A novel methodological approach to handle high-turbidity events of drinking water treatment plant

Abstract

Climate change is increasingly impacting the operation of drinking water treatment plants (DWTPs) by degrading surface water quality due to extreme weather events like heavy rainfall and flooding (Verlicchi et al., 2024). This leads to higher levels of turbidity, soluble metals, natural organic matter, and algal blooms, potentially compromising the ability of DWTPs to provide safe drinking water (Yadava et al., 2023). To mitigate these risks, stricter regulations have been introduced, such as the EU Directive 2020/2184, which sets a turbidity threshold of 0.30 NTU for 95% of measurements to prevent microbial contamination and ensure water safety. Additionally, the new EU Directive for the first time incorporated the concept of robustness into a regulatory framework compliance. Traditionally, DWTP performance has been assessed by monitoring the removal efficiency of specific contaminants like iron, E. coli, and turbidity from inlet to outlet (Bwapwa et al., 2024). However, this reactive approach fails to detect early signs of operational issues, only identifying problems after they have already impacted the system. A more proactive method is needed to provide early warnings and ensure process stability under varying raw water conditions. Robustness, defined as a plant’s ability to maintain high performance despite operational challenges, has been proposed as a key metric for evaluating DWTPs (Nemani et al., 2023). A recent study (De Marines et al., 2025) has introduced a Turbidity Robustness Index (TRI) to quantify plant stability over time. This index has shown greater sensitivity and specificity in identifying process failures than existing ones. This study proposes a new TRI-based methodology, named ALERT (hAndLe high-turbidity Events in drinking water tReatment planTs) to assess DWTP performance under fluctuating water quality conditions, identifying vulnerable treatment stages and critical thresholds above which a noticeable robustness loss is observable. The findings could have direct applications in defining management strategies to handle critical operational scenarios and achieve DWTP adaptation to climate change.