Journal of Water Resources Planning and Management

During the last $10\text{years}$ , the writers conducted four projects with Dr. G. V. Loganathan on water distribution system research and applications, and developed and used several tools, which, combined, formed a comprehensive methodology for water distribution system asset management. This paper highlights Dr. Loganathan’s contributions in water distribution system asset management. One of the projects was to develop a prioritized water main replacement program for a water utility experiencing a large number of cast iron water main breaks. For this project Dr. Loganathan formulated a computer program to analyze a large amount of water main break data, on a pipe-by-pipe basis, to formulate an economic model to identify an economically optimum time to replace a pipe, and to develop an optimum water main replacement program. In the second project Dr. Loganathan developed a methodology and a modeling system to predict structural failure and to prioritize candidate mains for renewal. Once an asset management program for renewal of pipes was developed, Dr. Loganathan formulated a decision support system software to evaluate and identify on a site-specific basis, the most suitable water main renewal technologies available to water utilities for renewal of a specific water main. For the most recent project with Dr. Loganathan, he developed software for optimization of valve placement and management in a water distribution network in minimizing customer outages due to valve and pipe failures. This comprehensive system of tools that Dr. Loganathan helped to develop will help water utilities develop a water distribution system asset management plan that will minimize adverse impacts due to valve and pipe failures.

Consumers face numerous problems when they experience leaks and premature failures in their potable drinking water plumbing system. A review of an existing database of copper pipe failures demonstrated that premature pipe failures and pinhole leaks have been documented across the United States. Additionally, there are “hotspots” in the United States where pinhole failures have been documented to occur at a fairly high incidence. A number of known and suspected factors can cause copper pitting corrosion that eventually develops into a pinhole leak, such as specific water qualities, microbial activity, hydraulics, and other installation factors. However, the current understanding does not adequately define the complex synergy between causal factors, which poses a challenge in assessing plumbing susceptibility and shaping an effective management plan. This work presents a preliminary ranking of the causal factors for assessing plumbing susceptibility. However, due to incomplete understanding of the pinhole phenomenon, advice from local experts and past service history should still be given priority in assessing the likelihood of problems.

In the United States, about 90% of drinking water home plumbing systems use copper pipes. Pinhole leaks in copper plumbing pipes have become a concern for the homeowners because such leaks have resulted in property damage, lowered property values, and the possibility of losing their insurance coverage. Homeowners would benefit from tools enabling them to decide on whether to continue to repair or replace their plumbing system, the factors to be considered in a replacement decision, and the type of material to use for replacement. Multiple attributes including price, corrosion resistance, fire retardance, health effects, longevity, resale value of home, and taste and odor are considered in choice of plumbing materials. We formalized “choosing alternative plumbing materials” within the framework of the analytic hierarchy process. Empirical surveys were administered to 135 students of Civil and Environmental Engineering at Virginia Tech. Survey results show that health effects, taste and odor, longevity, and corrosion resistance are the influential factors when choosing alternative plumbing materials. Health effects and taste and odor of drinking water are surrogates for the purity of water that dominates preferences for a plumbing material. Research results will assist homeowners in making better informed decision regarding their plumbing systems.

Water distribution systems are one of the most important infrastructures in urban areas. The objective of every urban water distribution system is to deliver enough water of acceptable quality with adequate pressure to different demand points. There are many interruptions and occasional disasters that impact the performance of the water distribution system, some of which could be quite devastating. The most common disasters are main breaks that may cause considerable water losses and bring up the system to partial or complete shutdown. Evaluation of the state of the system’s readiness helps managers make better decisions to prevent disasters and respond better to emergencies. In this paper, the state of the system’s readiness in dealing with disasters has been quantified using a hybrid index called the system readiness index. This index is developed based on the combined effects of three system performance indexes, namely reliability, resiliency, and vulnerability. They are combined through hydraulic characteristics of the network at some critical nodes of the water distribution system, using a neural network model. Different failure scenarios are defined to evaluate the system performance and to analyze the systems interruption. A Bayesian approach for updating the probability of failure is used to incorporate the new information on the state of the system. The proposed algorithm is applied to a part of the water distribution system of the Tehran metropolitan area in Iran. The results show the significant value of the proposed algorithm in helping the decision maker to improve the system’s performance and develop contingency plans when faced with disasters.

