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An introduction is presented in which author discusses articles on topics including focuses on "Sulfolane in contaminated sites: Environmental toxicity and bioremediation technologies" that examine treatment technologies of industrial solvent and sulfolane with adverse effects on human health.

In recent years, the development of renewable energy sources (RESs) and their integration with the conventional power network have increased significantly. Due to the power grid transformation brought about by the large penetration of power electronics converter‐based RESs such as wind and solar photovoltaic (PV), the operation and control of the interconnected power system has become a challenging task with respect to sustaining its stability and reliability. Power systems are confronted by several new stability issues because the dynamic behavior of converter‐interfaced renewable sources differs from conventional generation. In this respect, static synchronous compensator (STATCOM), a shunt connected flexible AC transmission system (FACTS), is recognized as a fundamental solution for maintaining power system stability. This paper presents a thorough and state‐of‐the‐art review of STATCOM control in wind‐ and/or PV‐interfaced power systems for enhancing system performance by addressing key stability issues related to rotor angle stability, voltage stability, and resonance stability. A comprehensive analysis of various control techniques of STATCOM based on conventional, adaptive, nonlinear, predictive, robust, and coordinated control and soft computing techniques is provided. Furthermore, the function of the grid‐side converter of the wind/PV plant as a STATCOM is also evaluated. Finally, the shortcomings of existing research are highlighted, current control challenges are presented, and several topics for future research are suggested. This paper provides researchers the opportunity to consider the current state of research and develop new control schemes for STATCOM to further improve the stability of modern power grids. [ABSTRACT FROM AUTHOR]

• Proposing a multi-model robust dynamic output feedback damping controller for the GCSC. • Investigating a two-step LMI approach for solving BMI optimization problem. • A multi-objective H 2 / H ∞ synthesis with regional pole-placement. • Power system operational uncertainties considering variations in operating conditions are represented as multi-model. In the recent decade, the power network has experienced a remarkable energy transition due to the large-scale integration of wind energy resources, especially converter-interfaced modern wind turbines. The increasing/decreasing wind penetration, on the other hand, unexpectedly affects the low frequency oscillations of the modern power grid. In this context, the proposed work adopts a multi-model multi-objective robust control framework to design a supplementary damping controller for the gate-controlled series capacitor (GCSC) to stabilize the hybrid power system with a permanent magnet synchronous generator (PMSG)-based off-shore wind farm (OSWF) and a doubly-fed induction generator (DFIG)-based onshore wind farm (ONWF). A bilinear matrix inequality (BMI) optimization problem, formulated as multi-objective synthesis considering H 2 / H ∞ performance along with pre-defined pole placement, is presented for the GCSC control design, which is solved by a two-step linear matrix inequality (LMI) approach. In addition, all LMI constraints are constructed based on the multi-model control framework to incorporate multiple operating conditions. Afterward, the significant improvement in the damping characteristics of the closed-loop system, covering a wide operating range, is confirmed using eigenvalue analysis. The effectiveness of the scheme is validated using two case studies based on the hybrid power system, subject to various disturbances and uncertainties. The simulation results show the robustness and higher damping performance of the proposed multi-model strategy, compared to a conventional and a robust damping controller, for mitigating power system oscillations alongside voltage fluctuations of the wind farms. [ABSTRACT FROM AUTHOR]

Environmental impact assessment of energy generation processes is essential to evaluate their contributions toward the global carbon footprint. Even though hydrogen is a non-carbonaceous energy source, the pathways undertaken for its production can have harmful environmental implications. Thus, this study focuses on investigating the exergoenvironmental performances of the copper-chlorine, iron-chlorine, and magnesium-chlorine thermochemical hydrogen generation processes. This study also performs a comparative exergoenvironmental analysis of the three processes. The performances of the various processes are examined based on of the environmental impact rates of exergy destruction, component-related environmental impact rates, cumulative environmental impact rates, and exergoenvironmental factors. The global warming potentials of the thermochemical cycles are also evaluated and compared for various electricity sources to obtain hydrogen. The modeling and simulation of each process are performed using Aspen-plus by considering various heat recovery approaches for thermal management. The results suggest that the environmental impact rates of exergy destruction are relatively much higher compared to the environmental impact rates associated with the components for all processes. Furthermore, the hydrolysis step yields the highest component-associated environment impact rate for all thermochemical cycles considered (Fe–Cl: 3497 mPts/h, Cu–Cl: 1997 mPt/h, and Mg–Cl: 910 mPts/h). Moreover, the magnesium-chlorine cycle results in the highest environmental impact rate of exergy destruction (650,328 mPts/h) while the iron-chlorine cycle has the highest component-related environmental impact rate (5219 mPts/h) among the three cycles. In addition, the global warming potential of the magnesium-chlorine cycle is relatively higher compared to the copper-chlorine cycle for several electricity sources. [Display omitted] • An exergoenvironmental analyses of three thermochemical cycles is performed. • Each cycle is incorporated with thermal management schemes for higher efficiencies. • Industrial waste flue gases are considered as a heat source for hydrolysis reaction. • A hydrogen production capacity of 668 kg/h is considered for each cycle. • A comparison of global warming potential for various electricity sources is made. [ABSTRACT FROM AUTHOR]

The aim of the study is to conduct an ecological risk assessment of accidental release of flowback water into freshwater body. Flowback water produced from the hydraulic fracturing process has a complex combination of high concentration of salts, organic compounds and metals. The toxicity of flowback water is assessed and an exposure assessment method for the inorganic constituents of the flowback water is developed. An equation for risk is derived to characterize the risk of the flowback water to the aquatic ecology. A case study is conducted for accidental release of hydraulic fracturing flowback water in Montney unconventional play trend in northern British Columbia. The flowback water quality data for 212 wells, including the concentrations of various salt ions, metal ions, and hydrogen sulfide, is collected for the assessment. The risk quotient is found to be 0.16 (<1), proving no significant risk to the aquatic ecosystem with 90% confidence. However, the overall results of the uncertainty and scenario analysis concludes that the risk to the ecology cannot be completely overlooked. Scenario analysis was done for monthly creek discharge and a relationship between risk quotient and the ratio of spill volume to the creek discharge was derived. [ABSTRACT FROM PUBLISHER]

