CITIZEN SCIENCE AND WATER RESOURCES MANAGEMENT: DIGITAL INTEGRATION AND DATA QUALITY

Abstract

This study examines the impact of citizen science (CS) projects on water resource management and environmental monitoring. The integration of digital technologies enhances community-based data collection processes for water quality monitoring, pollution detection, and ecosystem health. By providing examples from European Union-funded projects, the study demonstrates how digital tools, and mobile applications enable large-scale monitoring of environmental changes through extensive public participation. The reliability of CS data poses significant challenges in terms of scientific accuracy, yet the incorporation of machine learning and remote sensing technologies enhances data credibility. Furthermore, the study discusses the sustainability of citizen participation, motivation, and long-term engagement in these projects. The role of citizen science in environmental decision-making processes and policy development is emphasized. The paper suggests that for CS projects to be more effective, standardization of data collection methodologies, improvement of digital infrastructure, and overcoming legal and ethical barriers are necessary.