Establishing correlations between time series of wastewater parameters under extreme and regular weather conditions

This study investigates the correlations between key wastewater parameters – water level, turbidity, andelectrical conductivity – under varying weather conditions, including extreme rainfall events such as theMay 2023 flood event in Bologna, Italy. Data collected via IoT-based sensors are analyzed using DetrendedCross-Correlation Analysis and Autoregressive Distributed Lag (ARDL) models. The results highlight significantcorrelations between water level and other parameters, with distinct patterns emerging during extreme andregular weather periods. Notably, water level correlates negatively with electrical conductivity, particularlyduring flood events, due to the dilution effect of rainwater. Turbidity shows a complex relationship withwater level, influenced by weather conditions and the opposing effects of different factors. ARDL modelsfurther demonstrate the potential to predict turbidity and electrical conductivity from water level data, offeringvaluable insights for wastewater management in urban areas.