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A probabilistic approach that considers the entire lifecycle cost of the water pipeline, accounting for deterioration rate, failure consequences, cost of rehabilitation, accuracy and cost of inspection/condition assessment, cost of emergency repair versus planned intervention and cost of total pipe replacement was introduced in an earlier paper. The approach allows us to combine expert-opinion (semi-informative assessment) with hard field data. New hard field data (e.g., failure events, inspection/condition assessment results) continually become available throughout the life of the pipeline. This incoming data stream can be incorporated into the analysis to provide robust, well-informed and reproducible assessment of deterioration rate and remaining life. The framework was implemented in an MS-Excel-based decision support tool, referred to as pipeline inspection decision analyzer (PIDA). This paper demonstrates the practical application of the proposed framework in the real world through comprehensive case studies, data for which were obtained from collaborating Canadian and US water utilities and pipeline owners. As is always the case in reality, most pipeline owners did not have all the required data to carry out a fully informed analysis. We illustrate how one might deal with missing data, how PIDA may be used to arrive at well-supported, rational decisions on when to deploy inspection and condition assessment, what techniques/technologies to select among competing ones and when it is time to stop assessing the pipeline condition and plan for replacement. Sensitivity analyses are also conducted to explore how various assumptions, necessitated by uncertainty, may impact analysis results. [ABSTRACT FROM AUTHOR]

Much research effort has been dedicated to the development of optimal strategies for rehabilitation and/or replacement of water mains. Some of the methods are intended for high-level planning of groups or cohorts of pipes, while others address low-level scheduling of individual water mains. This paper focuses on the latter aspect. An approach is proposed for the efficient scheduling of individual water mains for replacement in a short to medium predefined planning period and subject to various budgetary constraints. This approach also accounts for economies of scale considerations as well as harmonization with other known infrastructure works. A multiobjective genetic algorithm scheme is used as a tool to search a vast combinatorial solution space, comprising various combinations of pipe replacement schedules. DOI: 10.1061/(ASCE)WR.1943-5452.0000062 CE Database subject headings: Water distribution systems; Pipes; Algorithms; Economic factors; Rehabilitation. Author keywords: Water mains; Pipes; Renewal planning; Multiobjective genetic algorithm; Roadwork; Economies of scale.

This paper describes an approach enabling well-supported, rational decisions about when to deploy inspection and condition assessment for high-consequence water pipelines, which techniques and technologies to select, and when to stop assessing pipeline condition and plan for replacement. The proposed probabilistic approach considers the entire life-cycle cost of the pipeline, accounting for deterioration rate, failure consequences, cost of rehabilitation, accuracy and cost of inspection/condition assessment, cost of emergency repair versus planned intervention, and cost of total pipeline replacement. The approach allows combining expert opinion (semi-informative assessment) with hard field data (historical failures, and inspection and condition assessment results) into a robust, well-informed, and reproducible assessment of pipeline deterioration rate. The approach also allows pipeline owners to incorporate new field data, which in turns permits continually updating the assessment of the pipeline condition. The approach also estimates the remaining life of the pipeline, in anticipation of its complete replacement. End-of-life is defined as the time at which it is no longer economical to continue repair or rehabilitation, and full replacement is economically preferable. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic affected the operation of water utilities across the world. In the context of utilities, new protocols were needed to ensure that employees can work safely, and that water service is not interrupted. This study reports on how the operations of 27 water utilities worldwide were affected by the COVID-19 pandemic. Interviews were conducted between June and October 2020; respondents represent utilities that varied in population size, location, and customer composition (e.g., residential, industrial, commercial, institutional, and university customers). Survey questions focused on the effects of the pandemic on water system operation, demand, revenues, system vulnerabilities, and the use and development of emergency response plans (ERPs). Responses indicate that significant changes in water system operations were implemented to ensure that water utility employees could continue working while maintaining safe social distancing or alternatively working from home. A total of 23 of 27 utilities reported small changes in demand volumes and patterns, which can lead to some changes in water infrastructure operations and water quality. Utilities experienced a range of impacts on finances, where most utilities discussed small decreases in revenues, with a few reporting more drastic impacts. The pandemic revealed new system vulnerabilities, including supply chain management, capacity of staff to perform certain functions remotely, and finances. Some utilities applied existing guidance developed through ERPs with slight modifications, other utilities developed new ERPs to specifically address unique conditions induced by the pandemic, and a few utilities did not use or reference their existing ERPs to change operations. Many utilities suggested that lessons learned would be used in future ERPs, such as personnel training on pandemic risk management or annual mock exercises for preparing employees to better respond to emergencies. [ABSTRACT FROM AUTHOR]