Municipal solid waste treatment options are not necessarily pragmatic if the stakeholders in the system don't mutually agree on their shares of liabilities. Stakeholders will select an option if their benefits are maximized and costs are minimized. A decision support framework is required to assess various waste treatment options and predict the optimal decision, considering multiple criteria and conflicting preferences of multiple stakeholders. Because of the inherent complexity, uncertainty is unavoidable and should be acknowledged to enhance the reliability in the decision-making process. Uncertainties in the cost and benefit estimates, and stakeholders' ability in verbalizing their preferences and their knowledge about each other's priorities can impact the outcome of such environmental management problem. In this study, uncertainty assessment methods such as sensitivity analysis, fuzzy Analytical Hierarchy Process, and Bayesian games have been explored. A case study in Vancouver (BC, Canada) has been used as a proof of concept. [ABSTRACT FROM AUTHOR]

In this paper, an index-based approach is proposed to locate chlorine booster stations in a water distribution network (DN). Chlorination is a common practice for secondary disinfection, essential for protection against microbiological regrowth and contaminant intrusion. However, higher levels of free residual chlorine (FRC) may lead to unwanted disinfectant by-products (DBPs) and taste and odor complaints. Booster chlorination can be used to maintain minimum levels of FRC. This requires proper selection of booster locations. The approach proposed here uses a generic hydraulic and water quality modeling software programmers' toolkit to predict FRC and total trihalomethanes (TTHMs) converted, thereafter, into a water quality index (WQI). A heuristic algorithm maximum covering location problem (MCLP) used in optimization maximizes WQI. TTHM is converted into trihalomethane (THM) species using quadratic optimization, then to cancer and noncancer risk potentials. Finally, the required number of booster stations is recommended based on a trade-off analysis of risk potentials, WQI, and the life cycle cost of booster chlorination. For proof of concept, case studies are conducted in a hypothetical and a municipal DN. [ABSTRACT FROM AUTHOR]

Small to medium sized water utilities face serious challenges to meet broad sustainability objectives, because of technical, human and financial constraints and limited involvement in the inter-utility benchmarking. Most of these utilities are unable to address the performance gaps for various functional components, such as personnel, operational, financial, etc., of their water supply systems and rely on emergency response. Even if the information obtained from such benchmarking process is available, the outcome (indices) showing performance of these components, at the utility level, is useful for top level management. The operations management is more interested in the performance of sub-components (under each functional component) of the water supply systems within the utility. An intra-utility performance management model is conceptualized and developed for effective decision making at both the levels. A hierarchical based top-down approach initiates from overall sustainability objectives at the top, followed by primary and secondary performance measures of the sub-components, and indicators (basic building blocks) receive inputs from data/decision variables at the bottom. The model assesses the performance of each component and sub-component as ‘ high ’, ‘medium’ , or ‘low’ . Fuzzy based technique has been employed to deal with uncertainty issues due to data limitations and vagueness in expert knowledge. Sensitivity analysis helped to rank the indicators for their contribution in decision making. The model is implemented for a medium sized utility containing three sub-systems in the Okanagan Basin (BC, Canada). The results demonstrate the model's practicality to efficiently achieve sustainable performance in small to medium sized water utilities. [ABSTRACT FROM AUTHOR]

Small-sized to medium-sized water utilities (SMWU) face severe challenges to maximize the customer satisfaction (CS) because of operational failures, limited trained staff, and financial issues. Conventional methods are based on performance benchmarking and interviews, which might not be feasible at all times for SMWU. A novel risk-based framework is developed for improving CS by improving the reliability of water supply systems operating in a utility. The framework is primarily based on comprehensive analysis of customer complaints and staff's observations on related complaints. Customer dissatisfaction is evaluated in terms of risk of not meeting CS, which starts when a customer reports a complaint; however, a complete evaluation of CS depends on the duration between the time of the report and the response until the complaints' full resolution. Different categories of complaints are identified from an exhaustive record of a medium-sized utility in Okanagan Basin (British Columbia, Canada). For risk management, root cause analysis and failure mode effect analysis are performed. To address inherent uncertainties associated with data limitations and vagueness in decision makers' perception, fuzzy set theory is employed. The results show that almost half of the cumulative risk can be reduced with inspection and maintenance interventions which are not very expensive; however, the remaining risk reduction requires large-scale infrastructure improvements. [ABSTRACT FROM AUTHOR]

Safety assessment of oil and gas (O&G) pipelines is necessary to prevent unwanted events that may cause catastrophic accidents and heavy financial losses. This study develops a safety assessment model for O&G pipeline failure by incorporating fuzzy logic into Bayesian belief network. Proposed fuzzy Bayesian belief network (FBBN) model explicitly represents dependencies of events, updating probabilities and representation of uncertain knowledge (such as randomness, vagueness and ignorance). The study highlights the utility of FBBN in safety analysis of O&G pipeline because of its flexible structure, allowing it to fit a wide variety of accident scenarios. The sensitivity analysis of the proposed model indicates that construction defect, overload, mechanical damage, bad installation and quality of worker are the most significant causes for the O&G pipeline failures. The research results can help owners of transmission and distribution pipeline companies and professionals to prepare preventive safety measures and allocate proper resources. [ABSTRACT FROM PUBLISHER]

