Journal of Water Resources Planning and Management

Looped water distribution system (WDS) repartitioning to district metering areas (DMAs) gained popularity as an effective technique to manage the system and detect and reduce system leakages. However, to apply this method to real WDS, various system properties should be taken into account to ensure efficient water supply. The battle of water networks district meter areas (BWNDMA) is a challenging problem that requires the redesign of the E-Town city network in Colombia. The water utility is looking to repartition the network into manageable DMAs while supplying future demands, keeping minimum and maximum pressures, improving water quality, operating the network at uniform low pressures, balancing water sources, and meeting their seasonal production capabilities. The problem is stated as a multiobjective optimization problem with DMA partitioning being one of eight equal-weighted objectives. They may be reached by (1) closing, opening, or replacing existing pipes, (2) adding parallel pipes, (3) managing storage tanks, pressure valves, and flow-control valves, and (4) utilizing pumps in the dry season. With no known analytical methodology to optimize such a large mixed-integer nonlinear problem, a major difficulty is to find a feasible solution; therefore, a multistage classic engineering approach was taken. First, source allocation and general design were carried out for the operational zones. Then, tank volumes were adjusted to meet their constraints. At this stage, DMAs were introduced to meet pressure regulations. Finally, detailed design and fine-tuning of the operations were carried out. This paper describes the taken procedures and obtained results for the redesign of the E-Town network.

Estimating the presence of economies of scale and scope is essential to support restructuring policies aimed at increasing the efficiency of the water industry. This paper demonstrates the usefulness and advantages of using a flexible technology to estimate economies of scale and scope in the water industry. The empirical application focuses on the English and Welsh water and sewerage industry, where companies offer a variety of services; water and sewerage companies (WaSCs) and water-only companies (WoCs) are two common business models within the industry. In this paper and for the first time, a flexible technology model is estimated that allows for type-specific technologies using a quadratic cost function to analyze the cost properties of water companies providing different services. The results do not support a common technology for WaSCs and WoCs. Thus, a flexible technology approach may be preferred for a reliable analysis of cost properties of WaSCs and WoCs. The results also show that the existence of economies of scale for WaSCs and WoCs, as well as integration economies between water and sewerage services, could potentially create substantial cost savings. The methodology and results of this study are of great importance to both companies and regulators to facilitate informed decision making in terms of optimal industry configuration and possible unbundling reforms.

Urban planners face challenges in water infrastructure development decisions due to short-term variation in water availability and demand, long-term uncertainty in climate and population growth, and differing perspectives on the value of water. This paper classifies these multiple uncertainties and develops a decision framework that combines simulation for probabilistic uncertainty, scenario analysis for deep uncertainty, and multistage decision analysis for uncertainties reduced over time with additional information. This framework is applied to a case from Melbourne, Australia, where a drought from 1997 to 2009 prompted investment in a $5 billion desalination plant completed in 2012 after the drought ended. The results show opportunities for significant reduction in capital investment using flexible design. Building no infrastructure is best in most simulations. However, in 10% of simulations, building no infrastructure leads to regret of greater than $10 billion compared with a small, flexible desalination plant. Scenario analysis for deep uncertainties underlines the significant impact of assumptions about the future and also on value judgments about the cost of water scarcity in evaluating infrastructure performance.

Construction of Shasta Dam on the Sacramento River in 1945 prevented anadromous fish from accessing their natural cold-water spawning habitat above the dam and is one of the factors that caused population declines in Chinook salmon and other species. To address listing of winter-run Chinook salmon under the Endangered Species Act, the U.S. Bureau of Reclamation began operating a temperature-control device (TCD) on Shasta Dam in 1997 that enabled selective withdrawal of reservoir outflows for control of downstream water temperatures while maximizing power generation. However, effectiveness of TCD operations for addressing fisheries concerns under hydroclimate variability is unknown. Stochastic methods to generate synthetic extreme hydroclimate conditions were combined with hydrodynamic modeling of reservoir operations and interactions with reservoir managers to examine the TCD’s ability to meet downstream temperature objectives. Model simulations suggest that TCD withdrawal schedules could reduce outflow temperature target exceedances when compared with more traditional dam operations such as solely hypolimnetic or epilimnetic releases. However, constraints imposed by multipurpose operational considerations, especially under extreme climate conditions, and the Sacramento–San Joaquin system’s complex regulatory environment limit use of reservoir management to provide optimal thermal conditions best for Chinook salmon spawning and recruitment.

Managing energy, water, and environmental priorities and constraints within a cascade hydropower system is a challenging multiobjective optimization effort that requires advanced modeling and forecasting tools. Within the mid-Columbia River system, there is currently a lack of specific solutions for predicting how coordinated operational decisions can mitigate the impacts of total dissolved gas (TDG) supersaturation while satisfying multiple additional policy and hydropower generation objectives. In this study, a reduced-order TDG uptake equation is developed that predicts tailrace TDG at seven hydropower facilities on the mid-Columbia River. The equation is incorporated into a general multiobjective river, reservoir, and hydropower optimization tool as a prioritized operating goal within a broader set of system-level objectives and constraints. A test case is presented to assess the response of TDG and hydropower generation when TDG supersaturation is optimized to remain under state water-quality standards. Satisfaction of TDG as an operating goal is highly dependent on whether constraints that limit TDG uptake are implemented at a higher priority than generation requests. According to the model, an opportunity exists to reduce TDG supersaturation and meet hydropower generation requirements by shifting spillway flows to different time periods. A coordinated effort between all project owners is required to implement systemwide optimized solutions that satisfy the operating policies of all stakeholders.

