Journal of Water Resources Planning and Management

This paper explores the trade-offs between water quality and pumping costs objectives in optimization of operation of regional multiquality water distribution systems. The optimization model is designed to concurrently minimize each objective, where water quality is represented by the deviations of constituent concentrations from required values and pumping costs are represented by energy consumed by the pumps. The optimization problem is solved using an optimization software, incorporating the nondominated sorting genetic algorithm II (NSGA-II), linked with network analysis software. Two typical but purposefully different example networks are used. First, a network with multiple water sources of different qualities and second, a network with one water source only, which was converted to represent a regional nondrinking water distribution system. The trade-offs between water quality and pumping costs are explored using a total of 14 scenarios reflecting different water quality configurations of these networks. Those scenarios, into which time variability was introduced for both source water quality and customer water quality requirements, were systematically developed to represent real-life situations that could be found in practice. The results indicate that for the majority of the scenarios, there is a trade-off with a competing nature between water quality and pumping costs objectives. Additionally, it was discovered that multiobjective optimization problems with water quality (i.e., concentration deviations) and pumping costs objectives could be reduced in certain instances into a single-objective problem of minimizing pumping costs. In fact, a regional water distribution system in which water quality is represented by a single conservative constituent can produce either a trade-off or single-objective solution between those two objectives, and this outcome is dependent on both the water quality configuration of the system and system operational flexibility. Last, some particular conclusions are drawn for both a water distribution system with multiple water sources and a water distribution system with a single water source, which suggest how changes in source water qualities or customer water quality requirements may impact system operation. It is, therefore, demonstrated that water utilities which operate regional multiquality nondrinking water distribution systems could benefit from the exploration of trade-offs between water quality and pumping costs for the purpose of operational planning.

Climate change and increased urban demand can significantly stress water supply systems, emphasizing the importance of reallocating reservoir storage for the designed uses. Most studies on climate change assessment have analyzed arid region reservoirs due to high interannual variability in streamflows. This study focuses on a within-year reservoir system, Lake Jordan in North Carolina, from a temperate region that has been experiencing rapid growth since the 1990s. Given the interest in utilizing climate change projections for planning purposes, the current operational policies are evaluated, and revised rules for operating the within-year system over 30 year period (2012–2041) are suggested. Downscaled general circulation model (GCM) projections are used to implement the soil and water assessment tool (SWAT) model for the Upper Cape Fear River basin to estimate changes in mean monthly streamflows during 2012–2041 at Lake Jordan. Projected monthly streamflows from four GCMs indicate wet winter conditions and increased interannual variability. The authors forced the reservoir model with multiple streamflow realizations that preserve the projected changes in monthly streamflow using a stochastic scheme. The within-year reservoir system performance was evaluated under stationary climate, climate change under existing and projected water demands, and by investigating interventions to ensure the design reliability under increased demands. These results indicate that the changes in the reliability due to increased urban demands are small because initial reservoir storage ensure the demand for multiple seasons. However, increases in the urban demand and streamflow variability tend to decrease the reservoir resiliency, forcing the within-year reservoir to behave like an over-year system. This could result in increased period of proactive measures such as restrictions and necessitates periodical reevaluation of drought management plans for better managing existing systems.

A utility may detect contaminant in a water distribution network through water quality sensor information, which indicates that a biological pathogen or chemical contaminant is present in the network. A utility manager should identify actions that can be taken to protect public health, and flushing a contaminant by opening a set of hydrants can be an effective response action. Hydrants should be selected and timed to flush the contaminant; however, accurately ascertaining the characteristics of the contaminant source may be impossible, which creates difficulties in developing a hydrant flushing strategy. This research develops a decision-making approach that is designed to select hydrant flushing strategies in response to sensor activations and does not require information about the characteristics of the contaminant source. A sensor-hydrant decision tree is introduced to provide a library of rules for opening and closing hydrants based on the order of activated sensors. Sensor-hydrant decision trees are developed for a wide range of contaminant events using a simulation-optimization methodology. Potential contamination events are generated using Monte Carlo simulation and are simulated using a water distribution system model. Events are classified based on the order of the activation of water quality sensors in the network, and a noisy genetic algorithm is used to identify hydrant strategies for each class of events. Three sensor-hydrant decision trees are developed to represent risky, risk-averse, and adaptive management strategies. A risk-averse strategy specifies immediate actions to achieve average performance over many events. A risky strategy specifies specialized actions based on the prediction of the plume movement or a decision to wait to receive more information. An adaptive strategy specifies the actions for opening hydrants as each sensor is activated. An adaptive approach does not require predictions of the plume movement, but may result in lower performance due to delays in taking actions. The methodology is demonstrated to develop sensor-hydrant decision trees for a virtual midsized municipality, Mesopolis.

