MULTIVARIATE STATISTICAL ANALYSIS AND USE OF GEOGRAPHIC INFORMATION SYSTEMS IN RAW WATER QUALITY ASSESSMENT

Abstract

This study aimed to apply a methodology for evaluating raw water quality and its relationship with land uses and occupations through multivariate statistical analysis and Geographic Information System. Hydrogenic potential, water temperature, dissolved oxygen, biochemical oxygen demand, chemical oxygen demand, total nitrogen, total phosphorus, and E. coli were monitored from August 2012 until March 2013. The geoprocessing tool enabled delimiting the contribution areas of each sampling site, as well as the individual identification of land use of each area. Principal Component Analysis resulted in: domestic sewage, domestic sewage/agriculture, and industrial discharge. Significant correlations were identified between the variable urban area and hydrogenionic potential (ρ = 0.446; p = 0.049), dissolved oxygen (ρ = -0.625; p = 0.003), total nitrogen (ρ = 0.649; p = 0.002), and E. coli (ρ = 0.932; p < 0.001). The methodology enabled to identify the contribution of land use factors as to water quality.

Keywords

• principal component analysis; spearman’s rank correlation coefficient; water pollution; land use.