Abstract
ABSTRACT Uncontrolled wastewater discharges have social and environmental consequences and generate increased operational costs. Wastewater treatment plants (WWTPs) are vulnerable infrastructure and require the implementation of risk and safety analyses in the context of climate change and flooding. Therefore, making decisions in changing weather conditions is one of the most important but also most difficult tasks for operators to maintain proper management of wastewater infrastructure facilities. The aim of the research was to develop a decision-making tool based on soft sensor methods to allow inflows to be classified into two classes of WTTP operating conditions. The quality of the regression models was maintained at 90.0%, while the classifier based on the coarse decision tree had a testing accuracy of 92.4%. The results can contribute to a reduction in wastewater load, which is significant in the context of ongoing climate change, and to an improvement in WWTP operation through automation.
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