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Classification of heterotrophic plate counts (HPC) in a water distribution network: a fuzzy rule-based approach

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Abstract

Heterotrophic plate count (HPC) is one of the most common indicators used to monitor microbiological water quality in distribution networks. This paper applies and compares two fuzzy rule-based models to estimate HPC levels in a distribution network using a limited number of water quality parameters. The proposed fuzzy rule-based models include Mamdani and TSK (Takagi, Sugeno, and Kang) algorithms. The models are discussed through a case study of a distribution network (DN) in Quebec City (Canada). Both models properly estimate when HPC levels (datum per datum) are low, however their predictive ability is limited when HPC levels are high. When the outputs (HPC levels) are converted into four classes and the models are used as “classifiers”, their performances are very good. The average percent deviation is lower for the TSK model (15%) than for Mamdani model (17%). Implemented as “classifiers”, both models can be used for identifying vulnerable locations for microbiological contamination within the DN. Given the complexity of the growth of HPC bacteria in water distribution networks and the involvement of numerous contributory factors; results obtained are “promising”. Nevertheless, strategies to improve the models are also discussed.

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Notes

  1. For example, let’s consider a monitoring location at which the historical HPC levels are being classified as class-I (say 1–10 cfu/ml), but routine monitoring data estimate HPC level such that it belongs to class-IV (say >100 cfu/ml). This suggests that there might be a problem (e.g., contaminant intrusion, sloughing of biofilm, “mucky” pipes) around this monitoring location (probably just upstream).

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Acknowledgments

The authors would like to thank the Natural Sciences and Engineering Research Council of Canada (NSERC), the Hydro-Quebec Institute in Environment, Development and Society and the Embassy of the Republic of Haiti in Canada for their financial support. Thanks are also due to the National Research Council (NRC) of Canada for providing resources for the computations and simulations.

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Authors and Affiliations

  1. École Supérieure d’Aménagement du Territoire et de Développement Régional, Université Laval, 1724 Pavillon Savard, Québec, QC, G1V 0A6, Canada

    Alex Francisque

  2. Okanagan School of Engineering, The University of British Columbia, 3333 University Way, Kelowna, BC, V1V 1V7, Canada

    Alex Francisque & Rehan Sadiq

  3. École Supérieure d’Aménagement du Territoire et de Développement Régional, Université Laval, 1628 Pavillon Savard, Québec City, QC, G1V 0A6, Canada

    Manuel J. Rodriguez

  4. Department of Civil Engineering and Applied Mechanics, McGill University, 817 Sherbrooke Street West, Montreal, QC, H3A 2K6, Canada

    Luis F. Miranda

  5. Division de la Qualité de l’Eau, Service de l’Environnement, Ville de Québec, 1595, Mgr Plessis, Québec City, QC, G1M 1A2, Canada

    François Proulx

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  1. Alex Francisque
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Correspondence to Alex Francisque.

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Francisque, A., Rodriguez, M.J., Sadiq, R. et al. Classification of heterotrophic plate counts (HPC) in a water distribution network: a fuzzy rule-based approach. Int J Syst Assur Eng Manag 2, 286–300 (2011). https://doi.org/10.1007/s13198-012-0082-0

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