Water transmission and distribution systems are critical urban infrastructure. The aging of water mains can lead to increased breakage rate, decreased hydraulic capacity, and deterioration of water quality. Condition assessment of water mains encompasses building computational model of failures, discerning distress indicators from inspection, rating health condition, and forecasting future failures. In this process, computational intelligence helps to achieve high-level awareness of system condition and facilitates the decision making in water main renewal and rehabilitation using the combined information from field knowledge, historical records, inspection results, and sensory data. This paper reviews computational approaches to achieve condition assessment of water mains. Inspection and sensor technologies involved in the assessment process are also briefly discussed. [ABSTRACT FROM PUBLISHER]

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 [ABSTRACT FROM AUTHOR]

Deterioration in cast iron mains manifests itself in the form of corrosion. External corrosion is typically found to occur in pipes buried in corrosive soils while internal corrosion is dependent on water chemistry and flow characteristics. In the literature, corrosion of cast iron pipes (external and internal) is typically characterized by corrosion pit depth even though corroded area and corroded pit volume as well as pit location may enhance this characterization. Knowledge of these corrosion pit properties permits the assessment of its structural integrity. Typically, internal and external corrosion pits and corroded areas are observed to occur in many irregular shapes and sizes, which make their characterization a challenge. This paper describes extreme value statistical models that can be used to estimate external and internal corrosion pit depths in cast iron pipes using indirect properties or parameters. The goal of these corrosion models is to be able to predict corrosion pit depth based on available data with an acceptable degree of confidence. The external corrosion model is calibrated using external corrosion data collected by Thames Water Utilities Ltd (TWUL) and subsequently validated with data obtained from the inspection of four cast iron pipe lengths. The internal corrosion model was calibrated using internal corrosion data but sufficient appropriate data was not available for its validation. [ABSTRACT FROM AUTHOR]

Ductile iron pipes have been used in North America since the late 1950s. This paper describes research that endeavored to gain a thorough understanding of the geometry of external corrosion pits and the factors (e.g., soil properties, appurtenances, and service connections) that influence this geometry. This understanding is subsequently used in the companion paper to devise a sampling scheme and to infer the condition of ductile iron buried water mains. Soil corrosivity is not a directly measurable parameter, and pipe external corrosion is primarily a random phenomenon. The literature is replete with methods and systems that attempt to use soil properties (e.g., resistivity, pH, and redox potential) to quantify soil corrosivity and subsequently predict pipe corrosion. In this research, varying lengths of ductile iron pipes were exhumed by several North American water utilities. The exhumed pipes were cut into short sections, sandblasted, and tagged. Soil samples were also obtained at discrete locations along the exhumed pipe. Pipe sections were scanned for external corrosion using a specially developed laser scanner. Scanned corrosion data were processed using specially developed software to obtain information on pit depth, pit area, and pit volume. Statistical analyses were subsequently performed on these three geometrical attributes. Various soil characteristics were investigated to determine their impact on the geometric properties of the corrosion pits. Subsequently, a method is proposed to assess the condition of a ductile iron pipe, based on the geometry of corrosion pits of several samples extracted along the pipe. This paper describes the pipe exhumation, data preparation, and statistical analysis of corrosion pits. The companion paper describes a sampling scheme to infer pipe condition of ductile iron buried water mains. [ABSTRACT FROM AUTHOR]

Ductile iron (DI) pipes have been used in North America since the late 1950s. This paper describes how understanding gained on the geometry of external corrosion pits is used to devise a sampling scheme and to infer the condition of ductile iron buried water mains. The companion paper describes the exhumation of varying lengths of ductile iron pipes in four North American water utilities. The exhumed pipes were cut into sections, sandblasted, and tagged. Soil samples extracted along the exhumed pipe were also provided. Pipe sections were scanned for external corrosion using a laser scanner to produce corrosion pit data sets. Statistical analyses were performed on geometric properties of corrosion pits such as pit depth, pit area, and pit volume. These analyses were developed further to assess the impact of the different soil characteristics on these pit properties. This paper describes the investigation of appropriate sampling schemes to represent the statistical properties of ductile iron pipe corrosion. With known statistical properties, an approach is developed to infer the condition of the pipe. [ABSTRACT FROM AUTHOR]