Disinfection with chlorine is a common practice to ensure secured drinking water, but results in potentially harmful disinfection by-products (DBPs), when excess chlorination is done. The US Environmental Protection Agency (US EPA) has established Stage 1 and Stage 2 disinfection by-product Rules (DBP rules) to control DBP exposure. A modified version of the Canadian Council of Ministries of the Environment water quality index (CCME WQI) is used to assess water quality. CCME WQI is a globally accepted index to assess water quality, but is too generic to be used for DBP rules. The study developed a scheme to make the index suitable for DBP rules. A scoring method based on an analytic hierarchy process (AHP) is applied to assign weights based on DBP rules. A previously modified CCME WQI (Islam et al., 2014) is adapted along with the weights to perform the assessment at the distribution network (DN). A case study was performed on 7 sampling stations in a Québec City DN. The spatial water quality variations are presented using kriging - a geostatistical method, which identifies the regions with relatively poor water quality and highlights the potential locations for re-chlorination points. The proposed assessment formulation is flexible to handle situations with limited data, which makes it especially suited to smaller municipalities. [ABSTRACT FROM AUTHOR]

An efficient waste treatment strategy should be cost-effective and minimize potential impacts on various stakeholders and the environment. This study proposes a decision framework that can model the stakeholder's conflicting priorities over the sustainability criteria, when selecting a municipal solid waste treatment option. The proposed framework compares life cycle sustainability impacts of selected options and develops a weighing scheme for combining impacts based on stakeholders' preferences. It then uses game theory to help the stakeholders fairly share the costs and benefits, and guides the stakeholders to reach an agreement on a mutually sustainable and pragmatic solution. In this study, the application of the framework to select a waste-to-energy technology for Vancouver, Canada is demonstrated. The case study discusses the prospect of producing refuse-derived fuel by cement industry and the municipality. Results show that the cement industry and the municipality may mutually benefit from the refuse-derived fuel, if the industry pays a tipping fee of $0.077–0.96 per kg waste to access the required amount of solid waste from the municipality. The outcome of the framework can help in the approval and application of an overall sustainable option by both stakeholders and in making the negotiation more efficient and timely. [ABSTRACT FROM AUTHOR]

Acid rock drainage (ARD) is a major environmental problem that poses significant environmental risks during and after mining activities. A new methodology for environmental risk assessment based on probability bounds and a geochemical speciation model (PHREEQC) is presented. The methodology provides conservative and non-conservative ways of estimating risk of heavy metals posed to selected endpoints probabilistically, while propagating data and parameter uncertainties throughout the risk assessment steps. The methodology is demonstrated at a minesite located in British Columbia, Canada. The result of the methodology for the case study minesite shows the fate-and-transport of heavy metals is well simulated in the mine environment. In addition, the results of risk characterization for the case study show that there is risk due to transport of heavy metals into the environment. [ABSTRACT FROM AUTHOR]

About 95% of the water supply systems in Canada are being operated by small-to-medium-sized water utilities (SMWU) serving populations less than 50,000. The representation of these utilities in National Water and Wastewater Benchmarking Initiative (NWWBI) is almost negligible due to less awareness, issues related to data availability, and financial constraints. In the present work, an inter-utility performance benchmarking model (IU-PBM) is developed, which entails consideration of 47 performance indicators (PIs) for different functional components of SMWU, such as water resources and environment, personnel, physical assets, quality of service, water quality and public health, and financial aspects. For performance benchmarking, 47 (linear, exponential, logarithmic, and polynomial) transformation functions have been established to translate the calculated PIs into performance levels between 10 and 100, which is based on literature, NWWBI reports, and expert judgment. The weights are estimated using a specific method from the literature for ranking of PIs by different water utilities in the Okanagan basin, British Columbia, Canada, and opinions of experts working in water infrastructure management. Finally, performance indices have been established by aggregating the transformed performance levels using the technique for order preference by similarity to ideal solution (TOPSIS) (i.e., based on the concept of relative closeness to the most desirable performance and remoteness from the least desirable performance). The IU-PBM results presented in the form of a web diagram demonstrate the utility's performance to the top management for pragmatic decision making. The proposed model has also been implemented for two SMWU operating in Okanagan Basin to evaluate its practicality. [ABSTRACT FROM AUTHOR]

In Canada, small to medium sized water utilities (SMWU) do not often participate in National Water and Wastewater Benchmarking Initiative due to lesser economies of scale, lack of resources, and data limitations. Consequently, such SMWU are managing their functional components (i.e., environmental, personnel, operational, physical assets, customer satisfaction, public health, and financial) without quantitatively assessing and knowing if they are meeting their performance objectives. A multilevel performance management framework, consisting of five modules has been developed and implemented for SMWU in BC, Canada. The framework provides an approach to identify and select the suitable performance indicators for SMWU, and to use them for inter-utility performance benchmarking under limited data. The subsequent modules can be used for detailed performance management at utility, system, and sub-component levels. The utility managers can effectively employ this framework to identify the underperforming functional components and can rationally take corrective actions, and address customer satisfaction with efficient inventory management and data analyses. [ABSTRACT FROM AUTHOR]

Small and medium sized water utilities (SMWU) are facing serious operational problems, and show less participation in benchmarking. Existing performance indicator (PI) systems developed for large water utilities need to be re-evaluated for SMWU. 114 Potential PIs were obtained in water resources and environment, personnel, operational, physical, water quality, quality of service and financial categories using a checklist. These PIs were evaluated against applicability, understandability, measurability and comparability criteria using the Elimination and Choice Translating Reality (ELECTRE) outranking method for multicriteria decision analysis. The criteria's weights and scoring of PIs were done through group decision making. The study results revealed thatELECTREis a suitable method when the preferences between various alternatives based on small differences of evaluations cannot be established. The network maps based on outranking results provides an opportunity to the utility management to encompass the most suitable PIs based on data availability and specific needs of their utility. [ABSTRACT FROM AUTHOR]

