Advancing ambient water quality monitoring and management through citizen science in low- and middle-income countries

In contexts where conventional environmental monitoring has historically been limited, citizen science (CS) for monitoring efforts can be an effective approach for decentralized data generation that also raises scientific literacy and environmental awareness. To that end, the United Nations Environmental Program (UNEP) is considering citizen science (CS) as a mechanism for producing ambient water quality data to track progress on Sustainable Development Goal (SDG) indicator 6.3.2: "proportion of bodies of water with good ambient water quality". However, the alignment of SDG 6.3.2 monitoring requirements with citizen science capacity and results in low- or middle-income countries has not been assessed. Through a systematic literature review of 49 journal publications, complemented by 15 key informant interviews, this article examines the methods and outputs of CS programs in resource-constrained settings. We explore the potential of these programs to contribute to tracking SDG 6.3.2. Using the Citizen Science Impact Assessment Framework (CSIAF), we evaluate broader outcomes of CS programs across 5 domains: society, economy, environment, governance, and science and technology. Despite large variability in scope, CS programs were consistently found to generate useful data for national-level reporting on physicochemical and ecological parameters; however, data quality is a concern for CS measurement of microbiological parameters. The focus in literature to-date is predominantly on scientific data production which falls only within the 'science and technology' outcome domain. Societal, governance, economic, and environmental outcomes are infrequently evaluated. Of the studies reviewed in this article, 75% identified some form of pollution but only 22% of them reported follow-up actions such as reporting to authorities. While CS has important potential, work is still needed towards the 'formalization' of CS, particularly if intended for more vulnerable contexts.