Analysis of Correlations and Principal Components among Water Quality Monitoring Indicators in the Liao River Basin

为快速监测辽河流域水质，有效追踪并控制水质污染情况，本文选用辽河流域14个水质监测站2023年12期监测数据，分析常规水质指标与核心水质指标间的相关性。使用时间变化趋势检验和主成分综合指数效价评估各断面指标变化，确定核心指标关联度参数，且与常规水质类别进行方差分析。结果表明，不同检测站的核心指标与常规指标的关联度各异，主成分1 (浊度、高锰酸盐指数、总磷)反映悬浮物与有机污染负荷，主成分2 (电导率、氨氮、总氮)表征氮营养盐富集，主成分3 (pH、溶解氧)指示水体自净能力。流域污染呈现“上游物理性浑浊–中下游氮负荷突出–工业点源复合污染”的空间分异格局，建议优先实施通江口截污控磷、于家房河段脱氮工程及工业区酸碱度监管，以针对性改善水质。To enable rapid water quality monitoring and effective pollution tracking and control in the Liao River Basin, this study analyzed correlations between conventional and core water quality indicators using 2023 monitoring data from 14 stations across 12 monthly periods in the Liao River Basin. Temporal trend analysis and principal component comprehensive index evaluation were applied to assess cross-section parameter variations, determine core indicator correlation coefficients, and conduct ANOVA with conventional water quality categories. Results revealed station-specific variability in core-conventional indicator correlations, with Principal Component 1 (turbidity, permanganate index, total phosphorus) reflecting suspended solids and organic pollution loads, Principal Component 2 (conductivity, ammonia nitrogen, total nitrogen) characterizing nitrogen nutrient salt enrichment, and Principal Component 3 (pH, dissolved oxygen) indicating self-purification capacity of water body. Spatial differentiation displayed distinct pollution patterns: “physical turbidity dominant in upper reaches, elevated nitrogen loading in mid-lower reaches, and compound industrial pollution in point-source zones”. Targeted mitigation strategies include prioritizing phosphorus interception at Tongjiangkou, implementing nitrogen removal in Yujiafang river sections, and enhancing pH regulation in industrial areas.