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The main purpose of a water distribution system (WDS) is to deliver safe water of desirable quality, quantity and continuity to consumers. However, in many cases, a WDS fails to fulfill its goal owing to structural and associated hydraulic failures and/or water quality failures. The impact of these failures can be reduced significantly if preventive actions are taken based on their potential of occurrences or if a failure occurs and is detected within a minimum period of time after its occurrence. The aim of this research was to develop a forensic system for WDS failures. As part of the proposed forensic analysis, a framework has been developed, which investigates structural and associated hydraulic failures as well as water quality failures and integrates all failure investigation under a single platform. Under this framework, four different models have been developed to evaluate and identify structural and associated hydraulic failures and water quality failures. If a failure is detected in the system, the framework is capable of identifying the most probable location of the failure. To investigate the effectiveness of the proposed framework, the developed models have been tested and implemented in different WDSs. [ABSTRACT FROM AUTHOR]

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Selecting and prioritizing monitoring locations (zones) in a water distribution network (DN) involves complex decision-making that warrants the use of risk-based decision-making. This paper couples the concept of risk with fuzzy sets and provides a simple approach to prioritizing monitoring locations in a DN. An index-based approach is proposed to estimate vulnerability, sensitivity and risk indices at a given DN location. The approach is based on fuzzy-based techniques that include fuzzy synthetic evaluation and fuzzy rule-base. Two types of analyses (deterministic and probabilistic) are used to demonstrate the proposed approach for a DN in Quebec City (Canada). Fifteen 'input factors' related to structural integrity, hydraulics, water quality and consumer sensitivity are used in the analyses. Based on the risk index results, the DN is divided into two parts. Sensitivity analysis results reveal that four factors, including two sensitivity factors (i.e. % population < 5 and > 75 yr) and two vulnerability factors (free residual chlorine and pipe breaks), explain 85% of the risk index variability. The usefulness of the proposed approach is demonstrated and strategies to improve the model are discussed. [ABSTRACT FROM AUTHOR]

Source water protection (SWP) is an important step in the implementation of a multi-barrier approach that ensures the delivery of safe drinking water. Available decision-making models for SWP primarily use complex mathematical formulations that require large data sets to perform analysis, which limit their use. Moreover, most of them cannot handle interconnection and redundancy among the parameters, or missing information. A fuzzy-based model is proposed in this study to overcome the above limitations. This model can estimate a reduction in the pollutant loads based on selected SWP strategies (e.g., storm water management ponds, vegetated filter strips). The proposed model employs an export coefficient approach and account for the number of animals to estimate the pollutant loads generated by different land usages (e.g., agriculture, forests, highways, livestock, and pasture land). Water quality index is used for the assessment of water quality once these pollutant loads are discharged into the receiving waters. To demonstrate the application of the proposed model, a case study of Page Creek was performed in the Clayburn watershed (British Columbia, Canada). The results show that increasing urban development and poorly managed agricultural areas have the most adverse effects on source water quality. The proposed model can help decision makers to make informed decisions related to the land use and resource allocation. [Copyright &y& Elsevier]