A Citizen Science and Crowdsourcing Framework for Community-Led Water Security Monitoring

The significant absence of localized, real-time data on water resources hinders water security for agricultural and WASH (Water, Sanitation, and Hygiene) purposes in the context of climate change. This research seeks to address this gap through the design and validation of a citizen science framework designed to enable local communities to monitor their own water resources. In this research, we propose a novel citizen science approach that fuses crowdsourced data from a co-designed mobile platform with satellite remote sensing and in situ sensors. Our research utilizes a Participatory Action Research approach to co-develop a mobile platform with community participants. The platform crowdsources high-resolution information on important indicators, such as surface water level, water point functionality, water quality, rainfall, temperature, and Water, Sanitation, and Hygiene-related health events. This grassroots data is integrated with in situ sensor measurements and satellite remote sensing products (e.g., MODIS, Sentinel) to improve the spatiotemporal accuracy of hydrological risk models that will help produce high-resolution hydro-climate information for the community and develop an integrated WASH Risk Index at the village scale. This research aims to validate the reliability of community-generated data and establish a scalable and sustainable model for community-led water monitoring. The expected outcome is a proven, open-source platform and a co-developed framework that provides policymakers with precise, actionable insights. This contribution will enable more informed water resource management, helping to enhance community resilience against water scarcity, safeguard agricultural productivity, and mitigate water-related health crises in a changing climate.