Contact
Peter Huck
Department of Civil and Environmental Engineering
Introduction
Robustness is the ability of a drinking water treatment plant (DWTP) to achieve the desired finished water quality during adverse raw water quality events. Increases in extreme weather due to climate change can cause unprecedented changes in surface water quality parameters (WQPs) that pose operational challenges to DWTPs. Increasing the short-term robustness of DWTPs can be a viable adaptation option during such events.
This study proposes and details a framework to systematically perform a quantitative evaluation of the robustness of critical steps in the treatment process and the overall DWTP. The framework is then applied to a full-scale DWTP to provide a proof of concept. Importantly, the framework explicitly identifies options to improve plant robustness as potential climate change adaptation measures.
Outcomes
A general framework outlining the main steps and methodology for systematic assessment and improvement of the robustness of a DWTP is presented (Figure 1). Step 1 (parameter) selects the WQP which is impacted by extreme weather and is of operational importance to a DWTP; this WQP then becomes the basis of the robustness evaluation (Figure 2a). Step 2 (identification) classifies treatment processes as critical or vulnerable, while step 3 (criteria) assigns thresholds for critical steps based on regulatory or performance goals. Step 4 (evaluation) conducts a quantitative robustness evaluation of each critical treatment process for three raw water scenarios; normal range, historical peaks and extreme values not yet experienced (Figure 2b). The first two scenarios were evaluated using historical data, the third scenario was evaluated using bench-scale setups that physically simulated waters of extreme water quality. Step 5 (assessment) calculates an overall robustness index for the DWTP, while step 6 (adaptation) identifies and applies short-term operational responses to improve the robustness of the system.
Figure 1: General robustness framework (Source: ACS EST Water 2023, 3, 5, 1305-1313).
Figure 2: Detailed methodology for steps 1 (a; parameter) and 4 (b; evaluation) of the general robustness framework (Source ACS EST Water 2023, 3, 5, 1305-1313).
The study then presents a parameter-specific framework using turbidity as the WQP and the turbidity robustness index (TRI) for evaluation. This turbidity framework is then applied to a full-scale DWTP in Ontario, Canada demonstrating how the framework can be tailored to a specific DWTP. Results indicated that the plant intake reservoir functioned as a natural sedimentation basin, which significantly reduced higher raw water turbidities and likely provides a natural cushion for future extreme-turbidity events. The coagulation–flocculation–sedimentation train was found to be lower in robustness for 2 out of 26 weeks, but was offset by operational intervention and robust filter performance. The consistent overall performance of the plant was further evidenced by the overall robustness index, which remained “stable” and “very stable” throughout the assessment period except in week 21 which was “slightly disturbed” based on the weighting approach.
Conclusions
The study proposes a step-by-step framework for a systematic robustness evaluation of individual treatment processes and DWTPs and demonstrates its application to a full-scale DWTP. Framework application is capable of identifying (i) less robust processes which are likely to be vulnerable during climate extremes, (ii) operational responses to increasing short-term robustness and (iii) a critical WQP threshold beyond which capital improvements are necessary.
An important feature of the framework is its ability to quantitatively evaluate treatment performance, considering both the plant's historical performance and its expected performance during potential extreme water quality events assessed through bench-scale experiments. By quantifying the historical data within normal ranges and past peaks, it becomes possible to identify the specific treatment processes that exhibited vulnerability during specific weeks. This analysis not only helps to identify areas that need improvement or enhancement, but also allows DWTP personnel to understand whether the vulnerability resulted from changes in the source water quality or other factors, such as operational regimes. By understanding the underlying causes, informed decisions can be made to optimize treatment strategies and effectively tackle potential challenges.
While recognizing the limitations of bench-scale experiments, results from this study can give an initial indication of the robustness of the critical treatment processes and operational changes can be tested for effectiveness as short-term adaptation options. The framework can help DWTPs in developing standard operating procedures for extreme weather events to guide operators in making operational changes in a systematic manner. Further investigation for scenario 3, extreme values not yet experienced, is recommended for coagulation–flocculation–sedimentation train and filtration processes. These additional investigations may identify a critical turbidity threshold beyond which operational interventions will not be successful and capital improvements to the plant will become necessary.
The framework can be integrated with provincial water quality plans, climate adaptation plans and other infrastructure resilience frameworks, offering a comprehensive approach to address the challenges faced by water treatment systems and enabling more robust decision-making and proactive measures to ensure the long-term sustainability and resilience of water treatment infrastructure.
Nemani, Kirti S., Peldszus, Sigrid, Huck, Peter M. Practical Framework for Evaluation and Improvement of Drinking Water Treatment Robustness in Preparation for Extreme-Weather-Related Adverse Water Quality Events. ACS EST Water 2023, 3, 5, 1305–1313, April 20, 2023. https://doi.org/10.1021/acsestwater.2c00627
For more information about WaterResearch, contact Julie Grant.