This paper deals with online water quality monitoring in distribution networks based on surrogate water quality parameters (WQPs). The present strategy is based on multi-level information fusion using hierarchical belief rule-based (BRB) systems. Networked fuzzy belief rule-based (NF-BRB) and high-level BRB systems are introduced for information fusion at the feature level. Primary and secondary features are extracted from online WQP signals. Primary features are analyzed using the NF-BRB system that is built through knowledge elicitation from experts. Secondary features are interpreted through the high-level BRB system that employs a fuzzy partitioning on the feature sets and a hybrid learning strategy for its rule base construction. Finally, the dynamic fuzzy evidential fusion is introduced to aggregate the local and spatial assessments in each analysis window. As an important contribution of this paper, we propose a new validation method for event detection in the water distribution network (WDN) based on adaptive projection of the signal patterns attributed to anomaly events, obtained through contamination experiments in a pilot facility, to the real WQP signals measured across the WDN. Single and composite contamination events based on several biological and chemical contaminants are simulated to evaluate the performance of the proposed framework in event detection. The proposed multi-level information fusion framework obtains a high detection rate and a reduced number of false negative and positive results. [ABSTRACT FROM AUTHOR]

With the increase in natural gas (NG) production in recent years, primarily from shale gas, some sources, including the US Environmental Protection Agency (EPA), have suggested that upstream methane emissions are increasing. Much of the recent controversy has centered on emissions during well drilling, testing, and completion even though emissions downstream of the wellhead are also of concern. The study critically assessed the current state of knowledge about the life cycle GHG footprint of NG, analyzed the assumptions, data and analysis methodologies used in the existing literature. This study comprehensively analyzed the emission of methane from different stage of the life of well for conventional and unconventional NG using the EPA's revised 2011 estimates as well as other existing literature and publicly available government data. The study proposed a probabilistic model to estimate the range of total GHG footprint of NG with varying probabilities. Through the bottom up approach starting from the well construction to the delivery of NG to the small user and using Monte Carlo simulation, the study identified the critical sources of fugitive emissions from the NG. As expected, emissions from well completion and periodic emissions (e.g. liquid unloading in the case of onshore conventional wells and workovers in the case of unconventional wells) are significant contributors to the overall GHG footprint of NG, and possess large opportunity for reduction. Finally the application of probabilistic model is demonstrated through a case study using the data from the Montney and Horn River shale gas basins in the Northern British Columbia to estimate the range of total GHG footprint of shale gas with varying probabilities. The study found that the GHG footprint of Montney and Horn River wells are much smaller than that of Barnett shale (which is representative of US shale gas) due to strict flaring regulations followed in BC. The study also undercuts the outcome of Howarth et al. (Clim Chang Lett 106:679-690, ), which states that the GHG footprint of shale gas is at least 20 % greater than coal. [ABSTRACT FROM AUTHOR]

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]

In infrastructure management, multi-criteria decision-making (MCDM) has emerged as a decision support tool to integrate various technical information and stakeholder values. Different MCDM techniques and tools have been developed. This paper presents a comprehensive review on the application of MCDM literature in the field of infrastructure management. Approximately 300 published papers were identified that report MCDM applications in the field of infrastructure management during 1980–2012. The reviewed papers are classified into application to the type of infrastructure (e.g. bridges and pipes), and prevalent decision or intervention (e.g. repair and rehabilitate). In addition, the papers were also classified according to MCDM methods used in the analysis. The paper provides taxonomy of those articles and identifies trends and new developments in MCDM methods. The results suggest that there is a significant growth in MCDM applications in infrastructure management applications of MCDM over the last decade. It has also been noted that many decision support tools based on multiple MCDM methods have been successfully used for infrastructure management. [ABSTRACT FROM PUBLISHER]

Acid rock drainage (ARD) is a major pollution problem globally that has adversely impacted the environment. Identification and quantification of uncertainties are integral parts of ARD assessment and risk mitigation, however previous studies on predicting ARD drainage chemistry have not fully addressed issues of uncertainties. In this study, artificial neural networks (ANN) and support vector machine (SVM) are used for the prediction of ARD drainage chemistry and their predictive uncertainties are quantified using probability bounds analysis. Furthermore, the predictions of ANN and SVM are integrated using four aggregation methods to improve their individual predictions. The results of this study showed that ANN performed better than SVM in enveloping the observed concentrations. In addition, integrating the prediction of ANN and SVM using the aggregation methods improved the predictions of individual techniques. [ABSTRACT FROM AUTHOR]

Reliability assessment of water supply systems (WSSs) is an important aspect of WSS planning and operations. Traditionally, WSS reliability involves the comparison of hydraulics (e.g., pressure or available water volume) and water quality (e.g., residual chlorine) parameters with their desired minimum level of service under various emergency loading conditions. To compute hydraulic dependent parameters (e.g., pressures, flow), different algorithms solve continuity and energy equations expressed in terms of certain independent parameters (e.g., roughness parameters and nodal demands) with certainty. Similarly, transport equations expressed in terms of different quality parameters are solved deterministically to compute water quality dependent parameters (e.g., residual chlorine). However, it is extremely challenging, even impossible, to estimate network-independent parameters with certainty. Therefore, estimated dependent parameters based on semiquantitative information bear uncertainty, which leads to a question of how reliable current reliability assessment results are. To address this issue, this paper proposes a new means of reliability assessment in which the reliability of a WSS is expressed in terms of utility and associated beliefs. The methodology developed provides an estimate of the uncertainties inherent in traditional reliability assessment results. It is expected that the proposed methodology will help municipalities to make informed decisions in order to increase the safety and security of public health. [ABSTRACT FROM AUTHOR]

Water supply systems (WSSs) are one of the most important and expensive core public infrastructures. The primary objective of a water supply utility is to have this valuable asset operate at its maximum possible efficiency with minimum cost throughout its design period. To achieve this objective, the first step is to evaluate the existing efficiency of all the components of the WSS using suitable performance indicators (PIs). Various agencies and organizations worldwide have developed detailed performance evaluation frameworks including several indicators to comprehensively cover all the aspects (e.g., physical asset, staffing, operational, customer satisfaction, economical) of the WSSs. Most of these frameworks and indicators have been developed for large-sized WSSs. Small- and medium-sized water supply systems (SM-WSSs) have specific performance-related issues, ranging from difficulties in collecting the data required to use the available systems of PIs to lack of skilled personnel and financial resources for efficient operations. A comprehensive review of the literature has been carried out to assess the suitability of reported performance evaluation systems for SM-WSSs in terms of their simplicity (easy and simple data requirements) and comprehensiveness (i.e., all the components of a WSS). This review also evaluates the individual PI with respect to its understandability, measurability, and comparability (i.e., within and across utility comparisons). On the basis of this detailed review, a conceptual performance evaluation system for SM-WSSs, consisting of a list of PIs grouped into their respective categories, has been proposed. The proposed system provides a stepwise approach, starting the performance evaluation process with the most significant and easy to measure PIs for small-sized WSSs and moving to a relatively complex set of indicators for SM-WSS depending on the availability of resources and specific operating conditions. [ABSTRACT FROM AUTHOR]

