, 990 university-trained participants conducted standardized assessments of over 9000 household drinking-water sources across India, Israel, and Uganda. Validation analyses demonstrated strong agreement between decentralized field measurements and expert- and laboratory-supported verification, supporting reliable data generation under structured protocols. The resulting spatial dataset identified localized areas with elevated water-quality risk indicators that may be missed by lower-resolution monitoring approaches. By expanding household-level coverage and incorporating structured quality-control and validation procedures, the framework provides early warning and supports targeted professional follow-up, while complementing, rather than replacing, certified laboratory and regulatory monitoring systems. Overall, this study establishes a transferable decentralized surveillance framework that complements existing monitoring infrastructure and strengthens sustainable water resource management in regions with appropriate training capacity, institutional support, ethical data governance, and validation infrastructure.