M. Shafiqul Islam

Leakage detection and location in water distribution systems using a fuzzy-based methodology

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.

Evaluating Water Quality Failure Potential in Water Distribution Systems: A Fuzzy-TOPSIS-OWA-based Methodology

The goal of a water distribution system (WDS) is to deliver safe water with desirable quality, quantity and continuity to the consumers. In some cases, a WDS fails to deliver safe water due to the compromise/ failure of water quality which may have devastating consequences. The frequency and consequence of a water quality failure (WQF) can be reduced if prognostic analysis and necessary remedial measures are taken on time. This study developed a prognostic model to predict WQF potential in a WDS. The study identifies important factors (parameters) which can directly and/or indirectly linked to WQFs. These factors are classified into two groups—the causes of WQF such as lack of free residual chlorine, or excess of total organic carbon, and the symptoms of WQF such as taste & odor, color which are in fact the effects of certain causes of WQF. The interrelationships among the symptoms and the causes have been established based on extensive literature review and elicited expert opinion. A fuzzy-TOPSIS-OWA-based model has been developed to identify the impacts of different influencing parameters on the overall WQF potential. The developed model has been implemented for a WDS in Quebec City (Canada). To study the impacts of uncertainties of the influencing factors, a Monte Carlo simulation-based sensitivity analysis has been carried out. It is anticipated that the developed model can help water utilities to understand the role of different factors on WQF.

Water distribution system failure: a framework for forensic analysis

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.

Data Fusion Methods for Human Health Risk Assessment: Review and Application

ABSTRACT The improved accessibility to data that can be used in human health risk assessment (HHRA) necessitates advanced methods to optimally incorporate them in HHRA analyses. This article investigates the application of data fusion methods to handling multiple sources of data in HHRA and its components. This application can be performed at two levels, first, as an integrative framework that incorporates various pieces of information with knowledge bases to build an improved knowledge about an entity and its behavior, and second, in a more specific manner, to combine multiple values for a state of a certain feature or variable (e.g., toxicity) into a single estimation. This work first reviews data fusion formalisms in terms of architectures and techniques that correspond to each of the two mentioned levels. Then, by handling several data fusion problems related to HHRA components, it illustrates the benefits and challenges in their application.

Data fusion-based risk assessment framework: an example of benzene

Environmental and health risk assessment projects involve processing of a large volume of uncertain information. To reduce uncertainties in the assessment process, the risk assessor evaluates a large volume of data from toxicological, exposure and health related databases. Being a data intensive assessment, for improved risk assessment, there is a need for these data to be harmonized and integrated by incorporating information from various sources and biological organizational criteria (e.g., gene, cellular, tissue, organ level health effects, if available). The main objective of this study is to have a front end or upstream approach towards an effective dynamic data fusion (DF)-based risk assessments. To achieve this goal, a generalized human health risk assessment and a system biology-based DF framework have been proposed. The proposed approach would be able to detect different trends and patterns and integrates various toxicological datasets from different biological organizational criteria (e.g., gene, cellular, tissue, organ level, if available) and integrates data from disparate sources. To demonstrate the effectiveness of the approach, both the proposed frameworks have been implemented in human health risk assessment for benzene originated from an illustrative example of a contaminated site. The application in this study shows that this approach can increase the efficiency of dynamic data integration and incorporation of toxicity pathway or system biology-based information in the human health risk analysis. Currently, the system biology facilitated DF framework is based on hypothesis driven modeling relationships between different bio-organizational criteria. Further work is needed to prove these relationships. For a data rich chemical example such as benzene, these relationships can be established based on the existing and the emerging knowledge-base on benzene toxicology.

Integrated Decision Support System for Prognostic and Diagnostic Analyses of Water Distribution System Failures

This paper presents an innovative decision support system (DSS) for prognostic and diagnostic analyses of water distribution system (WDS) failures. The framework of the DSS is based on four novel models developed and published by the authors of this paper. The four models include reliability assessment model, leakage potential model, leakage detection model, and water quality failure potential model. Information obtained from these models together with external information such as customer complaints, lab test results (if any), and historical information are integrated using Dempster-Shafer (D-S) theory to evaluate prognostic and diagnostic capabilities of the DSS. The prognostic capabilities of the DSS provide hydraulic and water quality states of a WDS whereas the diagnostic capabilities of the DSS help to identify the failure location with minimal time after the occurrence and will help to reduce false positive and false negative predictions. The framework has ‘unique’ capacity to bring the modeling information (hydraulic and Quality), consumer complaints, historical failure data, and laboratory test information under a single platform to perform a prognostic and diagnostic investigation of WDS failures (hydraulic and Quality). The proof of concept of the DSS has been demonstrated using data used in published four articles. The outcomes of this research widely addressed the uncertainties associated with WDS which improves the efficiency and effectiveness of diagnosis and prognosis analyses of WDS. It is expected that the developed integrated framework will help municipalities to make informed decisions to increase the safety, reliability and the security of public health.

Economic Analysis of Leakage in the Bangkok Water Distribution System

AbstractLoss of water caused by leakage is a common phenomenon observed in all water distribution systems (WDSs). The volume of leakage around the world is considerably high, and its control is crucial to meet the increasing water demand caused by rapid population growth and urbanization. The most important component of a leakage-control strategy is target setting in terms of economic level of leakage (ELL). The ELL is an economic indication depending on individual network conditions, operating system pressures, demands and their patterns, marginal cost of water, and operating practices. This paper discusses the economic aspects of leakage for a pilot district metered area (DMA) of the WDS of the Metropolitan Waterworks Authority (MWA) in Bangkok, Thailand. The study developed two nomographs for the quick estimation of ELL and active leakage-control cost (ALC) with minimal data analysis. The first nomograph shows the relationship between cost of leakage control, average operating pressure, and level of le...