Water Quality Indices (WQI) with Special Reference to CCME-WQI: Evolution, Methodological Framework, and Applications in Riverine Systems

Abstract

Assessment of water quality is essential for safeguarding human health, sustaining aquatic ecosystems, and supporting effective water resource management. Owing to the multidimensional nature of water quality datasets, Water Quality Indices (WQIs) have emerged as practical tools for integrating complex physicochemical information into a single, interpretable metric. This mini review synthesises the conceptual evolution, structural framework, and methodological components of WQI models, with particular emphasis on parameter selection, sub-indexing, weighting schemes, and aggregation functions. Special attention is given to the Canadian Council of Ministers of the Environment Water Quality Index (CCME-WQI), highlighting its statistical foundation, flexibility, and widespread applicability in riverine environments. The review summarises global applications of CCME-WQI across diverse hydro-climatic and pollution contexts, demonstrating its effectiveness in detecting spatial variability, pollution gradients, and deviations from water quality objectives. Key limitations of conventional WQI approaches, including subjectivity and eclipsing effects, are also discussed. Finally, future research directions are outlined, emphasising the integration of biological indicators, land-use drivers, and data-driven techniques to enhance the ecological relevance of WQI-based assessments. Therefore, this review emphasizes the continued relevance of CCME-WQI as a robust decision-support tool for river water quality assessment and sustainable river basin management.

Introduction

Water Quality Indices (WQIs) are essential tools for assessing, monitoring, and communicating the status of water resources, particularly in rivers, which support complex ecological processes and biodiversity. WQIs condense multiple physicochemical parameters into a single, interpretable numerical value, facilitating evaluation for scientists, policymakers, managers, and the public.

Key Points

1. Importance of Water Quality Assessment

• Ensures safe drinking water, irrigation, recreation, and healthy aquatic ecosystems.

• Continuous monitoring of rivers is crucial due to biodiversity support and ecological complexity.

• Reliable water quality data inform policy formulation, conservation planning, and sustainable resource management.

2. Evolution of WQIs

• Horton introduced the first mathematical framework combining multiple water quality variables.

• NSF-WQI refined this method with improved parameter selection and weighting.

• CCME-WQI (2001, Canada) evolved from the British Columbia WQI for broader applicability.

• Modern developments include multivariate statistics, soft computing, AI, and machine learning for optimization.

• Over 35 WQIs have been developed globally, reflecting regional priorities and applications.

3. Structural Framework of WQI Models

Most WQI models follow a four-step process:

1. Selection of parameters based on availability, expert judgment, and environmental relevance.

2. Transformation to unitless sub-indices (optional in some models like CCME-WQI).

3. Assignment of weights according to parameter importance.

4. Aggregation into a single index score and classification into water quality grades.

4. Parameter Selection and Weighting

• Parameters typically include oxygen availability, eutrophication indicators, dissolved substances, and health-related contaminants.

• Some WQIs use unequal weighting, summing to 1; others like CCME-WQI skip weighting.

• Aggregation combines sub-indices or concentrations into a single score to simplify interpretation.

5. Significance of WQIs

• Provide a simple, comprehensible measure of water quality for the public and stakeholders.

• Aid in identifying pollution hotspots, seasonal variations, and long-term trends.

• Useful for evaluating restoration, rejuvenation, and treatment program effectiveness.

• Assist in assessing impacts of pre- and post-developmental activities on river health.

6. Limitations of WQIs

• Time and spatial limitations may affect reliability.

• Can be ambiguous or subjective, relying on expert judgment.

• Eclipsing effect: poor quality in one parameter may be masked by acceptable values in others, potentially misrepresenting overall water quality.

• A single number may not capture all water quality information, requiring complementary assessments.

7. Global Applications of CCME-WQI

• Developed in 2001 from British Columbia WQI.

• Requires minimum four water quality variables.

• Uses three components: scope, frequency, and amplitude, reflecting extent, consistency, and magnitude of deviations from water quality objectives.

