Costs and benefits of the development methods of drinking water quality index: A systematic review

The drinking water quality index (DWQI) transforms multiple water quality parameters into a dimensionless number, thus, presenting comprehensive status of drinking water in an intuitive manner. However, there are very few studies summarize the current progress of DWQI. Thus, we systematically reviewed 514 articles to evaluated the methods used in each DWQI developmental step with the aim of helping environmental workers choose the most appropriate index-generation model for local application. We observed that existing studies usually select 10-15 (55.4% of the studies) physicochemical parameters (such as Cl, pH, SO4, Ca, Mg etc.) to develop a DWQI. The weights of selected parameters are most often assigned using the five-scale method (53.7%), but these values varied considerably among the different studies due to the lack of clear evaluation standards. Semiquantitative and quantitative methods have been applied to overcome the subjectivity involved in these steps, including the analytical hierarchy process, information entropy, and factor analysis etc. The measurement results are normalized using the permissible limit, and multiplied by the corresponding weight, then added up to get the final DWQI result. Specifically, two distinct approaches, fuzzy logic and WQI adopted by Canadian Council of Ministers of the Environment (CCME-WQI) are discussed. Comparing with the more common approach based on classic set theory, fuzzy logic can better resolve the inherent uncertainty in the assessment of DWQI, whereas, the CCME-WQI is more appropriate for evaluating the spatiotemporal variations in DWQI over a given period. Some studies have assessed the robustness of the developed DWQI by conducting sensitivity analyses and its effectiveness was validated by comparisons with expert scores, existing WQIs or toxicological endpoints. Fifty-seven predefined classification schemes have been proposed to interpret DWQI value. As no one-size-fits-all approach exists for DWQI development, we recommended here to clarify the principles to be followed at each step, disclose the details of each method, and validate the developed index in future research. Meanwhile, additional efforts are required to develop new water quality monitoring methods and conduct DWQI studies on central water supply system.

Automated summary

This study systematically reviewed the progress of the drinking water quality index (DWQI) and assessed the methods used in each step of DWQI development. The results showed variations in the selection and weighting of physicochemical parameters, as well as the use of different methods to overcome subjectivity. Two distinct approaches, fuzzy logic and CCME-WQI, were discussed. The study also highlighted the need for clear principles, detailed method disclosure, and validation of the developed index in future research.