A Neurofuzzy Decision Framework for the Management of Water Distribution Networks

Among the most important components of sustainable management strategies for water distribution networks is the ability to integrate risk analysis and asset management decision-support systems (DSS), as well as the ability to incorporate in the analysis financial and socio-political parameters that are associated with the networks in study. Presented herein is a neurofuzzy decision-support system for the performance of multi-factored risk-of-failure analysis and pipe asset management, as applied to urban water distribution networks. The study is based on two datasets (one from New York City and the other from the city of Limassol, Cyprus), analytical and numerical methods, and artificial intelligence techniques (artificial neural networks and fuzzy logic) that capture the underlying knowledge and transform the patterns of the network’s behaviour into a knowledge-repository and a DSS.     

A Framework of Identifying Critical Water Distribution Pipelines from Recovery Resilience

Water Resources Management - Identifying critical facilities in a water distribution system (WDS) from the standpoint of recovery resilience is significant for emergency inspection and restoration...     

Water Distribution Networks Resilience Analysis: a Comparison between Graph Theory-Based Approaches and Global Resilience Analysis

Water Resources Management - The structure and connectivity of infrastructure systems such as water distribution networks (WDNs) affect their reliability, efficiency and resilience. Suitable...     

A Pipe Ranking Method for Water Distribution Network Resilience Assessment Based on Graph-Theory Metrics Aggregated Through Bayesian Belief Networks

Water Resources Management - The resilience assessment is crucial for many infrastructures, including water supply and distribution networks. In particular, the identification of the...     

Comparison Among Resilience and Entropy Index in the Optimal Rehabilitation of Water Distribution Networks Under Limited-Budgets

The replacement of existing pipes is a strategy for the rehabilitation of water distribution networks that is frequently adopted by water companies. Usually, the optimal choice of the pipes diameter is a difficult optimization task, because limited budgets are available. In order to support the selection of a rehabilitation strategy, surrogate reliability measures are often used as an indirect measure of the water distribution system hydraulic performance. Among others, the resilience and entropy indices have attracted considerable interest because they both represent a measure of the network robustness. In the present work, a comparison between these indices is provided in the framework of the optimal rehabilitation of an existing network under limited budget constraint. The resilience and entropy indices are applied to the case of a realistic water distribution network in an extended period simulation framework. Several values of the maximum budget allocable for rehabilitation are considered, and hydraulic calculations are undertaken by means of a pressure driven approach within a modified EPANET 2 environment. The effectiveness of the two surrogate reliability measures is demonstrated by an a-posteriori reliability assessment.     

A Prioritization Model for Rehabilitation of Water Distribution Networks Using GIS

Decision-making for the rehabilitation of water distribution networks in the traditional procedure is based on some simple indices such as the number of incidents while several mechanical, hydraulic and qualitative factors are involved in this process. Evidently, making decision on the rehabilitation of water networks seems to be very difficult as the number of factors increases and they interact with each other. The main objective of this research is to prepare, implement and evaluate a conceptual model to prioritize the rehabilitation of pipes based on different scenarios with respect to the combination effects of basic factors in physical, hydraulic and experimental categories. In order to organize the wide range of data to be used in decision-making models, including the plans aimed for pipe replacement, it is necessary to use geographical information systems (GIS). By determining and introducing the factors involved in the rehabilitation of water networks, this research aims to provide an integrated model consisting of conceptual, GIS, hydraulic analysis and the breakage models to prioritize the rehabilitation schemes. By using the data provided from a real network, the advantages of the proposed methodology are evaluated. Based on the obtained results, age factor, among all the other physical parameters, and pressure, among the hydraulic factors, have the greatest influence in outlining the final rehabilitation scenario. The importance of the pipe length has decreased considerably as well. Furthermore, it can be concluded that rehabilitation management of pipe networks can be optimized by using this methodology.     