Abstract: Emergy synthesis is capable of quantifying environmental resources and services, as well as economic and human services, that are used up directly or indirectly to make a product available. However, a controversial aspect of emergy synthesis is the lack of research characterizing and documenting uncertainties in the emergy evaluation process. Uncertainty can arise from analysis of numerous components and flows in a complex environmental system. The reliability of emergy synthesis results may be undermined by both the inherent uncertainty of emergy parameters and models, and by a lack of knowledge regarding the certainty of resulting outputs. This paper explores the utility of fuzzy-based methods in emergy synthesis. Applying fuzzy set theory facilitates the gradual assessment of Unit Emergy Values (UEVs) as a set of possible UEVs. In other words, uncertainty of UEVs is described with the aid of a membership function valued in the real unit interval [0, 1]. The proposed fuzzy-based emergy synthesis has been applied for Life Cycle Assessment (LCA) of a transportation infrastructure system. A paved road, with different pavement options (i.e. asphalt and concrete), has been selected as a case study to highlight the impacts of propagation of different sources of uncertainties in the emergy evaluation process and decision making. Results indicate that fuzzy-based modeling can provide better insight for both emergy and LCA practitioners. The developed methodology provides transparency that should be an integral part of an emergy-based decision making process. [Copyright &y& Elsevier]

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]

The selection of remedial alternatives for mine sites is a complex task because it involves multiple criteria and often with conflicting objectives. However, an existing framework used to select remedial alternatives lacks multicriteria decision analysis (MCDA) aids and does not consider uncertainty in the selection of alternatives. The objective of this paper is to improve the existing framework by introducing deterministic and probabilistic MCDA methods. The Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) methods have been implemented in this study. The MCDA analysis involves processing inputs to the PROMETHEE methods that are identifying the alternatives, defining the criteria, defining the criteria weights using analytical hierarchical process (AHP), defining the probability distribution of criteria weights, and conducting Monte Carlo Simulation (MCS); running the PROMETHEE methods using these inputs; and conducting a sensitivity analysis. A case study was presented to demonstrate the improved framework at a mine site. The results showed that the improved framework provides a reliable way of selecting remedial alternatives as well as quantifying the impact of different criteria on selecting alternatives. [Copyright &y& Elsevier]

Abstract: Protecting drinking source water quality is a critical step in ensuring a safe supply of drinking water. Increasingly, drinking source water protection programs rely on the active participation of various stakeholders with differing degrees of water science knowledge. A drinking source water quality index presents a potential communication and analysis tool to facilitate cooperation between diverse interest groups as well as represent composite water quality. We tested the effectiveness of the Canadian Council of Ministers of the Environment Water Quality Index (CCME WQI) in capturing expert assessments of drinking water quality. In cooperation with a panel of drinking water quality experts we identified a core set of parameters to reflect common source water concerns. Drinking source water target values were drafted for use in the index corresponding to two basic treatment levels. Index scores calculated using the core parameter set and associated source water target values were strongly correlated with expert assessments of water quality. We recommend a modified index calculation procedure to accommodate parameters measured at different frequencies within any particular study period. The resulting drinking source water CCME WQI provides a valuable means of monitoring, communicating, and understanding surface source water quality. [Copyright &y& Elsevier]

Loss of water due to leakage is a common phenomenon observed in all water distribution systems. However, the water loss can be reduced to an acceptable limit by improved understanding of leakage mechanisms and pathways, and the influencing factors that lead to leakage. This study proposes a methodology to estimate leakage potential (LP) in a water distribution system (WDS). The study has identified various factors which are directly and/or indirectly associated with LP in a WDS. The research has defined a selected set of influencing factors as fuzzy variables and has developed a fuzzy rule-based (FRB) model using Mamdani inferencing algorithm. The impact of influencing factors varies under different operating pressure, therefore a generalized methodology has been proposed. The proposed methodology has been implemented for a real WDS in Bangkok (Thailand). To evaluate the impacts of uncertainties of influencing factors on LP, Monte Carlo simulation-based sensitivity analysis has been carried out. It has been concluded that the operating system pressure and age of the network are the two most important factors that contribute to LP of a WDS. The proposed model will help water utility managers to prioritize their network rehabilitation strategies and to establishing an efficient active leakage control program. [ABSTRACT FROM AUTHOR]

Studying uncertainties in hydrological modeling is necessary because of data scarcity or abundance and quality issues. These uncertainties can have significant effects on environmental decision making. Traditionally, probabilistic methods have been used to study uncertainties; however, recently, more comprehensive methods are used in the treatment of uncertainty. These methods are capable of addressing uncertainty in the form of vagueness, ambiguity, and conflict, which cannot be studied efficiently using probabilistic frameworks. The Dempster-Shafer theory of evidence (DST) is one of the popular methods that can provide a unified platform to address data conflict and incompleteness. In this paper, the use of DST to model and propagate the uncertainty arising from two snow water equivalent data sets with a high degree of conflict (DST conflict k=0.74) is demonstrated. In DST, on the basis of the nature of data, e.g., the degree of conflict, different combination rules are applicable. Here, four DST combination rules are applied including Dempster-Shafer, Yager, mixture, and the proportional conflict redistribution rule number 6 (PCR6). The outcomes from these rules are compared, and their effects on subsequent decision-making are discussed. Considering the specific condition of the data used, i.e., high-conflict data with limited quality information, results indicate that mixture and PCR6 rules are more appropriate. The resultant uncertainty-driven data set is subsequently used as input into an illustrative hydrologic model demonstrating a method for propagating uncertainty. In addition, the issues of resolving conflict for less contradicting data sets, the dependency between bodies of evidence, and modeling incompleteness are also discussed. [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]

