Multiple linear regression analysis (MLR) applied for modeling a new WQI equation for monitoring the water quality of Mirim Lagoon, in the state of Rio Grande do Sul—Brazil

Abstract

Accurate assessment of the type and extent of water pollution is a difficult and complicated task. Therefore, the use of the Water Quality Index (WQI) proves to be a useful tool, as this index has the advantage of resulting in a single number that is easy to communicate and understand. One of the statistical methods that can be used to develop a new WQI equation for a given water body is Multiple Linear Regression (MLR). Therefore, this work aims to develop a new WQI equation for Mirim Lagoon through MLR and to evaluate the suitability of that equation. For this, 154 samples collected at 7 monitoring points of Mirim Lagoon over three years were analyzed, from which the original WQI results were obtained. With these results, MLR was applied, generating a new WQI equation with only three variables: phosphorus, dissolved oxygen (DO) and thermotolerant coliforms. This MLR model obtained an R2 coefficient equal to 0.728, demonstrating that 72.8% of the data variability was explained by the equation generated by this model. Through the paired t test it was possible to demonstrate that the results of the new WQI did not differ significantly from the results of the original WQI, obtaining significance values greater than 0.05 for both absolute WQI values and quality ranges (p value 0.886 and 0.467, respectively), attesting to the adequacy of the new equation. The reduction in the number of variables for monitoring water quality has several advantages, from financial ones, as it makes monitoring less costly, even in reducing the eclipse effect. Therefore, it is concluded that it is of great importance to generate an equation with fewer variables for monitoring the quality of the waters of Mirim Lagoon.