Examples of Applications:

1. Bangladesh: Surma River – classified as poor due to anthropogenic pressures.

2. Algeria: Tafna River – CCME-WQI effectively assessed drinking water suitability.

3. Egypt: Nile River – captured spatial variation in water quality.

4. Turkey: Coruh River – detected contamination in mountainous, high-energy river systems.

5. India:

   • Yamuna River – identified deterioration from urban and industrial inputs.

   • Damodar River – captured industrially impacted spatial variability.

   • Mundeswari River – showed pronounced spatial differences under cumulative human pressures.

8. Summary

The CCME-WQI provides a robust, interpretable framework for river health assessment, integrating multiple water quality parameters into a single index. It enables the identification of pollution trends, spatial differences, and temporal variations, supporting effective river management, policy decisions, and public awareness, while acknowledging that complementary measurements are needed to capture complete water quality information.

Conclusion

Water Quality Indices have emerged as indispensable tools for synthesising complex water quality datasets into interpretable metrics that support river health assessment and environmental decision-making. Among the various indices developed globally, the CCME-WQI stands out due to its methodological simplicity, flexibility in parameter selection, and robust statistical foundation. Its widespread application across diverse hydrological, geographical, and pollution contexts demonstrates its reliability for assessing spatial variability and overall river water quality status. However, conventional WQI approaches remain limited by subjectivity, parameter eclipsing, and the exclusion of biological and landscape-level information. Future research should therefore focus on integrating biological indicators, land-use drivers, and advanced data-driven techniques to enhance the ecological relevance and management utility of WQI-based assessments, particularly in increasingly stressed riverine systems.

