WCW24

Water treatment plants supplied by surface water must ensure that treatment processes are sufficiently robust to handle rapid increases in raw water turbidity and natural organic matter (NOM) that occasionally accompany spring runoff or heavy rainfall events. Climate change is expected to increase the likelihood of extreme weather events, causing more variability in source water quality and underscoring the importance of robust treatment operations. Robustness refers to the ability of treatment systems to produce safe drinking water and maintain desired water quality consistently, even during adverse changes in raw water quality. High turbidity creates obvious challenges for clarification and filtration processes, whereas high NOM increases coagulant demand, not only affecting turbidity removal but also increasing disinfectant requirements and associated by-product formation. For plants relying on UV disinfection, controlling NOM is particularly important for maintaining adequate UV transmittance. The robustness framework developed by Nemani et al. (2023) applies quantitative metrics to all critical treatment processes, taking into account both turbidity and NOM removal, to allow an overall assessment of robustness. This presentation illustrates how a combined approach, using indices for both turbidity and NOM removal, has been applied to ten years of water quality and operational performance data to determine the robustness of two plants that occasionally experience extremely adverse source water quality conditions with turbidities >1000 NTU and colour > 100 TCU. After reviewing historical operational practices and treatment effectiveness during extreme source water quality events, alternative short-term adaptation options were evaluated. The resulting recommendations will allow a more proactive approach to applying operational interventions during impending events. The evaluation is also expected to guide long-term planning decisions related to infrastructure upgrades and alternative process selection. Reference: Nemani, K.S., S. Peldszus, P.M. Huck, 2023. ACS Environmental Science & Technology - Water, 3(5), 1305-1313.