The objective of this study is to propose and apply a novel approach to develop a drinking water quality index that enables water managers to routinely identify the vulnerabilities in a distribution system (DS) while taking into account the priorities of water managers and operators. Here, we propose an innovative approach based on the participation of eight researchers and water managers. The input from these participants was included through a combination of the Delphi and MACBETH (Measuring Attractiveness by a Categorical-Based Evaluation Technique) methods, which were applied to an index developed using fuzzy logic. The index was then validated by conducting sensitivity and comparative analyses on a database from field sampling campaigns conducted in various small municipal DSs in two Canadian provinces: Quebec and Newfoundland and Labrador. Finally, the drinking water quality index was applied to a database of the DS in Quebec City, Canada. Sensitivity and comparative analyses revealed that the developed index could allow for the characterization of water sample quality and could prove useful for prioritizing interventions in the DS. The index was also useful for representing the spatial variability of water quality, and provided nuanced information about water quality, especially when the water quality parameter values complied with guidelines and regulations. These results provide a transferable and integrated approach for developing customized drinking water quality indices. This study will help pave the way for water quality managers to better prevent episodes of possible water quality deterioration.
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We acknowledge the City of Quebec for providing water quality data. We are especially grateful to the panellists that agreed to participate in this study.
This study received funding from the National Research Council of Canada.
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Scheili, A., Delpla, I. & Rodriguez, M.J. Development of a drinking water quality index based on a participatory procedure using mixed multicriteria methods. Environ Monit Assess 192, 558 (2020). https://doi.org/10.1007/s10661-020-08516-7
- Expert panel
- Fuzzy logic
- Water quality index
- Multicriteria methods