Abstract: Performing risk analysis can be a challenging task for complex systems due to lack of data and insufficient understanding of the failure mechanisms. A semi quantitative approach that can utilize imprecise information, uncertain data and domain experts’ knowledge can be an effective way to perform risk analysis for complex systems. Though the definition of risk varies considerably across disciplines, it is a well accepted notion to use a composition of likelihood of system failure and the associated consequences (severity of loss). A complex system consists of various components, where these two elements of risk for each component can be linguistically described by the domain experts. The proposed linguistic approach is based on fuzzy set theory and Dempster–Shafer theory of evidence, where the later has been used to combine the risk of components to determine the system risk. The proposed risk analysis approach is demonstrated through a numerical example. [Copyright &y& Elsevier]

Abstract: The potential for generation of disinfection byproducts (DBPs) in swimming pools is high due to the concentrations of chlorine required to maintain adequate disinfection, and the presence of organics introduced by the swimmers. Health Canada set guidelines for trihalomethanes (THMs) in drinking water; however, no such guideline exists for swimming pool waters. Exposure occurs through ingestion, inhalation and dermal contact in swimming pools. In this research, a multimedia model is developed to evaluate exposure concentrations of THMs in the air and water of an indoor swimming pool. THM water concentration data were obtained from 15 indoor swimming pool facilities in Quebec (Canada). A level III fugacity model is used to estimate inhalation, dermal contact and ingestion exposure doses. The results of the proposed model will be useful to perform a human health risk assessment and develop risk management strategies including developing health-based guidelines for disinfection practices and the design of ventilation system for indoor swimming pools. [Copyright &y& Elsevier]

Abstract: In recent years, numerous attempts have been made to reduce the global environmental and associated socio-economic impacts of construction activities to achieve sustainable development goals. A sustainable system or activity refers to an eco-friendly, cost effective and socio-politically viable solution. This paper utilizes triple-bottom-line (TBL) sustainability criteria for the selection of a sustainable flooring system in Tehran (Iran). Three types of block joisted flooring systems – concrete, clay, and expanded polystyrene (EPS) blocks – have been investigated using life cycle analysis (LCA). Proposed approach provides a comprehensive evaluation system based on TBL criteria that are further divided into thirteen sub-criteria. It includes: (1) Environmental concerns (resource depletion, waste and emissions, waste management, climate change, environmental risk, embodied energy and energy loss); (2) Economic concerns (material cost, construction cost, and occupation and maintenance cost); and (3) Socio-political issues (social acceptance, vulnerability of area, and building weight). Analytical hierarchy process (AHP) is used as a multi-criteria decision making technique that helps to aggregate the impacts of proposed (sub)criteria into a sustainability index (SI) through a five-level hierarchical structure. Integration of AHP and LCA provides a framework for robust decision making that is consistent with sustainable construction practices. A detailed analysis shows that the EPS block is the most sustainable solution for block joisted flooring system in Tehran. [ABSTRACT FROM AUTHOR]

Drought is a stochastic natural hazard that is instigated by intense and persistent shortage of precipitation. Following an initial meteorological phenomenon, subsequent impacts are realized on agriculture and hydrology. Among the natural hazards, droughts possess certain unique features; in addition to delayed effects, droughts vary by multiple dynamic dimensions including severity and duration, which in addition to causing a pervasive and subjective network of impacts makes them difficult to characterize. In order manage drought, drought characterization is essential enabling both retrospective analyses (e.g., severity versus impacts analysis) and prospective planning (e.g., risk assessment). The adaptation of a simplified method by drought indices has facilitated drought characterization for various users and entities. More than 100 drought indices have so far been proposed, some of which are operationally used to characterize drought using gridded maps at regional and national levels. These indices correspond to different types of drought, including meteorological, agricultural, and hydrological drought. By quantifying severity levels and declaring drought's start and end, drought indices currently aid in a variety of operations including drought early warning and monitoring and contingency planning. Given their variety and ongoing development, it is crucial to provide a comprehensive overview of available drought indices that highlights their difference and examines the trend in their development. This paper reviews 74 operational and proposed drought indices and describes research directions. [ABSTRACT FROM AUTHOR]

Source water protection (SWP) is the most important step in the implementation of a multi-barrier approach that ensures cost-effective delivery of safe drinking water. However, implementing SWP strategies can be a challenging task owing to technical and administrative issues. Decision support tools for effective implementation of SWP strategies can be very helpful that may lead to saving time and resources. This paper critically reviews different SWP strategies available for surface waters and also discusses various formulations for water quality assessment at the source. Source water quality regulations in Canada and other jurisdictions around the world are also discussed. Stormwater management ponds, vegetated filter strips, pollution control by effective agricultural practice (e.g., cover crop and crop rotation) and fencing are found to be frequently mentioned in those regulations. These strategies are discussed in details in terms of their key features to achieve the highest possible removal efficiencies for selected water quality parameters. Finally, a conceptual model is proposed to evaluate water quality changes at the source based on selected source water protection strategies. The model uses SWP strategies as a means to reduce possible pollutants in the source water. It also utilizes simple mass balance equations (dilution) to estimate the concentrations in the receiving water bodies and does not consider physico-chemical and other reactions. A surrogate measure, water quality index (WQI), based on selected water quality parameters, is used for the assessment of source water quality. [ABSTRACT FROM AUTHOR]