Water utilities (especially in colder climates) often experience an increase in water main breaks in colder seasons. Some observers argue that this increase largely occurs during the period when there are sudden and prolonged changes in water and air temperatures, which typically occur during the late fall to early winter (temperature drop) and late winter to early spring periods (temperature rise). This paper examines the impact of temperature changes on observed pipe breakage rate for three pipe materials, namely, cast iron, ductile iron and galvanised steel. Several water and air temperature-based covariates were tested in conjunction with a non-homogeneous Poisson pipe break model to assess their impact on water main breaks, using data sets from three different water utilities in the USA and Canada. Temperature-based covariates, such as average mean air temperature, maximum air temperature increase and decrease, and how fast the air temperature increase and decrease over a specific period of days, were found to be consistently significant. While the availability of water temperature data (which most utilities do not have) can enhanced the prediction of water main breaks, it appears that air temperature data alone (which most utilities can access) are usually sufficient. [ABSTRACT FROM AUTHOR]

The evaluation of the risk of water quality failures in a distribution network is a challenging task given that much of the available data are highly uncertain and vague, and many of the mechanisms are not fully understood. Consequently, a systematic approach is required to handle quantitative-qualitative data as well as a means to update existing information when new knowledge and data become available. Five general pathways (mechanisms) through which a water quality failure can occur in the distribution network are identified in this article. These include contaminant intrusion, leaching and corrosion, biofilm formation and microbial regrowth, permeation, and water treatment breakthrough (including disinfection byproducts formation). The proposed methodology is demonstrated using a simplified example for water quality failures in a distribution network. This article builds upon the previous developments of aggregative risk analysis approach. Each basic risk item in a hierarchical framework is expressed by a triangular fuzzy number, which is derived from the composition of the likelihood of a failure event and the associated failure consequence. An analytic hierarchy process is used to estimate weights required for grouping noncommensurate risk sources. The evidential reasoning is proposed to incorporate newly arrived data for the updating of existing risk estimates. The exponential ordered weighted averaging operators are used for defuzzification to incorporate attitudinal dimension for risk management. It is envisaged that the proposed approach could serve as a basis to benchmark acceptable risks in water distribution networks. [ABSTRACT FROM AUTHOR]

Cathodic protection is a viable measure to extend the residual life of water mains and thus defer capital investments in their rehabilitation and renewal. The effectiveness of cathodic protection varies with the unique set of conditions under which it is applied and is therefore difficult to quantify. Consequently, reported case histories have been largely anecdotal and most often based on the observed reduction of water main breaks following the application of cathodic protection. Models to assess the impact of cathodic protection programs were proposed in a previous companion paper “Quantifying the Effectiveness of Cathodic Protection in Water Mains: Theory.” This paper describes the application of these models to five groups of water mains from two water utilities that have had on-going programs of hot spot and retrofit cathodic protection. The case histories show that cathodic protection programs (hot spot and retrofit strategies) have had a significant effect on reducing breakage rates, however, in some cases it appears that the much cheaper hot spot strategy is sufficiently effective and there is no need to retrofit as well. The proposed analytical methods should assist water utilities to optimize the implementation and scheduling of future cathodic protection programs. [ABSTRACT FROM AUTHOR]

Intrusion of contaminants into water distribution networks requires the simultaneous presence of three elements: contamination source, pathway and driving force. The existence of each of these elements provides ‘partial’ evidence (typically incomplete and non-specific) to the occurrence of contaminant intrusion into distribution networks. Evidential reasoning, also called Dempster–Shafer theory, has proved useful to incorporate both aleatory and epistemic uncertainties in the inference mechanism. The application of evidential reasoning to assess risk of contaminant intrusion is demonstrated with the help of an example of a single pipe. The proposed approach can be extended to full-scale water distribution networks to establish risk-contours of contaminant intrusion. Risk-contours using GIS may help utilities to identify sensitive locations in the water distribution network and prioritize control and preventive strategies. [ABSTRACT FROM AUTHOR]

