Establishing correlations between time series of wastewater parameters under extreme and regular weather conditions
Year: 2024
Type: article
Abstract: This study investigates the correlations between key wastewater parameters – water level, turbidity, and electrical conductivity – under varying weather conditions, including extreme rainfall events such as the May 2023 flood event in Bologna, Italy. Data collected via IoT-based sensors are analyzed using Detrended Cross-Correlation Analysis and Autoregressive Distributed Lag (ARDL) models. The results highlight significant correlations between water level and other parameters, with distinct patterns emerging during extreme and regular weather periods. Notably, water level correlates negatively with electrical conductivity, particularly during flood events, due to the dilution effect of rainwater. Turbidity shows a complex relationship with water level, influenced by weather conditions and the opposing effects of different factors. ARDL models further demonstrate the potential to predict turbidity and electrical conductivity from water level data, offering valuable insights for wastewater management in urban areas.
Source: Journal of Hydrology
Institution: University of Bologna
Language: English
Subfield: Environmental Engineering
Field: Environmental Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,790
Award: G1712730057
OpenAlex ID: W4405041335