Managing urban storm water is challenging under the best of situations, and due to projected increases in intensity of rainfall events, is exacerbated by climate change. Institutional and individual aspects of urban storm water management and the implications for low-impact development (LID) are presented. The paper frames storm water as a public good provision issue in order to build on existing knowledge about that kind of social dilemma. This topic is then examined in more detail through stakeholder interviews conducted in Somerville, Massachusetts, United States. Interviews were completed at a variety of management levels, from household to regional planning level, and are related back to the theory of public good provision. Finally, synthesis of theory and practice results in specific recommendations for urban storm water management, based on revising the storm water institutional framework, showcasing redevelopment opportunities, and facilitating education and awareness through local NGOs.

Maintaining sufficient chlorine residual in a water distribution system is important for water quality and system integrity. Discharging stagnant water from the pipeline through automatic flushing device (AFD) is a feasible method to maintain water quality. This paper presents a simulation-based optimization method to minimize total AFD discharge volume during a 24-h horizon. EPANET 2.0 is used as a hydraulics and water quality simulator. This is formulated as a single-objective optimization problem. The decision variables are the AFD operation patterns. The methodology has three phases. In the first phase, AFD discharge capacities are calculated to evaluate whether the existing AFDs are able to maintain chlorine residuals in the water network. In the second phase, the decision variables are converted to AFD discharge rates. A reduced gradient algorithm is used to quickly explore and narrow down the solution space. At the end of this phase, decision variables are switched back to the AFD operation patterns. In the third phase, simulated annealing is used to search intensively to exploit the global minimum. The method is demonstrated on the water system located at the south end of Pinellas County, Florida, where AFD optimal operation patterns are achieved.

A methodology to analyze the vulnerability of water distribution networks (WDNs) to earthquakes by means of risk assessment is presented. The consequences of multiple pipe failures due to earthquakes are investigated in terms of unsupplied demand to customers. To this aim the steady-state WDN analysis is performed considering system topology changes due to closing isolation valves in order to separate the network segments where failures occur. The pipe failure probability is calculated using fragility curves from the American Lifelines Association (ALA). The identification of the worst pipe failure scenarios as trade-offs between unsupplied demand and probability of occurring is formulated as a multiobjective combinatorial problem and solved using a multiobjective genetic algorithm as optimization strategy. The methodology is applied to the Exnet network. Results show that WDN seismic vulnerability depends also on network segmentation due to the existing isolation valve system. The methodology allows analyzing and ranking the worst scenarios, being a valuable decision support for improving WDN preparedness to earthquakes and allowing planning appropriate asset enhancements and mitigation measures to improve system resilience.

Many people in developing countries do not have access to sufficient water supply according to the World Health Organization. In addition, most water distribution systems are branched due to their lower pipe costs and, therefore, do not have redundancy in case of a pipe break. As funds do become available, the question arises as to which loop to connect first to provide the most redundancy at the least cost. A loop selection algorithm suitable for the educational background of development workers, employing an adaptive greedy heuristic algorithm, is proposed and demonstrated on two real branched systems in Central and South America in which a sufficiently large pipe was added to each possible loop with adjacent dead-end junctions and the redundancy and cost quantified. These possible loops were then ranked in terms of their ability to provide water service to the most users for the least cost. It was found that first priority must be given to the possible loop that connects the water source to an additional system junction since, if the sole pipe that connects the source to the system fails, then no users have access to water. After that, connecting upstream loops first provided the most redundancy if all users were considered of equal importance, but not always at the least cost, since upstream loops may cost more to connect due to (1) long lengths, or (2) neighboring pipes having to be enlarged to handle the extra flow caused by the connection of the loop.