An Optimization Strategy for Water Distribution Networks

An optimization strategy based on head losses minimization is developed for the least cost design of water distribution networks. A new weighting approach is suggested for calculating the initial flow distribution and optimum pipe diameters of the weighted flow distribution is presented by using least square method. In the mean time homogenous and isotropous head losses are maintained with implications of head loss path choice. The model is employed for designing and/or modifying pipe sizes while the classical Hardy-Cross network solver is used to balance the flows. The whole algorithm is programmed and applied to a two-looped network selected from the literature and the results are presented on a comparative basis. A FORTRAN software with the necessary steps in the flow chart is written for the optimization calculations in this paper.     

GA-ILP Method for Optimization of Water Distribution Networks

Optimization of water distribution networks has been of central importance for recent decades. Genetic Algorithms (GA) are the most famous metaheuristics widely used for this purpose with great success. However, the fact that GA basically requires a large number of computations, has led to investigate for faster solvers. In this research, a new approach is proposed in which a simple GA is linked with the Integer-Linear Programming (ILP) method resulting in a hybrid optimization scheme. Using the mathematical method of ILP, the search space is significantly reduced thereby a limited number of evaluations are required to achieve a good solution. The approach is applied to two benchmark pipe-networks in order to show its ability in terms of accuracy and speed. The results are then compared with the previous works. The obtained results indicate that the proposed model is computationally efficient, like classic methods, while is still very promising in finding the global optimum like the nature-inspired metaheuristics.     

Resilience Indexes for Water Distribution Network Design: A Performance Analysis Under Demand Uncertainty

Traditionally, the optimal design of water distrubution networks has been dealt with using single-objective constrained approaches, where the aim is to minimize the network investment cost while maintaining minimum pressure head constraints at all nodes. However, in the last decade some authors have proposed multi-objective approaches which optimize other objectives than network investment cost. In most cases, these objectives have been formulated using the concept of resilience index, which mimics the design aim of providing excess head above the minimum allowable head at the nodes and of designing reliable loops with practicable pipe diameters. Although several authors have proposed different resilience indexes for this pupose, to date there is no empirical study that analyzes the advantages and disadvantages of these proposals. This paper evaluates the performance of a well-known multi-objective evolutionary algorithm, the Strength Pareto Evolutionary Algorithm 2, using three different resilience indexes. The results obtained in two water supply networks under a large number of simulated over-demand scenarios show the advantages and disadvantages of these measures.     

A Branch-and-Bound Algorithm for Optimal Pump Scheduling in Water Distribution Networks

Nowadays water distribution operation systems are accomplished with the aid of qualified professionals who use their experience in order to achieve a satisfactory performance of the several hydromechanical devices, which are part of the system, such as boosters and valves. In general, these operational rules are empirical and the main goal is to assure the availability of water for the population, with no special concerns about saving energy used in pumping systems. Besides, these empirical rules often disregard hours of lower energy rates. There are several research works concerning the developments of operational rules optimization applied to specific water distribution systems. However, in this work, a general optimization routine integrated with EPANET is presented, which allows the determination of strategic optimal rules of operation for any type of water distribution system. Moreover, a Branch-and-Bound algorithm is also used, where finding the global optimal solution is guaranteed, in admissible computational times. The water distribution system used in this work corresponds to a hypothetical network proposed in the specialized literature.     

Water, People, and Sustainability—A Systems Framework for Analyzing and Assessing Water Governance Regimes

Freshwater resources might become the most limited resource in the future due to rising demands, climate change, and the degradation of aquatic ecosystems. While the urgency of this challenge is uncontested, water governance regimes still struggle to employ suitable responses. They lack of: taking a comprehensive perspective on water systems; focusing on social actors, their actions, needs, intentions, and norms as drivers of water systems; engaging in a discourse on tangible goals to provide direction for governance efforts; and promoting a comprehensive perspective on water sustainability that equally recognizes depletion, justice, and livelihood issues in the long-term. We present an approach that intends to overcome these limitations by putting the focus on what people do with water, and why, along with the impacts of these doings. First, we outline an integrated approach to water governance regimes, and then, we present a holistic set of principles by which to evaluate sustainable water governance. Solution-oriented research applying this approach integrates natural sciences and engineering perspectives on water systems with social science studies on water governance, while also specifying and applying normative principles for water sustainability. The approach we develop herein can be used to reform and innovate existing water governance regimes as well as stimulate transformative governance research.     

