Evaluating the water quality characteristics and tracing the pollutant sources in the Yellow River Basin, China

Evaluating water quality characteristics (WQC) and tracing pollutant sources (PS) have gradually attracted worldwide attention. This study was conducted to develop an integrated method framework for evaluating WQC, tracing PS, and improving understanding of their relationship to efficiently managing the water environment. The single-factor index, comprehensive water quality index (CWQI), and hazard quotient and hazard index (HQ and HI) were used to evaluate the characteristics of single pollutant concentration, comprehensive concentration, and human health risk, respectively. These evaluation methods combined with relevant standards selected data from the original sampling data. These selected data were used for tracing PS by principal component analysis and Pearson correlation methods. 3384 sampling data were collected in the Yellow River Basin in 2021, and the WQC assessment and pollutant traceability were carried out by using the above-integrated method framework. The results showed that TN(total nitrogen) was the primary pollutant with an average concentration of 4.54 mg/L, followed by CODcr(dichromate oxidizability), NH₄⁺-N(ammonia nitrogen), and TP(total phosphorous). The CWQI values ranged from 1.26 to 110.03, with an average of 7.74, indicating the pollution level of trace elements was excellent. The HQ and HI max values of As(arsenic) and Cr⁶⁺(hexavalent chromium) elements were over 1, meaning the elements have negatively affected local human health. Furthermore, the anthropogenic input was the primary pollutant source for TN. The anthropogenic input and agricultural source pollution emission could be considered for CODcr, NH₄⁺-N, TP, and BOD5(five-day biological oxygen demand). The anthropogenic input and the weathering and leaching of loess could be considered for As elements. For Cr⁶⁺, F(fluorine), Anionic, and Petroleum, the anthropogenic activities were the primary pollutant sources, including the metal mining and production and the coal mining and processing industry. Our results could provide effective information to support adaptive management measures to improve water environment conditions and protect human health.