Abstract: Understanding the fish diversity and distribution characteristics in Dongxixi watershed is crucial for conserving aquatic biodiversity in the region. We used environmental DNA (eDNA) metabarcoding and traditional netting methods to detect the fish community structure and diversity in Dongxixi watershed in Xiamen City, in the wet, dry, and normal seasons from 2023 to 2024. Additionally, we evaluated the advantages of eDNA technology and traditional netting methods for fish monitoring. Results showed that a total of 134 fish species were detected by eDNA technology during the wet season, which was significantly higher than those in dry season and normal season (61 and 48 species, respectively). The fish composition in different hydrological periods was dominated by Cypriniformes and Perciformes, accounting for 59.96%-99.56% of the total detected fish species. There was an ecological invasion phenomenon of Tilapias species, such as Coptodon zillii, Oreochromis aureus, and Oreochromis niloticus. There was no significant difference in fish alpha diversity among different sampling points in Dongxixi watershed. The Shannon index and Margalef index in wet season were significantly higher than those in dry season and normal season (P<0.05), while the Pielou index in dry season was significantly higher than those in wet season and normal season (P<0.05). Non-metric multidimensional scaling analysis (NMDS) showed that the heterogeneity between dry season and normal season was low and the species composition was similar, while the fish species composition in wet season and the other two hydrological periods was significantly different and the heterogeneity was high. Moreover, the number of fish species detected by eDNA technology was significantly higher than that captured by traditional methods, and the ecological types of fish obtained (feeding habits, habitat, and pollution tolerance) were highly consistent. This study proves that eDNA technology is feasible in the fishery resources survey in the watershed, and it is better than traditional morphology method in the species detection efficiency. Combined with traditional detection, it can further increase the reliability of monitoring investigation.