Master Student Program in Environmental Sciences and Agricultural Sustainability, Dom Bosco Catholic University, Campo Grande, MS, Brazil.
Department of Sanitary and Environmental Engineering, Dom Bosco Catholic University, Campo Grande, MS, Brazil.
Environ Monit Assess. 2019 Aug 3;191(9):539. doi: 10.1007/s10661-019-7647-1.
The externalities generated by disorderly urbanization and lack of proper planning becomes one of the main factors that must be considered in water resource management. To address the multiple uses of water and avoid conflicts among users, decision-making must integrate these factors into quality and quantity aspects. The water quality index (WQI), using the correlation matrix and the multivariate principal component analysis (PCA) and cluster analysis (CA) techniques were used to analyze the surface water quality, considering urban, rural, and industrial regions in an integrated way, even with data gaps. The results showed that the main parameters that impacted the water quality index were dissolved oxygen, elevation, and total phosphorus. The results of PCA analysis showed 86.25% of the variance in the data set, using physicochemical and topographic parameters. In the cluster analysis, the dissolved oxygen, elevation, total coliforms, E. coli, total phosphorus, total nitrogen, and temperature parameters showed a significant correlation between the data's dimensions. In the industrial region, the characteristic parameter was the organic load, in the rural region were nutrients (phosphorus and nitrogen), and in the urban region was E. coli (an indicator of the pathogenic organisms' presence). In the classification of the samples, there was a predominance of "Good" quality, however, samples classified as "Acceptable" and "Bad" occurred during the winter and spring months (dry season) in the rural and industrial regions. Water pollution is linked to inadequate land use and occupation and population density in certain regions without access to sanitation services.
城市化无序发展和缺乏合理规划所产生的外部性，成为水资源管理中必须考虑的主要因素之一。为了协调水资源的多种用途，避免用户之间的冲突，决策必须将这些因素纳入质量和数量方面。本研究采用水质指数（WQI），利用相关矩阵和多元主成分分析（PCA）和聚类分析（CA）技术，综合考虑城市、农村和工业区域，甚至在存在数据差距的情况下，对地表水水质进行分析。结果表明，影响水质指数的主要参数是溶解氧、海拔和总磷。PCA 分析结果表明，数据集的 86.25%的方差可以用理化参数和地形参数来解释。在聚类分析中，溶解氧、海拔、总大肠菌群、大肠杆菌、总磷、总氮和温度参数在数据维度之间表现出显著的相关性。在工业区域，特征参数是有机负荷；在农村地区是营养物质（磷和氮）；在城市地区是大肠杆菌（指示病原体的存在）。在样本分类中，“良好”质量占主导地位，但在农村和工业地区的冬季和春季（旱季）会出现“可接受”和“差”的样本。水污染与某些地区土地利用和占用不足以及缺乏环境卫生服务有关，这些地区的人口密度较高。
