基于多元统计分析的黄河水质评价方法

为探讨一种适用于大尺度、多断面和长时间的水质评价方法,用系统聚类分析将2000—2002年黄河6个监测断面的90个水质样本分为7组,并用判别分析验证了结果的可靠性。其主要程序为：利用多元方差分析对各断面多年水质监测样本进行空间尺度上的显著差异性分析,识别出具有显著差异的样本,然后通过系统聚类分析把上述样本进行聚类分组,最后应用判别分析方法对各组样本进行水质评价,此方法的特点为在不损失信息的前提下能大大减轻水质评价工作量,且客观可信、分辨率高,并能综合反映总体与个别特征。结果表明,黄河流域干流从上游到下游水质总体状况呈逐渐下降趋势,上游水质一般为Ⅰ-Ⅲ类,而中游和下游水质基本为Ⅳ-Ⅴ类和超Ⅴ类。

Water Quality Assessment of Yellow River Based on Multivariate Statistical Analysis

In order to find a new approach for water quality assessment which could be useful for the monitoring of large-scale,long-term and many sections,hierarchical cluster analysis was applied to group 90 water quality samples into 7 clusters. The samples generated from five monitoring sections of Yellow River during 3 years（2000~2002）. The main procedures of this approach included：（1）analyzing the spatial differences of independent samples according to multivariate analysis of variance, and recognizing the samples which were statistically significantly different between each others;（2）grouping the former samples into clusters on the basis of similarities with in a cluster and dissimilarities between different clusters based on hierarchical cluster analysis（HCA）;（3）modeling the appropriate discriminatory analysis neural networks to evaluate the surface water quality of each class, then feeding back this results to every original samples. Moreover, its particular characteristics were that it could reduce the workload in assessment and comprehensively represent both holistic condition and individual and its result was objective and discriminative. The results were assigned to the five sections.Water quality of the Yellow River belonged to class Ⅰ and Ⅱ in Ningxia and Lanzhou section could meet the need of drinking water resource.But water quality of the Huayuankou to Luokou section mostly belonged to class Ⅲ and Ⅳ.