The effective management of failure risk of buried infrastructure assets requires knowledge of their current condition, their rate of deterioration, the expected consequences of their failure and the owner's (decision-maker) risk tolerance. Fuzzy-based techniques seem to be particularly suited to modeling the deterioration of buried infrastructure assets, for which data are scarce, cause-effect knowledge is imprecise and observations and criteria are often expressed in vague (linguistic) terms (e.g., ‘good’, ‘fair’ ‘poor’ condition, and so on). The use of fuzzy sets and fuzzy-based techniques helps to incorporate inherent imprecision, uncertainties and subjectivity of available data, as well as to propagate these attributes throughout the model, yielding more realistic results. This paper is the second of two companion papers that describe an entire method of managing risk of large buried infrastructure assets. The first companion paper describes the deterioration modeling of buried infrastructure assets, using a fuzzy rule-based, non-homogeneous Markov process. This paper describes how the fuzzy condition rating of the asset is translated into a possibility of failure. This possibility of failure is combined with the fuzzy failure consequences to obtain fuzzy risk of failure throughout the life of the pipe. This life-risk curve can be used to make effective decisions on pipe renewal. These decisions include when to schedule the next inspection and condition assessment or alternatively, when to renew a deteriorated pipe, and what renewal alternative should be selected. [ABSTRACT FROM AUTHOR]

Dearth of data is the greatest acknowledged obstacle to the deterioration modeling of the buried infrastructure assets. In the last two decades numerous models have been proposed with a greater emphasis on Markovian Deterioration Processes (MDP). The MDP requires that the condition of the deteriorating system be encoded as an ordinal condition rating, based on numerous distress indicators obtained possibly from direct and indirect observations, as well as from non-destructive tests. The encoding of distress indicators into condition rating is inherently imprecise and involves subjective judgment. This imprecision is not considered, let alone propagated in the traditional application of the MDP. In this paper a new approach is presented to model the deterioration of buried infrastructure assets using a fuzzy rule-based, non-homogeneous Markov process. This deterioration model yields the ‘possibility’ of failure at every time step along the life of the asset. The use of fuzzy sets and fuzzy techniques help to incorporate the inherent imprecision and subjectivity of the data, as well as to propagate these attributes throughout the model, yielding more realistic results. This paper is the first of two companion papers that describe a complete method of managing failure risk of large buried infrastructure assets. The second companion paper describes how the condition ratings along the life of the asset are converted to risk values and how effective decisions can be made about the renewal and/or scheduling the next inspection of the asset. [ABSTRACT FROM AUTHOR]

An important step towards the assessment and management of failure risk in large-diameter (transmission) water mains is to observe distress indicators through scheduled inspections (using non-destructive or visual techniques) and translate these into condition ratings. Condition rating reflects an aggregate state of the pipe's health. Distress indicators are physical manifestations of the ageing process. The type (or form) and location of observed distress indicators in large-diameter mains are dependent on the pipe material and its surrounding environment. The physicochemical processes that promote ageing are often not understood well enough to merit an adequate physicochemical (based on mechanics or electrochemistry or microbiology) model. Further, the encoding of distress indicators into condition rating is inherently imprecise and involves subjective judgement. Fuzzy logic-based tools enable the use of engineering judgement, experience and scarce field data to translate the level of distress to condition ratings. This paper describes the translation of distress indicators detected by non-destructive or visual techniques into fuzzy condition ratings. Examples of distresses observed in prestressed cylinder concrete pipes (PCCP) and cast iron pipes are used to illustrate the proposed method. [ABSTRACT FROM AUTHOR]

A fuzzy-based method is proposed to evaluate soil corrosivity from soil properties such as soil resistivity, pH, redox potential, sulfide content, and soil type. The fuzzy-based method considers three levels of soil corrosivity, noncorrosive, moderately corrosive, and corrosive. This is in contrast to the commonly used 10-point scoring (10-P) method that has only two classes, corrosive and noncorrosive. Membership functions for each of the soil properties are used to quantify their affinity to the level of soil corrosivity. These membership values form an evaluation matrix from which a weighted vector is developed using pair-wise soil property comparisons. The final classification is determined from the cross product of the weighted vector and the evaluation matrix. Two case studies are examined to validate the application of the proposed fuzzy-based method to predict soil corrosivity, and the results are compared to the 10-P method. Both case studies showed that the fuzzy-based method outperformed the 10-P method. [ABSTRACT FROM AUTHOR]