References

[1] R. K. Verma, S. Murthy, R. K. Tiwary, and S. Verma, “Development of simplified WQIs for assessment of spatial and temporal variations of surface water quality in Upper Damodar River Basin, eastern India,” Applied Water Science, vol. 9, no. 1, pp. 1–15, 2019, doi: 10.1007/s13201-019-0893-0. [2] M. K. Mahato, A. K. Singh, P. K. Singh, and G. Singh, “Evaluation of factors influencing surface water quality in a coalfield area of Damodar Valley, India,” International Journal of Environmental Analytical Chemistry, pp. 1–23, 2021, doi: 10.1080/03067319.2021.1946685. [3] P. Ghosh and A. K. Panigrahi, “Evaluation of water quality of Mundeswari River in eastern India: A water quality index (WQI) based approach,” Journal of Applied and Natural Science, vol. 15, no. 1, pp. 379–390, 2023, doi: 10.31018/jans.v15i1.4340. [4] K. R. Singh, A. P. Goswami, A. S. Kalamdhad, and B. Kumar, “Surface water quality and health risk assessment of Kameng River (Assam, India),” Water Practice and Technology, vol. 15, no. 4, pp. 1190–1201, 2020, doi: 10.2166/wpt.2020.090. [5] T. Abbasi and S. A. Abbasi, “Water-quality indices: Looking back, looking ahead,” in Water Quality Indices, T. Abbasi and S. A. Abbasi, Eds. Amsterdam, The Netherlands: Elsevier, 2012, pp. 353–356, doi: 10.1016/B978-0-444-54304-2.00016-6. [6] S. Gupta and S. K. Gupta, “A critical review on water quality index tool: Genesis, evolution and future directions,” Ecological Informatics, vol. 63, p. 101299, 2021, doi: 10.1016/j.ecoinf.2021.101299. [7] A. Lumb, T. C. Sharma, and J.-F. Bibeault, “A review of genesis and evolution of water quality index (WQI) and some future directions,” Water Quality, Exposure and Health, vol. 3, no. 1, pp. 11–24, 2011, doi: 10.1007/s12403-011-0040-0. [8] A. Najah Ahmed et al., “Machine learning methods for better water quality prediction,” Journal of Hydrology, vol. 578, p. 124084, 2019, doi: 10.1016/j.jhydrol.2019.124084. [9] M. G. Uddin, S. Nash, and A. I. Olbert, “A review of water quality index models and their use for assessing surface water quality,” Ecological Indicators, vol. 122, p. 107218, 2021, doi: 10.1016/j.ecolind.2020.107218. [10] A. D. Sutadian, N. Muttil, A. G. Yilmaz, and B. J. C. Perera, “Development of a water quality index for rivers in West Java Province, Indonesia,” Ecological Indicators, vol. 85, pp. 966–982, 2018, doi: 10.1016/j.ecolind.2017.11.049. [11] Z. Ma, H. Li, Z. Ye, J. Wen, Y. Hu, and Y. Liu, “Application of modified water quality index (WQI) in the assessment of coastal water quality in main aquaculture areas of Dalian, China,” Marine Pollution Bulletin, vol. 157, p. 111285, 2020, doi: 10.1016/j.marpolbul.2020.111285. [12] A. D. Sutadian, N. Muttil, A. G. Yilmaz, and B. J. C. Perera, “Development of river water quality indices—A review,” Environmental Monitoring and Assessment, vol. 188, no. 1, p. 58, 2015, doi: 10.1007/s10661-015-5050-0. [13] M. W. Gitau, J. Chen, and Z. Ma, “Water quality indices as tools for decision making and management,” Water Resources Management, vol. 30, no. 8, pp. 2591–2610, 2016, doi: 10.1007/s11269-016-1311-0. [14] I. Zotou, V. A. Tsihrintzis, and G. D. Gikas, “Performance of seven water quality indices (WQIs) in a Mediterranean river,” Environmental Monitoring and Assessment, vol. 191, no. 8, pp. 1–14, 2019. [15] M. Terrado, D. Barceló, R. Tauler, E. Borrell, S. de Campos, and D. Barceló, “Surface-water-quality indices for the analysis of data generated by automated sampling networks,” TrAC Trends in Analytical Chemistry, vol. 29, no. 1, pp. 40–52, 2010, doi: 10.1016/j.trac.2009.10.001. [16] G. M. Munna, M. M. I. Chowdhury, A. M. Ahmed, S. Chowdhury, and M. M. Alom, “A Canadian water quality guideline–water quality index (CCME-WQI) based assessment study of water quality in Surma River,” Journal of Civil Engineering and Construction Technology, vol. 4, no. 3, pp. 81–89, 2013. [17] A. Hamlat, A. Guidoum, and I. Koulala, “Status and trends of water quality in the Tafna catchment: A comparative study using water quality indices,” Journal of Water Reuse and Desalination, vol. 7, no. 2, pp. 228–245, 2017. [18] A. M. Abdel-Satar, M. H. Ali, and M. E. Goher, “Indices of water quality and metal pollution of Nile River, Egypt,” Egyptian Journal of Aquatic Research, vol. 43, no. 1, pp. 21–29, 2017, doi: 10.1016/j.ejar.2016.12.006. [19] A. Bilgin, “Evaluation of surface water quality by using Canadian Council of Ministers of the Environment Water Quality Index (CCME WQI) method and discriminant analysis method: A case study Coruh River Basin,” Environmental Monitoring and Assessment, vol. 190, no. 9, p. 554, 2018, doi: 10.1007/s10661-018-6927-5. [20] D. Sharma and A. Kansal, “Water quality analysis of River Yamuna using water quality index in the national capital territory, India (2000–2009),” Applied Water Science, vol. 1, no. 3, pp. 147–157, 2011, doi: 10.1007/s13201-011-0011-4. [21] D. Haldar, S. Halder, P. Das (Saha), and G. Halder, “Assessment of water quality of Damodar River in South Bengal region of India by Canadian Council of Ministers of Environment (CCME) Water Quality Index: A case study,” Desalination and Water Treatment, vol. 57, no. 8, pp. 3489–3502, 2016, doi: 10.1080/19443994.2014.987168.

Copyright

Copyright © 2026 Pratyush Ghosh. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.