Zooplankton is an important component of aquatic ecosystems, and is sensitive to external disturbances and changes in the water environment. Monitoring its species diversity and community composition can not only help us better understand the dynamics of lake ecosystems, but also provide a scientific basis for water quality management, which is of great significance for understanding lake ecosystems. In recent years, environmental DNA (eDNA) metabarcoding technology has been increasingly used in biological surveys. However, whether the results based on eDNA technology are in line with those obtained through traditional morphological identification for detecting zooplankton diversity in the field, remains unclear. In this study, we conducted a 2-year seasonal field survey in 2014 and 2015 in Lake Fuxian, aiming to compare the results obtained by eDNA technology and morphological identification in detecting the species diversity and community composition of zooplankton. The results showed that: (1) the eDNA metabarcoding technology based on high-throughput sequencing of mitochondrial CytochromecOxidase Ⅰ gene ( COI ) and morphological identification obtained the same seasonal trend of alpha diversity (species richness and Shannon-Wiener index) changes of zooplankton in Lake Fuxian during our 2-year period of field monitoring; (2) Compared to morphological identification, eDNA technology based on COI gene high-throughput sequencing could detect more species; though the number of rotifer species identified at the genus level was lower than that identified by morphological methods; (3) Both methods found that the zooplankton community structure in Lake Fuxian exhibited temporal decay trends, but eDNA technology was more effective than morphological identification in distinguishing seasonal differences in zooplankton community composition. Despite the limitations of eDNA technology in detecting rotifer species and zooplankton biomass, it has a clear advantage in detecting seasonal variations in zooplankton diversity and community structure.This study attempted to apply eDNA technology to zooplankton detection in lakes using field anniversary monitoring samples, and confirmed that COI based eDNA technology has higher resolution in the discrimination of zooplankton community composition, but its database needs to be improved before promoting eDNA technology in zooplankton diversity research and water ecology monitoring.