An Agent-based Modeling Framework for Assessing the Public Health Protection of Water Advisories

In the event that pathogens or toxins are introduced to a water distribution system, a utility manager may identify a threat through water quality data or alerts from public health officials. The utility manager may issue water advisories to warn consumers to reduce water use activities. As consumers react and change water demands, dynamic feedbacks among the community, utility managers, and the engineering infrastructure can create unexpected public health consequences and network hydraulics. A Complex Adaptive System (CAS)-based methodology is developed to couple an engineering model of a water distribution system with agent-based models (ABM) of consumers, public health officials, and utility managers to simulate feedback among management decisions, system hydraulics, and public behavior. A utility manager and a public health official are represented as agents, who respond to the event using a set of rules and equations that are based on a statistical analysis of a set of recorded water events. Consumers are represented as agents who update their water activities based on exposure to the contaminant and warnings from a utility agent and family members. A model of consumer compliance is developed using results from two surveys that report data to characterize consumer perceptions toward information sources during a water contamination event. The ABM framework is applied for an illustrative mid-sized virtual city to quantify the significance of interactions and advisories on public health consequences.     

Pressure Management Model for Urban Water Distribution Networks

A technique for leakage reduction is pressure management, which considers the direct relationship between leakage and pressure. To control the hydraulic pressure in a water distribution system, water levels in the storage tanks should be maintained as much as the variations in the water demand allows. The problem is bounded by minimum and maximum allowable pressure at the demand nodes. In this study, a Genetic Algorithm (GA) based optimization model is used to develop the optimal hourly water level variations in a storage tank in different seasons in order to minimize the leakage level. Resiliency and failure indices of the system have been considered as constraints in the optimization model to achieve the minimum required performance. In the proposed model, the results of a water distribution simulation model are used to train an Artificial Neural Network (ANN) model. Outputs of the ANN model as a hydraulic pressure function is then linked to a GA based optimization model to simulate hydraulic pressure and leakage at each node of the water distribution network based on the water level in the storage tank, water consumption and elevation of each node. The proposed model is applied for pressure management of a major pressure zone with an integrated storage facility in the northwest part of Tehran Metropolitan area. The results show that network leakage can be reduced more than 30% during a year when tank water level is optimized by the proposed model.     

Assessing Decentralised Water Solutions: Towards a Framework for Adaptive Learning

This paper reports on the use of qualitative analysis to inform a risk analysis framework for decentralised water systems. To realise the benefits from these technologies, a methodology is applied to learn from previous difficulties in implementing and managing them. A workshop process was used to capture stories from industry professionals on difficulties they have encountered in planning and implementation. Qualitative analysis of story narratives revealed stages where there was some type of development process failure; as well as failure modes and factors influencing the difficulties encountered. The analysis also generated insights: difficulties in one part of the development process tends to propagate to subsequent stages; system difficulties most often occurred in the policy stage of development due to institutional inertia and lack of adaptive governance; and the best indicator of problems with a decentralised system was complaints of poor water quality. Furthermore, this paper also provides a method to learn from past difficulties by identifying what data needs to be collected in order to populate a risk model which can be used for improving risk assessment of the development process for decentralised systems. This can provide a basis for better decision making, policy and guidelines; an important factor in mainstream acceptance.     