With increasing population and development, communities worldwide face shortages of water for potable supply. A report has identified hot spots of likely conflict over water in the western United States by 2025; therefore, unexploited sources of water must be identified to reduce these problems. Direct potable reuse (DPR) is a supply-side approach that can improve sustainability and reliability of water supplies by recovering drinking water from wastewater. Most potable reuse research has focused on large, coastal communities, which have different opportunities and constraints regarding water rights, treatment technologies, regulatory considerations, and costs than inland communities in arid environments. It is concluded that the challenges associated with the coastal and inland contexts are very different, and information regarding DPR suitability generated for coastal communities may not be applicable to inland communities. This paper identifies the unique challenges associated with the technical, regulatory, and economic aspects of DPR in inland communities. More research is needed on inland DPR, and this paper highlights what would be most useful to assist inland communities in assessing the feasibility of DPR.

In order to satisfy the practical requirement of the power grid in China, this paper presents a multiobjective operation model for a cascaded hydropower system simultaneously considering the maximization of gross generation and firm output, as well as various complex constraints. Then, a multiobjective particle swarm optimization (MOPSO) is presented here to solve this problem. This algorithm combines the merits of chaos theory, genetic operators, adaptive adjustment strategy, and the heuristic constraint-handling method to help the population explore the search space efficiently: the logistic map is introduced to generate the initial population distributed uniformly in problem space; both the inertia weight and learning coefficients are dynamically changed as iteration goes on; an archive set is used to conserve the nondominated solutions found during evolution; the personal and global best position for each particle are determined by crowding distance and a feasibility-based dominance relationship; the classical mutation and crossover operators are introduced to enhance the population diversity; a novel constraint-handling method is proposed to address the complicated constraints. To testify to its effectiveness, the MOPSO is applied to the Wu River cascade hydropower system in southwest China. The results in different cases indicate that MOPSO is able to provide better solutions than the NSGA-II method, providing an effective technique for the operation of a hydropower system.

In this study, a new evaluation method for the water supply safety of a dam is proposed. This method considers both climatic conditions and storage characteristics of a dam. The annual variation of dam storage is represented by a broken-line model, the lines of which are determined by only three factors: the monthly design water supply during the dry period; dam storage at the end of the dry period; and changes in dam storage during the wet period. From the results of bivariate frequency analysis, a unique broken-line model is derived under multiple scenarios with the given return periods for the evaluation of water supply. The proposed method is applied to a total of five major dams in Korea. It is shown that the water supply safety of a dam can be quantified by using the concept of the return period, and five major dams have water supply safety corresponding to return periods of 10–50 years. Among them, the Soyanggang Dam is found to be the most stable with respect to water supply safety in Korea.

Pumped water storage (PWS) is an advanced component of interbasin water transfer (IBWT) projects that plays a critical role in addressing streamflow variability. However, improper operating rules result in a large amount of unnecessary pumping and spills, wasting water resources and energy. Here, multiobjective optimization (MO) was applied to develop effective operating rules for PWS with the objectives of minimizing the water shortage index and maximizing the net revenues of consumed and produced energy. A metaheuristic algorithm named cuckoo search was used to optimize the decision variables in the framework of parameterization–simulation–optimization. Additionally, the water diversion performance of PWS and parallel reservoirs (without pumped storage) were compared. The Han to Wei IBWT project in northwest China was selected for a case study. The results indicate that (1) the proposed MO model and adopted methods are effective for derivation of PWS operating rules, improving water use benefits and decreasing operational costs significantly; (2) the two optimization goals established in the MO model conflict (increasing water supply reliability will decrease the net revenue of energy); and (3) when the water diversion target is relatively small, parallel reservoirs outperform PWS; however, PWS is superior to parallel reservoirs when the water diversion target increases.

As an important renewable energy resource, hydropower plays an irreplaceable role in reducing power shortages in modern electrical systems throughout the world. This study focuses on the fixed head hydropower operation problem considering power shortages, which is classified as a large-scale nonlinear constrained optimization problem with a set of complex operational constraints. In order to efficiently solve this problem, a novel quadratic programming (QP) model is developed, in which the goal is to find the optimal hourly operational policy for all hydropower plants in a system so as to minimize the sum of squared energy deficits over the scheduling horizon. The results of a ten-reservoir hydropower system show that the proposed approach can efficiently find better solutions than several previous optimization methods for energy deficit reduction. Thus the proposed technique is effective for hydropower scheduling problems in which the assumption of fixed hydraulic head holds.