The pathways, through which water quality in the distribution network can be compromised, may be classified into five categories: intrusion of contaminants into the distribution system (e.g. through cross connection); regrowth of bacteria in pipes and distribution storage tanks; water treatment breakthrough; leaching of chemicals or corrosion products from system components (pipes, tanks, liners, etc.); and permeation of organic compounds through plastic pipe and pipe components in the system. Quantification and characterization of the various risk factors in water distribution systems is a difficult task. Many kilometer of pipes of different ages and materials, uncertain operational and environmental conditions, unavailability of reliable data, and lack of understanding of some factors and processes affecting pipe performance make it extremely challenging. It is often difficult to identify or validate specific cause(s) for water contamination or waterborne disease outbreak because real-time data are rarely, if ever, available. For these reasons, high uncertainties are inherent in any risk measure that may be assigned to the distribution system. Further, the current inability to precisely quantify most of these risks may warrant the usage of a quantitative-qualitative framework. In this paper, a framework is presented for the analysis of aggregative risk associated with water quality failure in the distribution system. Each risk item is defined by the product of the likelihood of a failure event and its consequence (peril). Both the likelihood and the consequences of a failure event are defined using fuzzy numbers to capture vagueness in the qualitative linguistic definitions. A multi-stage hierarchical model of aggregative risk for water quality failure is developed. An analytic hierarchy process is used for estimating the priority matrix (weights) for grouping risk attributes. The framework is applied on a simplified structure of risk hierarchies for a water distribution system. [ABSTRACT FROM AUTHOR]

Cathodic protection is a viable measure to extend the residual life of water mains and thus defer capital investments in their rehabilitation and renewal. The effectiveness of cathodic protection varies with the unique set of conditions under which it is applied, and it is difficult to confirm or validate whether its application can be considered successful. Therefore, the reported success histories have been largely anecdotal and most often based on the reduction of water main breaks using cathodic protection. This paper describes methodologies and associated models to quantify and assess the performance of cathodic protection programs implemented by water utilities. The effectiveness of cathodic protection programs applied under various conditions can be determined and weighed against their costs in order to maximize the benefit from their implementation. These proposed methodologies and models should assist water utilities to optimize the implementation and scheduling of future cathodic protection programs. A companion paper, “Quantifying Effectiveness of Cathodic Protection in Water Mains: Case Studies,” describes the application of proposed models to assess the impact of cathodic protection programs. [ABSTRACT FROM AUTHOR]

A decision framework is introduced to assist municipal engineers and planners to optimize decisions regarding the renewal of large infrastructure assets such as water transmission pipes, trunk sewers, or other assets with high costs of failure, inspection, and condition assessment. The proposed decision framework identifies a need for immediate intervention or, alternatively, enables optimization of the scheduling of the next inspection and condition assessment. The deterioration of the asset is modeled as a semi-Markov process and is thereby discretized into condition states. The waiting times in each state are assumed to be random variables with “known” probability distributions. If pertinent data are scarce (as is typical in most municipalities) these probability distributions can be initially derived based on expert opinion. These distributions will then be continually updated as observed deterioration data are collected over time. Monte Carlo simulation is used to calculate the distributions of the cumulative waiting times. Conditional survival probabilities are used to compile age-dependent transition probability matrices in the various states. The expected discounted total cost associated with an asset (including cost of intervention, inspection, and failure) is computed as a function of time. The time to schedule the next inspection/condition assessment is when the total expected discounted cost is minimum. Immediate intervention should be planned if the time of minimum cost is less than a threshold period (2 to 3 years) away. A computer program is prepared for demonstration and proof of concept. The decision framework lends itself to a computer application fairly easily. Although usable in its current form, this paper identifies some issues that require as yet unavailable data as well as more research in order to develop the framework into a comprehensive application tool. [ABSTRACT FROM AUTHOR]

The evaluation of the risk of water quality failures in a distribution network is a challenging task given that much of the available data are highly uncertain and vague, and many of the mechanisms are not fully understood. Consequently, a systematic approach is required to handle quantitative-qualitative data as well as a means to update existing information when new knowledge and data become available. Five general pathways (mechanisms) through which a water quality failure can occur in the distribution network are identified in this article. These include contaminant intrusion, leaching and corrosion, biofilm formation and microbial regrowth, permeation, and water treatment breakthrough (including disinfection byproducts formation). The proposed methodology is demonstrated using a simplified example for water quality failures in a distribution network. This article builds upon the previous developments of aggregative risk analysis approach. Each basic risk item in a hierarchical framework is expressed by a triangular fuzzy number, which is derived from the composition of the likelihood of a failure event and the associated failure consequence. An analytic hierarchy process is used to estimate weights required for grouping noncommensurate risk sources. The evidential reasoning is proposed to incorporate newly arrived data for the updating of existing risk estimates. The exponential ordered weighted averaging operators are used for defuzzification to incorporate attitudinal dimension for risk management. It is envisaged that the proposed approach could serve as a basis to benchmark acceptable risks in water distribution networks.