The quality of surface water is a very sensitive issue and it is a great environmental concern worldwide. In recent years, there has been an increase in awareness and concern about water pollution across the globe. Thus, new approaches towards achieving sustainable water resources management have been developed internationally. A variety of water quality indices have been designed to judge out the overall water quality within a particular area promptly and efficiently. As the indicator has the function to simplify, other techniques have been applied to identify some informative content which may influence the safe management of water resources.
In present study multivariate statistical approaches are used; interpretation of large and complex data matrix obtained during a monitoring of the Açude da Macela, which is located in Itabaiana, Sergipe, Brazil and used for human consumption and irrigation of vegetables.
Samplings were done on selected sites for two years (2010–2012) across in the reservoir width with a view to monitor changes caused by anthropogenic sources. Sampling, preservation and transportation of the samples to the laboratory were done in concordance with standard methods. Eleven physicochemical and bacteriological variables have been analyzed in water samples collected two years where river is affected by man made and seasonal influences. The dataset was treated using Principal Component Analysis (PCA) on the R Project for Statistical Computing to extract the parameters that are most important in assessing variation in water quality in order to modify the IQAR index. The parameters of water quality were compared with the limits established by CONAMA’s Resolution nº. 357/2005 and the quality of its water were determined according to three indexes, commonly used - IAQR (IAP), O-WQI, PW-WQI– and the new proposed index, in order to minimize subjectivity and improve the credibility of the final evaluation. Five Principal Factor were identified as responsible for the data structure explaining 72% of the total variance of the dataset, in which nutrient factor (25.57%), dissolved pollutants and salinity (13.59%), physicochemical sources of variability (12.35%), waste water pollution from industrial and organic load (10.60%) and sewage and feacal contamination (10.04%) that represents total variance of water quality in the Açude da Macela. The results for the IQAR (IAP), O-WQI, PW-WQI and IQAR-m indexes allowed classify this reservoir, respectively, as extremely polluted, very bad, very bad and very polluted. The analysis of variables showed that the Açude’s water quality was found with high concentrations of ammonia-N and total phosphorus, like the anthropogenic activities, resulting from dumping of domestic, industrial and agricultural effluents, possibly, the main and most significant sources of pollution. The present study suggests that PCA techniques are useful tools for identification of important surface water quality parameters, showing that it is necessary to adopt measures for the control and reduction of nutrients and organic loads in the water to contain the eutrophication process of this reservoir. In this context, it is essential to monitor the physical, chemical and biological parameters in order to assess the impact of human action on this water resource.