We consider the problem of designing a contaminant warning system for a municipal water distribution network that uses imperfect sensors, which can generate false-positive and false-negative detections. Although sensor placement optimization methods have been developed for contaminant warning systems, most sensor placement formulations assume perfect sensors, which does not accurately reflect the behavior of real sensor technology. We describe a general exact nonlinear formulation for imperfect sensors and a linear approximation. We consider six general solution strategies, some of which have multiple solution methods. We applied these methods to three test networks, including one with over 10,000 nodes. Our experiments indicate that it is worth deploying a sensor network even when sensors have low detection probability. They also indicate it is worth paying attention to sensor imperfections when placing sensors even when there is a response delay of up to 8 h. The best choice of solution strategy depends upon the user’s goals and the problem size. However, for large-scale problems with a moderate number of sensors, using a local search for the linear approximation formulation provides a reasonable-quality solution in a few minutes of computation. Our models assume that sensors can fail via false negatives. Additionally, we discuss ways to model false positives, ways to limit them, and how to trade them off against false negatives. All of our solution methods can handle false positives but our experiments do not explicitly consider them.

Engineers and planners responsible for the selection and design of storm-water best management practices (BMPs) face a formidable array of practices and techniques for managing the quality of urban runoff. Primary factors affecting the choice of BMP invariably include the performance capability of a given class of BMPs and the new impervious cover fraction arising from development projects. We introduce the analytical hierarchal process (AHP) as an analytical framework for BMP selection, through priority ranking of storm water control objectives and BMP performance metrics. Using the AHP, a BMP priority ranking is accomplished through the construction of pairwise relative rankings of the selection criteria and then of the BMPs themselves against the respective selection criteria. The use of normalized ranking vectors, obtained through eigenvector approximation, is employed to provide a final ranking of BMP choices that then can be carefully reviewed by the design engineer. Two BMP selection applications are included in the context of a residential/commercial development and a linear highway project.

This paper describes the development of an optimal water quality tool for managing wet weather discharges that uses a macrolevel simulation model (i.e., the Streeter-Phelps equation) linked with a highly efficient optimization algorithm (i.e., a modified version of the Box complex method). The proposed approach can be applied to an urban watershed impaired by multiple sources of wet weather discharges. As an application, the proposed approach is used to develop optimal water quality management strategies for the Beargrass Creek watershed in Louisville, Ky.

The needs for conservation, efficient management, and accounting of water uses intensify as demands increase relative to supplies. Storage accounting, properly performed, can provide a framework to meet these needs and to efficiently and equitably allocate the benefits, costs, and risks of water resource systems. Rule-based storage accounting is one approach that allows actual water uses and reservoir operations to be tracked against prior existing systemwide rules. This approach is especially well suited to sustainable and adaptive management policies that accommodate: (1) updated allocations of storage in multipurpose reservoirs to most beneficial uses; and (2) targeted credits and penalties for water use and reservoir operations to incentivize conservation, prevent cross-subsidization among included purposes, and check unsustainable demands on the system. The writers review and contrast rule-based with traditional storage accounting methods, and provide an example application of the former to a reservoir system operated to meet multiple consumptive and nonconsumptive uses in conjunction with complex instream flow regimes. Rule-based accounting does not facilitate initial or reallocations of water and storage but, by holding both reservoir operators and water users accountable for compliance with established allocations, discloses their efficiency, fairness and sustainability, and consequently serves to guide future adaptive management strategies.

Water-distribution systems least-cost pipe sizing/design is probably the most explored problem in water-distribution systems optimization. Attracted numerous studies over the last 4 decades, two main approaches were employed: decomposition in which an “inner” linear programming problem is solved for a fixed set of flows/heads, while the flows/heads are altered at an “outer” problem using a gradient or a subgradient type technique; and the employment of a general evolutionary optimization algorithm. In 1995 Loganathan and his colleagues proposed to couple these two approaches into one framework, thus overcoming the limitations of each. This study employs this framework with two modifications: (1) application of a genetic algorithm for the “outer” optimization search instead of simulated annealing; and (2) constraining the sought solution to the lowest cost spanning tree layout with the spanning tree chords kept at their minimum permissible pipe diameters. A comparison of the methodology to a genetic algorithm application without the refinement of using a spanning tree with minimal chord diameters was explored, showing the proposed methodology dominance. The suggested method is limited to one loading gravitational systems, and is demonstrated using a simple example application.