| Abstrakt: |
The Yalong River in Panzhihua, China is an important water source for the production and in the lives of people in the region. This river plays an irreplaceable role in economic development and human health. In this study, the cluster (CA) and the discriminant analyses (DA) of multivariate statistical analysis were performed to evaluate the water quality in the Yalong River from 2016 to 2018. Parameters, such as water temperature, flow rate, pH, conductivity, dissolved oxygen, 5-d biochemical oxygen demand (BOD5), ammoniacal nitrogen, total nitrogen (TN), chlorophyll a (Chl-a), and arsenic (AS), each of which contains 72 samples, were selected to understand the temporal variations in the water quality of the Yalong River. Through CA, the watershed was divided into three groups based on the similarities of water quality characteristics. The first, second, and third groups comprise the May and June, the August, September, and October, and the January, February, March, April, July, November, and December samples, respectively. These three groups correspond to the dry, flood, and flat seasons. The correctness of the group clustering was verified through DA. The important parameters that sufficiently represent spatiotemporal differences include pH, BOD5, DO, Chl-a, and TN. The water quality parameters imply that the main problem in the Panzhihua section of the Yalong River is the high water organic pollutant content. However, the pollution level is within the Class III standard, and the overall quality of the water body is acceptable. Therefore, the monitoring frequency of these parameters should be strengthened, and the sampling method should be optimized to provide a scientific basis for the water quality monitoring in the Yalong River. [ABSTRACT FROM AUTHOR] |
