Development and operationalization of a citizen science framework for hydrological monitoring and knowledge co-generation

Citizen science (CS) empowers communities in data collection and problem-solving, enhancing research inclusivity and local relevance. However, the absence of a comprehensive framework limits their development and potential contributions to sustainable practices. In this study, we developed and tested a CS framework for hydrological data collection and the co-creation of nature-based solutions (NbS). The framework has 3 major stages: establishment, operation and knowledge generation - each involving multiple activities. It was piloted in the Kelekindo watershed of Central Rift Valley Lakes Basin of Ethiopia, engaging the citizen scientists (CSts) in monitoring of rainfall, river water level, shallow groundwater (SGW) and water quality. The CS data allowed to investigate poorly understood hydrological behaviour of the watershed, including the fill-and-spill effect and characterization of an extreme runoff event. Co-interpretation of data that SGW recharge can support thousands of farmers in practicing backyard irrigation. The river and well water in the study area were within safe limits for irrigation in terms of the commonly monitored water quality parameters. CSts were engaged in the selection and co-design of a priority NbS for watersheds. The study showed that a well-designed citizen science framework can generate reliable hydrological data and meaningfully engage communities.