Abstract: The main objective of this study is to develop a methodology that integrates indicators for performance assessment of small drinking water utilities. The investigation entails 10 water utilities in the Province of Québec (Canada) that use surface water or groundwater under the direct influence of runoff, and apply chlorination as the only treatment before distribution. All 10 water utilities were sampled five times during different months and a total of 50 data sets were collected, which were divided into two groups – training and validation data sets. The assessment of each water utility was done on an arbitrary normalized scale of being ‘problematic’ over a scale of [0,1], where zero mean fully non-problematic and vice versa. The performance indicators consist of source water, treatment, infrastructure, operational, and maintenance characteristics of utilities that are aggregated using ordered weighted averaging (OWA) operators. The major thrust behind selecting the OWA operator for aggregation of multi-criteria is its capability to encompass a range of operators bounded between minimum and maximum. The small utility performance indicators developed suggest that it is feasible to combine information operational, infrastructure, and maintenance characteristics to establish utility performance. The findings of this study is useful to government bodies in terms of achieving a better understanding and assessment of small utilities’ specific infrastructure needs and subsequent allocation of appropriate resources. [Copyright &y& Elsevier]

The deterioration of water quality can adversely affect consumers' health as well as the aesthetic properties of water (taste, odour, colour). To date, little consideration has been given to the impact of deteriorating (ageing) water mains on water quality as a major decision driver for the renewal/rehabilitation of water mains. The main objective of this research was to identify major deterioration mechanisms in distribution networks that may contribute to water quality failures (WQF) and develop a model to quantify overall potential for WQF as a function of this deterioration. Numerous factors affect water quality in the distribution network and interactions among them are complex and often not well understood. Water quality failures in distribution networks are relatively scarce, which makes it difficult to establish statistically significant generalizations. In such data-sparse circumstances, expert knowledge and judgement can serve as a supplement or even as alternative source(s) of information. This paper discusses major deterioration mechanisms that may contribute to WQFs in distribution networks, and proposes a modelling framework using fuzzy-based methods. The following two papers in this series will provide a mathematical formulation of the proposed model and its application using two case studies, respectively. [ABSTRACT FROM AUTHOR]

Soil corrosivity is considered to be a major factor for the deterioration of metallic water mains. Using a 10-point scoring method as suggested by the American Water Works Association, soil corrosivity potential can be estimated by five soil properties: (1) resistivity; (2) pH value; (3) redox potential; (4) sulfide; and (5) percentage of clay fines. However, the relationship between soil corrosivity and pipe deterioration is often ambiguous and not well-defined. In order to identify the direct relationship between soil properties and pipe deterioration, which is defined as the ratio of the maximum pit depth to pipe age, predictive data mining approaches are investigated in this study. Both single- and multipredictor based approaches are employed to model such relationship. The advantage of combining multiple predictors is also demonstrated. Among all approaches, rotation forest achieves the best result in terms of the prediction error to estimate pipe deterioration rate. Compared to the random forest method, which is next to the best, the normalized mean square error decreased 50%. With the proposed approaches, the assessment of pipe condition can be achieved by analyzing soil properties. This study also highlights the importance for collecting more reliable soil properties data. [ABSTRACT FROM AUTHOR]

The purpose of indices is to summarize a large volume of information into a single number that is easy to understand and interpret. Environmental indices provide a composite picture of an environmental condition derived from a series of observed measurements and parameters. They are used as communication tools by regulatory agencies to characterize the state of a specific environmental system (air, water, and sediments) and to study the impact of regulatory policies on various environmental management practices. In the development of environmental indices, a few issues and problems have been encountered arising as a result of the abstraction of information and data. These problems are referred to as characteristic properties that include ambiguity, eclipsing, compensation and rigidity. These characteristic properties have long been identified and interpreted in Boolean (e.g., Yes/No) or qualitative (e.g., low, medium, high) terms. In this paper, we propose a new approach to describe the above stated characteristic properties on a continuous scale to evaluate and compare the behavior of various aggregation models. Our approach is based on developing penalty functions for each characteristic property. A water quality index example by is used to explain our approach. A detailed case study for a developing microbial risk index is also provided to show how the proposed approach can be extended to complex hierarchical systems. Results show that it is possible to improve aggregation models for index development. Future research directions to improve index development are also discussed. [Copyright &y& Elsevier]

Analytic hierarchy process (AHP) is a utility theory based decision-making technique, which works on a premise that the decision-making of complex problems can be handled by structuring them into simple and comprehensible hierarchical structures. However, AHP involves human subjective evaluation, which introduces vagueness that necessitates the use of decision-making under uncertainty. The vagueness is commonly handled through fuzzy sets theory, by assigning degree of membership. But, the environmental decision-making problem becomes more involved if there is an uncertainty in assigning the membership function (or degree of belief) to fuzzy pairwise comparisons, which is referred to as ambiguity ( non-specificity). In this paper, the concept of intuitionistic fuzzy set is applied to AHP, called IF-AHP to handle both vagueness and ambiguity related uncertainties in the environmental decision-making process. The proposed IF-AHP methodology is demonstrated with an illustrative example to select best drilling fluid (mud) for drilling operations under multiple environmental criteria. [ABSTRACT FROM AUTHOR]

Environmental indices (EI) constitute a common communication tool that is often used to describe the overall status of environmental systems (air, water and soil). EI development entails the use of mathematical operators to aggregate various non-commensurate input parameters in a logical manner. The ordered weighted averaging (OWA) operator is a general mean type operator that provides flexibility in the aggregation process such that the aggregated value is bounded between minimum and maximum values of the input parameters. This flexibility of the OWA operator is realized through the concept of orness, which is a surrogate for decision maker’s attitude. The type of input parameters also affects the choice of aggregation operators. If the input parameters are linguistic or fuzzy, the aggregation through OWA operators is not possible, and the use of fuzzy arithmetic is warranted. The concept of fuzzy number OWA (FN-OWA) operators is explored to handle situations in which one or more input parameter has fuzzy (or linguistic) values. The proposed approach is demonstrated using data provided in an earlier study by Swamee and Tyagi (ASCE J Environ Eng 126(5):451–455, ) for establishing water quality indices. Multiple hypothetical scenarios are also generated to highlight the utility and sensitivity of the proposed approach. [ABSTRACT FROM AUTHOR]