Parameter Estimation in Water Distribution Networks

Estimation of pipe roughness coefficients is an important task to be carried out before any water distribution network model is used for online applications such as monitoring and control. In this study, a combined state and parameter estimation model for water distribution networks is presented. Typically, estimation of roughness coefficient for each individual pipe is not possible due to non-availability of sufficient number of measurements. In order to address this problem, a formal procedure based on K-means clustering algorithm is proposed for grouping the pipes which are likely to have the same roughness characteristics. Also, graph-theoretic concepts are used to reduce the dimensionality of the problem and thereby achieve significant computational efficiency. The performance of the proposed model is demonstrated on a realistic urban water distribution network.     

Nodal Analysis of Urban Water Distribution Networks

There are three methods for analysing the flow and pressure distribution in looped water supply networks (the loop method, the node method, the pipe method), accounting for the chosen unknown hydraulic parameters. For all of these methods, the nonlinear system of equations can be solved using iterative procedures (Hardy–Cross, Newton–Raphson, linear theory). In the cases of the extension or the rehabilitation of distribution networks, the unknown parameters are the hydraulic heads at nodes, and the nodal method for network analysis is preferred. In this paper, a generalised classic model is developed for the nodal analysis of complex looped systems with non-standard network components and the solvability of new problems, along with the determination of the pressure state in the system. In addition, this paper exhibits a different approach to this problem by using the variational formulation method for the development of a new analysis model based on unconditioned optimisation techniques. This model has the advantage of using a specialised optimisation algorithm, which directly minimises an objective multivariable function without constraints, implemented in a computer program. The two proposed models are compared with the classic Hardy–Cross method, and the results indicated a good performance of these models. Finally, a study is performed regarding the implications of the long-term operation of the pipe network on energy consumption using these models. The new models can serve as guidelines to supplement existing procedures of network analysis.     

Optimization of Investments in the Resilience of Water Distribution Systems Subject to Interruptions

In this paper, we propose an optimization model to support decisions related to the design of water distribution systems (WDS) that are subjected to interruptions caused by disruptive events, emphasizing their resilience capabilities, namely: absorption, adaptation, and recovery. Considering the exposure of WDS operation to random interruptions, we aim at minimizing the total investment considering the possibility of implementing actions that improve these capabilities, which can be put in place prior or posterior to the occurrence of a disruptive event. An application example is discussed as a way to understand the nature of the problem and to support the formulation of the proposed model. The results demonstrate the need to invest in resilient capacities adequate to each interruption probability associated to the disruptive scenarios, characterizing these considerations as of great importance to support managerial decisions, thus constituting a guideline for the allocation of investments before and/or after the occurrence of the event.

     

Calibration of Design Models for Leakage Management of Water Distribution Networks

Water Resources Management - Water losses in urban water distribution networks (WDN) accelerate the deterioration of such infrastructures. The enhanced hydraulic modelling provides a...     

Energy Production in Water Distribution Networks: A PAT Design Strategy

Pump operating as turbine (PAT) is an effective source of reducing the equipment cost in small hydropower plants. However, the manufacturers provide poor information on the PAT performance thus representing a limit for its wider diffusion. Additional implementation difficulties arise under variable operating conditions, characteristic of water distribution networks (WDNs). WDNs allow to obtain widespread and globally significant amount of produced energy by exploiting the head drop due to the network pressure control strategy for leak reductions. Thus a design procedure is proposed that couples a parallel hydraulic circuit with an overall plant efficiency criteria for the market pump selection within a WDN. The proposed design method allows to identify the performance curves of the PAT that maximizes the produced energy for an assigned flow and pressure-head distribution pattern. Finally, computational fluid dynamics (CFD) is shown as a suitable alternative for performance curve assessment covering the limited number of experimental data.     

Utilizing Matrix Completion for Simulation and Optimization of Water Distribution Networks

Water Resources Management - Simulation of water distribution networks (WDNs) constitutes a key element for the planning and management of water supply systems. The literature presents different...