Citizen science has become an essential tool for ecological monitoring, however concerns remain regarding data reliability, particularly for taxa that require advanced identification skills. The present study evaluates detection accuracy and count reliability in citizen-based waterbird monitoring conducted at the Siheung Gaetgol Wetland, South Korea. The study analyzed a total of 27 citizen surveys and 7 expert-accompanied surveys collected from 2015 to 2019. We quantified (1) species-level detection rates, (2) the effect of citizen group size on species richness, and (3) relative count bias based on mean abundance per survey. The detection analyses revealed pronounced discrepancies for approximately one-third of species, particularly, and other visually challenging or crepuscular taxa, for which expert detection rates exceeded citizen rates by 0.2~0.5. Conversely, common and readily identifiable species exhibited no discernible variations. The number of species detected was found to be independent of the size of the citizen science group, with a range of 4 to 13 participants. This suggests that observer expertise, rather than survey effort, is a primary determinant in determining detection efficiency. The count bias indices further demonstrated a systematic overestimation of flocking species and underestimation of cryptic or small-bodied species. Despite the limitations of the study, which include unequal survey frequency and uncontrolled environmental conditions, the results consistently indicate that observer proficiency exerts a significant influence on both detection and abundance estimates. These findings underscore the necessity for targeted expert involvement, species-specific training, standardized counting roles, and routine data-quality assessments to enhance the reliability of citizen-based bird monitoring program.