Modelo estatístico para o crescimento da bactéria E. Coli considerando influência de parâmetros físico-químicos e índice pluviométrico: um estudo de caso no manancial de Cascavel

Abstract

It has been reported that there is a raise in the number of studies that use the statistics model as a useful tool for water quality monitoring. This paper will focus on the influence of physical-chemical factors and pluviometric index on the microbiological growth of the wellspring, which affects instantly the water quality of the Cascavel river, necessary for the city water maintenance, where linear regression models where adjusted to estimate the microbial rate of the river, with data from the water treatment plant of Cascavel between the years of 2014 and 2017. The study was conducted based on the microbial rate of E. coli. The variables where analized according to water data and climate data from the Cascavel river basin, such as precipitation, pH and turbidity. The first statistical analysis, as the descriptive statistics evaluation, connections, changes in the used variables where used so the first model could be adjusted to the data. The results of the first model where not acceptable, so it was noticed the need of performing with differentiating series, which significantly improved the model trial statistics. Finally, it was tried out in a parsimoniouly way, which showed satisfatory results, and therefore, was the chosen one. The results of the regression analysis indicated that the independente variables explain 70% of the E. coli. variation, taking into account the numbers where superior to those found on the literature (between 40% and 60%), however, the developed linear regression model was not as simple as the referential ones, because the serie differentiation and the terms of error repair where necessary. The obtained results in the adopted model showed itself eficiente, since it was obtained a significant correlation between E. coli. and the turbidity, which is affected by precipitation. Nevertheless, the precipitation does not influence the E. coli., so the model can be used as an assistance for the wellspring monitoring.