| Abstract | The impact of deteriorating pipes on water quality (WQ) in the distribution network has not been consistently taken into account in decision making related to pipe renewals. In this paper, a detailed modeling approach based on fuzzy cognitive maps is developed using fuzzy rule-based models and fuzzy measures theory to investigate potential of WQ (physical, chemical, and biological) failure in distribution networks. Based on information and data obtained from preliminary analysis, literature, and expert opinion, a decision support tool named Q-WARP (water quality - water main renewal planner) is developed to consider uncertain, subjective/linguistic and/or incomplete data. Q-WARP provides a plausible way to represent and comprehend ill-defined and complex relationships such as those that govern WQ in the distribution network. The proposed model has the capacity to perform the 'baseline analysis' that performs risk assessment and risk evaluation; and the 'decision analysis' that performs risk management and guides decision making. The developed model has also been applied to a case study in Stanley Street (Philadelphia) to evaluate the model's capability. The results manifested that the model can efficiently assess the 'potential' for WQ failures and can also be used in decision making for WQ improvements by making infrastructure changes in distribution systems. |
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