DNA metabarcoding, a technique based on next-generation genetic sequencing, enables the rapid characterization of species composition in bulk biodiversity samples or when analyzing environmental DNA, and thus facilitates comprehensive, large-scale biodiversity assessments and monitoring. The Qinling Mountain range, extending in an east-west direction across central China, includes a series of valleys traversed by mountain streams of various sizes. Although these streams potentially contain an array of aquatic organisms, the complexity of the environment and the presence of small, cryptic, rare, or poorly characterized species makes studying the aquatic biodiversity of these streams a challenge. The goal of this study was to use DNA metabarcoding to examine the composition of both the aquatic fauna and of the aquatic communities as a whole in the Qinling Mountain streams, employing alpha diversity, beta diversity and cluster analyses to evaluate differences in biodiversity from samples collected from different locations. For this purpose, 10 samples containing both zooplankton and zoobenthos were collected from downstream and upstream locations of five streams (Jin Longxia, Shi Bianyu, Feng Yukou, Wutai Mountain and Meridian Valley) in the Qinling Mountains. The cytochrome c oxidase subunit Ⅰ (COⅠ) and 18S ribosomal RNA (18S rRNA) genes were selected as barcoding sequences. Following DNA extraction and PCR amplification using degenerate primers, the amplicons were sequenced on an Illumina MiSeq platform, and Qiime and Mothur software were used to analyze the raw data and to obtain an operational taxonomic unit (OTU) list. Ecological analysis was subsequently performed using Excel, R, and Qiime software. Analysis of the fauna composition revealed that a total of 89 orders, from 48 classes, and 10 phyla were identifiable in the total group of samples using the two gene markers. Individually, 52 orders, from 42 classes, and 9 phyla were identified using the 18S rRNA sequences, and 36 orders, from 11 classes, and 5 phyla were identified using the COⅠ sequences, demonstrating that the two gene markers together resulted in a higher rate of identification than either marker alone. With regard to community composition, analysis of COⅠ gene sequences revealed that the Arthropod orders Diptera, Trichoptera, Ephemeroptera and Coleoptera were the most common taxa, with lower occurrences of Protozoa and Rotifera. Analysis of community composition using the 18S rRNA gene sequences, on the other hand, indicated three main groups in the samples, namely the Arthropda, Mollusca and Platyhelminthes. Both the fauna composition and community composition analyses showed that the number of groups in the downstream samples was higher than that in the upstream samples. Moreover, alpha diversity analysis revealed that the three sampling plots (Jin Longxia, Shi Bianyu and Feng Yukou) most intensively affected by human activities had relatively high values of community richness and diversity compared with the two more natural sampling plots (Wutai Mountain and Meridian Valley), suggesting that aquatic biodiversity may be improved if a location has a certain degree of external interference. Finally, beta diversity analysis demonstrated that, although community variations may be very obvious when samples collected from different environments are compared, such variations may not be so obvious in samples collected from similar environments, with cluster analysis showing that community similarity values in such samples are relatively high.