Search

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 © 2013 Elsevier Ltd. All rights reserved.)

Heterotrophic plate count (HPC) constitutes a common indicator for monitoring of microbiological water quality in distribution systems (DS). This paper aims to identify factors explaining the spatiotemporal distribution of heterotrophic bacteria and model their occurrence in the distribution system. The case under study is the DS of Quebec City, Canada. The study is based on a robust database resulting from a sampling campaign carried out in about 50 DS locations, monitored bi-weekly over a three-year period. Models for explaining and predicting HPC levels were based on both one-level and multi-level Poisson regression techniques. The latter take into account the nested structure of data, the possible spatiotemporal correlation among HPC observations and the fact that sampling points, months and/or distribution sub-systems may represent clusters. Models show that the best predictors for spatiotemporal occurrence of HPC in the DS are: free residual chlorine that has an inverse relation with the HPC levels, water temperature and water ultraviolet absorbance, both having a positive impact on HPC levels. A sensitivity analysis based on the best performing model (two-level model) allowed for the identification of seasonal-based strategies to reduce HPC levels.

For the last few decades, concerns have repeatedly been raised about deteriorating water mains in Canada. Small to medium sized water utilities are generally impacted more due to lack of technical and financial resources. This paper presents a user-friendly life cycle cost (LCC) analysis-based decision support tool to help these utility managers to prioritize water mains rehabilitation or replacement (R/R) strategies. The deterioration curves for water mains of different materials and sizes have been developed based on their likelihood of failure. The proposed model is implemented for the water supply network of City of Kelowna (Canada). It compares the costs of various R/R scenarios for each pipe over its life cycle and suggests the most cost-effective decision to the managers to efficiently allocate their limited resources. [ABSTRACT FROM AUTHOR]

All over the world water mains are under increasing threat due to aging, aggressive environmental factors, operational factors and inadequate maintenance. Extensive maintenance, repair and rehabilitation practices, or replacement of water mains are required to ensure an acceptable performance of water supply systems. Investment deficit for water system maintenance and rehabilitation has been estimated in billions. Small to medium sized water utilities are generally impacted more because of limited financial resources and lack of technical expertise. However, water mains integrity is of primary interest due to potential adverse consequences related to public health, safety, and heavy financial liabilities in case of a failure. This paper presents a user-friendly decision support tool to help managers of these water utilities to prioritize maintenance, repair, and replacement (M/R/R) strategies for water mains. This paper proposes a risk index approach which aggregates the water mains vulnerability and associated failure consequences. The developed tool can help decision-makers to rank the water mains and help to prioritize M/R/R strategies. The results have been integrated with a geographic information system that will allow a decision-maker to visualize the vulnerable zones within the network. The City of Kelowna water network is used to demonstrate the proposed approach. [ABSTRACT FROM AUTHOR]

Loss of water due to leakage is a common phenomenon observed practically in all water distribution systems (WDS). However, the leakage volume can be reduced significantly if the occurrence of leakage is detected within minimal time after its occurrence. This paper proposes a novel methodology to detect and diagnose leakage in WDS. In the proposed methodology, a fuzzy-based algorithm has been employed that incorporates various uncertainties into different WDS parameters such as roughness, nodal demands, and water reservoir levels. Monitored pressure in different nodes and flow in different pipes have been used to estimate the degree of membership of leakage and its severity in terms of index of leakage propensity (ILP). Based on the degrees of leakage memberships and the ILPs, the location of the nearest leaky node or leaky pipe has been identified. To demonstrate the effectiveness of the proposed methodology, a small distribution network was investigated which showed very encouraging results. The proposed methodology has a significant potential to help water utility managers to detect and locate leakage in WDS within a minimal time after its occurrence and can help to prioritise leakage management strategies. [ABSTRACT FROM AUTHOR]

This paper explores the application of the quality function deployment (QFD) approach to identify and prioritize factors to reconcile 'actual' risk with 'perceived' risk for drinking water in a distribution network. Consumers' complaints (regarding water odour, taste, colour and other problems) and consumers' perception about water safety are used to define customers' requirements (aka 'whats'). Twelve water quality parameters and distribution network properties (e.g. turbidity, pipe breaks) are used as indicators for drinking water quality -- the product characteristics (aka 'hows'). Correlations between 'whats' and 'hows' are established using data obtained from a case study. Opinions of experts in drinking water and consumers are used to define correlations between the 'what' 'microbial safety' and the 'hows'. The analytic hierarchy process allows prioritizing customer requirements. Three QFD-based methods are applied to prioritize factors affecting water quality in a distribution network. The proposed approach is demonstrated through a case study of a water distribution network in Quebec City (Canada). Results show that the factors that primarily affect customers' requirements include free residual chlorine, turbidity and trihalomethanes. Sensitivity analyses using three scenarios confirm the robustness of the proposed approach. Utility managers must take action, especially concerning these product characteristics, to satisfy customers' requirements. [ABSTRACT FROM AUTHOR]

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]