河北环境工程学院学报

选取2023年山东省黄河流域典型村庄所在县域河流出入境断面及湖库等地表水监测结果,采用因子分析和聚类分析相结合的方式对评价指标进行优化筛选和分类,探究各水质评价指标的影响程度和区域水质特征。结果表明,在现有的地表水环境质量标准中的21个基本指标中,铜、锌、六价铬3个指标未出现超标情况。通过对其余18个指标的因子分析发现,化学需氧量、高锰酸盐指数、五日生化需氧量等11个指标对研究区水质的影响较大。在因子分析的基础上,通过聚类分析将沿黄9市根据区域的污染特征和水质特点分为三类:农业产业主导的水质敏感区、生活污染源与工业污染源叠加区、传统工业污染区。建议根据分类情况和各市产业结构、自然条件等开展农村县域地表水污染治理和防控。

The study selected surface water monitoring results, including river inflow and outflow sections and lake reservoir water quality in typical villages across counties in the Yellow River Basin of Shandong Province in 2023. Using a combination of factor analysis and cluster analysis, the evaluation indicators were optimized, screened, and classified to explore the influence of each water quality indicator and regional water quality characteristics. The results showed that among the 21 basic indicators in the current surface water environmental quality standards, Cu, Zn, and Cr(Ⅵ) did not exceed the limits. Factor analysis of the remaining 18 indicators revealed that 11 indicators,such as COD, COD_mn, BOD₅, had a significant impact on the water quality of the study area. Based on factor analysis, the nine cities along the Yellow River were clustered into three categories according to regional pollution characteristics andwater quality features: agricultural-industry-dominated water quality-sensitive areas, mixed domestic and industrial overlapping areas, and traditional industrial pollution areas. It is recommended to implement rural county-level surface water pollution control and prevention measures based on the classification and the industrial structure and natural conditions of each city.