Water Quality Index by Multivariate Statistical Technique to Estimate the Temporal Decay of the Watercourses

Objective: This study aims to add some variables that characterize the water quality in a water quality index (WQIacp), observing the events of precipitation and land use watersheds. Method: The water samples were characterized in 180 local rivers, and they were monthly analyzed. To ellaborate the WQIacp, a multifactorial analysis statistic and the weighted least squares method were used. Results and Discussion: The first factor explained 42.68% of variance, and variables apparent color and total coliform variables showed higher scores in the formation of the WQIacp. According to the analysis, it´s observed that there is a strong correlation between areas that have higher rates of remaining with the municipalities that have a better WQIacp. Cluster analysis of the municipalities, considering the remaining native vegetation, shows that in the extreme north of Goiás are the cities with the largest reserves. In central and southern part of the state lie the most deforested municipalities. Finally, in the northwestern, part of central and southern of Goiás State, are those cities that present inequality related to the the amount of native vegetation. The worst WQIacp indexes for municipalities evaluated, -1.00 and -0.96, are in the center of Goiás, in Meia Ponte River and João Leite River, respectively, near the city of Goiânia, while the best is in northern of Goiás, 0.68, in Campos Belos in Santa Tereza River. It is still observed that for all the years analyzed, there is an improvement in water quality in the dry season. The average rates grow from April on and get lower from October on, in the beginning of the rainy season. This loss of water quality during flooding is represented mainly by varying color, total coliforms and turbidity, which have scores 0.200, 0.187 and 1.179, respectively. Research Implications: The creation of a water quality index helps in diagnosing and comparing the quality of water sources, facilitating decision-making by managers of Sanitation Concessionaires. Originality/Value: This study contributes to the literature, proposing a methodology based on descriptive statistics to create a water quality index, which can assist managers in decision-making.