Departamento de Ciências do Ambiente, Escola Superior Agrária de Beja, Beja, Portugal.
Environ Monit Assess. 2010 Jun;165(1-4):539-52. doi: 10.1007/s10661-009-0965-y. Epub 2009 May 12.
Multivariate statistical techniques were applied to evaluate spatial/temporal variations, and to interpret water quality data set obtained at Alqueva reservoir (south of Portugal). The water quality was monitored at nine different sites, along the water line, over a period of 18 months (from January 2006 to May 2007) using 26 water quality parameters. The cluster analysis allowed the formation of five different similarity groups between sampling sites, reflecting differences on the water quality at different locations of the Alqueva reservoir system. The PCA/FA identified six varifactors, which were responsible for 64% of total variance in water quality data set. The principal parameters, which explained the variability of quality water, were total phosphorus, oxidability, iron, parameters that at high concentrations indicate pollution from anthropogenic sources, and herbicides indicative of an intensive agricultural activity. The spatial analysis showed that the water quality was worse in the north of the reservoir.
多元统计技术被应用于评估时空变化，并解释在葡萄牙南部的阿尔库埃瓦水库获得的水质数据集。在 18 个月的时间内（从 2006 年 1 月到 2007 年 5 月），使用 26 个水质参数在九个不同的地点沿水线监测水质。聚类分析允许在采样点之间形成五个不同的相似性组，反映了阿尔库埃瓦水库系统不同位置的水质差异。PCA/FA 确定了六个变量因子，它们负责总方差的 64%。解释水质变化的主要参数是总磷、可氧化物质、铁，这些参数浓度高表明来自人为来源的污染，以及指示密集农业活动的除草剂。空间分析表明，水库北部的水质较差。
