Use of Complex Network Modelling to Assess the Influence of the Parameters on Water Quality of Rivers

Abstract

The purpose of this study is to evaluate the influence of parameters, used in the monitoring and classification of the rivers water quality, for the analysis of environmental impacts in two important water resources in the interior of São Paulo State. Based on the complex networks theory for modelling, the used data refer to collections and laboratory analyses of water samples, carried out from 2006 to 2017, by a research team. The collections took place at strategic points on the rivers, in a densely populated and industrialized place, therefore of great economic importance for the country. The region bathed by the rivers presents evidence of anthropogenic actions due to domestic, industrial, and agricultural effluents, the main effluents from oil refining, representing a challenge for government agencies regarding the quality of water resources. For the analysis, a database was created containing information from the evaluations of thirteen monitoring parameters: pH, dissolved oxygen, biochemical oxygen demand, total nitrogen, total phosphorus, turbidity, Escherichia coli quantity, total solids, temperature, chemical oxygen demand, electrical conductivity, chlorides, and precipitation. The relationships among sampled parameters were analyzed applying Spearman correlations. The developed model sought to identify the most impacting variables on river pollution during the mentioned period, supported by the water quality index of the São Paulo State Environmental Company (CETESB). According to results, electrical conductivity and chlorides were the most influential network parameters in rivers pollution. Besides, the correlation among parameters is greater when more polluted the rivers are.