Effective inspection and monitoring practices for the condition assessment of pipes ensure better decision(s) for repair or replacement before they fail. Pipe deterioration is a physical manifestation of the aging process in which many factors can contribute to structural failure. Various technologies/ techniques have been developed during the last few years to inspect/monitor piping systems, but how to intelligently interpret the collected data remains a challenge. In this paper, a new approach based on hierarchical evidential reasoning is proposed. This approach uses Dempster–Shafer (D-S) theory to make inferences for condition assessment of buried pipes. A hierarchical evidential reasoning model can help combine different distress indicators (bodies of evidence) at different hierarchical levels using D-S rule of combination. The proposed hierarchical evidential reasoning method is demonstrated with an example of condition assessment for a large diameter pipe. Information from multiple sources is fused to obtain a more reliable assessment of pipe deterioration. [ABSTRACT FROM AUTHOR]

The concepts of system load and capacity are pivotal in risk analysis. The complexity in risk analysis increases when the input parameters are either stochastic (aleatory uncertainty) and/or missing (epistemic uncertainty). The aleatory and epistemic uncertainties related to input parameters are handled through simulation-based parametric and non-parametric probabilistic techniques. The complexities increase further when the empirical relationships are not strong enough to derive physical-based models. In this paper, ordered weighted averaging (OWA) operators are proposed to estimate the system load. The risk of failure is estimated by assuming normally distributed reliability index. The proposed methodology for risk analysis is illustrated using an example of nine-input parameters. Sensitivity analyses identified that the risk of failure is dominated by the attitude of a decision-maker to generate OWA weights, missing input parameters and system capacity. [ABSTRACT FROM AUTHOR]

Chlorine used for the disinfection of water supplies can react with naturally occurring organic compounds and form potentially harmful disinfection by-products (DBPs). A risk index for two regulated groups of chlorinated DBPs—trihalomethanes (THMs) and haloacetic acids (HAAs), using fuzzy C-means (FCM) clustering algorithm and fuzzy rule-based modeling is proposed for risk communication. The proposed index evaluates the cancer and non-cancer risks individually for THMs and HAAs using the FCM algorithm. Subsequently, two different fuzzy rule-bases were used to evaluate the overall risk-index based on cancer and non-cancer risks. The overall risk-index will provide drinking water utilities with an effective communication tool for communicating aggregated water quality compliance. Simulated DBP occurrence data obtained from the City of Quebec, Canada, is used to demonstrate the application of this methodology. [ABSTRACT FROM AUTHOR]

Environmental risk management is an integral part of risk analyses. The selection of different mitigating or preventive alternatives often involve competing and conflicting criteria, which requires sophisticated multi-criteria decision-making (MCDM) methods. Analytic hierarchy process (AHP) is one of the most commonly used MCDM methods, which integrates subjective and personal preferences in performing analyses. AHP works on a premise that decision-making of complex problems can be handled by structuring the complex problem into a simple and comprehensible hierarchical structure. However, AHP involves human subjectivity, which introduces vagueness type uncertainty and necessitates the use of decision-making under uncertainty. In this paper, vagueness type uncertainty is considered using fuzzy-based techniques. The traditional AHP is modified to fuzzy AHP using fuzzy arithmetic operations. The concept of risk attitude and associated confidence of a decision maker on the estimates of pairwise comparisons are also discussed. The methodology of the proposed technique is built on a hypothetical example and its efficacy is demonstrated through an application dealing with the selection of drilling fluid/mud for offshore oil and gas operations. [ABSTRACT FROM AUTHOR]

Total coliforms are used as indicators for evaluating microbial water quality in distribution networks. However, total coliform provides only a weak "evidence" of possible fecal contamination because pathogens are subset of total coliform and therefore their presence in drinking water is not necessarily associated with fecal contamination. Heterotrophic plate counts are also commonly used to evaluate microbial water quality in the distribution networks, but they cover even a wider range of organisms. As a result, both of these indicators can provide incomplete and highly uncertain bodies of evidence when used individually. In this paper, it is shown that combing these two sources of information by an appropriate data fusion technique can provide improved insight into microbial water quality within distribution networks. Approximate reasoning methods like fuzzy logic and probabilistic reasoning are commonly used for data fusion where knowledge is uncertain (i.e., ambiguous, incomplete, and/or vague). Traditional probabilistic frameworks like Bayesian analysis, reasons through conditioning based on prior probabilities (which are hardly ever available). The Dempster–Shafer (DS) theory generalizes the Bayesian analysis without requiring prior probabilities. The DS theory can efficiently deal with the difficulties related to the interpretation of overall water quality where the redundancy of information is routinely observed and the credibility of available data continuously changes. In this paper, the DS rule of combination and its modifications including Yager's modified rule, Dubois–Prade disjunctive rule and Dezert–Smarandache rule are described using an example of microbial water quality in a distribution network. [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]

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]

Several factors may contribute to the structural failure of cast and ductile iron water mains, the most important of which is considered to be corrosion. The ANSI/AWWA C105/A21.5-99 10-point scoring (10-P) method is commonly used to predict the corrosivity potential of a given soil sample using certain soil properties. The 10-P and other scoring methods use binary logic to classify the soil as either or . Fuzzy logic extends binary logic in this context as it recognizes the real world phenomena using a certain degree of membership between 0 and 1. This article presents a fuzzy logic expert system capable of predicting the deterioration of cast and ductile iron water mains based on surrounding soil properties. The proposed model consists of two modules: a knowledge base and an inference mechanism. The knowledge base provides information for better decision making and is developed in a two-tier fuzzy modeling process. First in the expert knowledge generates a subjective model to describe the characteristics of the system using fuzzy linguistic variables. Later in the field data are used to develop an objective model, which is eventually used in conjunction with the subjective model to provide a more reliable knowledge base for the expert system. The inference mechanism uses fuzzy approximate reasoning methods to process the encoded information of the knowledge base. [ABSTRACT FROM AUTHOR]