Journal of Water Resources Planning and Management

The design of district metered areas (DMAs) in existing water distribution networks, especially in urban areas, involves a high number of decision variables, and the effects of implementing them in districts have to be evaluated in order not to affect the quality of the service to customers. A new methodology for designing a given number of districts in looped water distribution networks is proposed here. It is based on graph theory and takes into account some important DMA design criteria: the maximum and minimum size recommended for a district, the connectedness of each district to the water supply source, and the absence of links between the districts. Therefore, it allows the creation of DMAs that are independent from each other. A recursive bisection procedure has been applied to create districts, while an algorithm for graph traversal has been used to verify whether each district can be reached from the water source and connectivity between the nodes. The successful application of the proposed methodology to a case study has proven its effectiveness for district metered areas design in real urban water distribution networks.

The multiobjective optimization model described in this study is aimed at exploring the tradeoff between cost and resiliency for water distribution systems optimal design. Many have dealt previously with minimizing cost where reliability was quantified as a constraint. Fewer considered both cost and reliability as objectives. This work suggests a methodology for least cost versus reliability (quantified as resiliency) optimal design, introducing the following contributions: (1) a genetic algorithm multiobjective formulation integrating a previous theoretical result of a possible maximum of two adjacent discrete pipe diameters for a single pipe; (2) comparable results to previous best least-cost design solutions for the two-looped and Hanoi networks; (3) a real life-sized example application analysis for pipes reinforcement; and (4) an interpretation of resiliency through its comparison to two explicit reliability measures involving demands increase and pipes failure, reconfirming that resiliency improvement does not necessarily imply a reliability increase. Three example applications are explored through base runs and sensitivity analyses for demonstrating the study findings.

Long-term price changes in water resources benefits may greatly affect a project’s value, however the traditional approach to river basin planning has not been able to take full account of these uncertainties. Additionally, the relatively recent approach of adaptive management does not provide much systematic guidance for planners. This paper proposes an approach that allows planners of river basins to incorporate flexibility into the design to enable them to increase the expected value of these projects by avoiding untimely elements, taking advantage of favorable opportunities. This paper considers the application of a midfidelity screening model to identify flexible design opportunities and strategies. Such a model is adopted to explore the impacts of future electricity price uncertainty on a proposed system of hydroelectric dams in Ethiopia. Using possible price paths developed from a binomial lattice model calibrated on price variability, the screening model is used to (1) identify the most flexible construction sequence for building the dams and (2) value various options exercised on the most flexible construction sequence. Scenarios are evaluated using the criteria of expected net present value and capital expenditure and assessed using cumulative distribution functions. Results indicate that the best option increases the expected net present value of the most flexible construction sequence by nearly 2%. Furthermore, the cumulative distribution function curve analysis demonstrates how a failure to consider uncertainties such as price may result in a significant underevaluation or overevaluation of the project. Thus, this study highlights the value of a systematic approach using a midfidelity screening model to assess the uncertainties present in water resource infrastructure investments.

This research investigates the application of multiobjective optimization (MO) modeling to the issue of water resources sustainability, from a water supply standpoint, with specific application to the Prescott Active Management Area (AMA) in Arizona. One unique aspect of the investigation is the development of a method to quantify the nonuse value of groundwater for use in a quantitative optimization model. Another is the incorporation within the model of objectives that include the typically conflicting goals of growth, conservation, and cost minimization. The model is solved using a multiobjective genetic algorithm.

Many different methods have been devised to solve the nonlinear systems of equations that model water distribution networks. Probably the most popular is Todini and Pilati’s global gradient algorithm (GGA). Given the GGA’s success, alternative methods have not aroused much interest. One example is the co-tree method, which requires some cumbersome steps in its implementation. In this paper, a reformulated co-trees method (RCTM) is presented that simplifies the procedure by manipulating the incidence matrix into trapezoidal form: a lower triangular block at the top representing a spanning tree and rectangular block below it representing the corresponding co-tree. This reordering leads to significant efficiencies that make the RCTM competitive with the GGA in certain settings. The new method has some similarities to the loop flows corrections formulation, and it is shown, by application to a set of eight case study networks with between 932 and 19,647 pipes and between 848 and 17,971 nodes, to be between 15 and 82% faster than the GGA in a setting, such as optimization using evolutionary algorithms, where the methods are applied hundreds of thousands, or even millions, of times to networks with the same topology. It is shown that the key matrix for the RCTM can require as little as 7% of the storage requirements of the corresponding matrix for the GGA. This can allow for the solution of larger problems by the RCTM than might be possible for the GGA in the same computing environment. Unlike some alternatives to the GGA, the following features make the RCTM attractive: (1) it does not require a set of initial flows that satisfy continuity; (2) there is no need to identify independent loops or the loops incidence matrix; (3) a spanning tree and co-tree can be found from the incidence matrix without the addition of virtual loops, particularly when multiple reservoirs are present; and (4) it does not require the addition of a ground node and pseudoloops for each demand node and does not require the determination of cut sets. In contrast with the GGA, the RCTM does not require special techniques to handle zero flow problems that can occur when the head loss is modeled by the Hazen-Williams formula (a sufficient condition is given). The paper also (1) reports a comparison of the sparsity of the key RCTM and GGA matrices for the case study networks; (2) shows mathematically why the RCTM and GGA always take the same number of iterations and produce precisely the same iterates; and (3) establishes that the loop flows corrections and the nullspace methods (previously shown by Nielsen to be equivalent) are actually identical to the RCTM.

This paper develops optimal hedging rules for reservoir flood control operation under hydrological uncertainty using hydroeconomic and mathematical analysis. The capacity to convey flood flows is sometimes a scarce resource. Hedging for flood operations uses reservoir storage to allocate the expected flood-safety margin (EFSM, i.e., the gap between expected flood volume and flood-conveyance capacity) optimally between present and future periods. Optimal flood-operation hedging falls into three cases, namely, (1) for large expected floods, all flood storage and almost all channel-conveyance capacity are used in the current period to cope with the current, more certain, and urgent flood risk; (2) for medium expected floods, the available EFSM is balanced between the current and future periods, but a larger portion of the total EFSM remains allocated to the current stage; and (3) for small expected floods, the future stage receives greater EFSM allocation by keeping reservoir space empty in the current period. Optimal hedging for flood operation is illustrated by a curve similar to that of hedging for water supply. The physical implications of hedging highlight the economic significance of this practice for balancing the marginal value of scarce flood-management resources under uncertainty.

The Intergovernmental Panel on Climate Change (IPCC) suggests that vulnerability to climate change depends on three main factors: exposure, sensitivity, and adaptive capacity. Each factor was evaluated in a hydrologic context; for instance, exposure was interpreted as a change in surface runoff. Factors were combined using a geographic information system (GIS), and an overall methodology was proposed to map hydrologic vulnerability. The Lerma-Chapala basin was selected as a case study since the largest water body in Mexico is located at its outlet. The long-term rate of change in surface runoff was estimated considering the variation in future precipitation from 23 atmosphere–ocean general circulation models (AOGCMs) and by using the reliability ensemble averaging (REA) method. Two climate change scenarios from an IPCC special report on emissions scenarios and three time horizons (2030, 2050, and 2100) were chosen. Results showed a decrease in surface runoff of up to 29% (A1B-2100) in the northern part of the basin, and consequently this area is likely to have more frequent droughts. However, it would be challenging to compensate for the lack of surface runoff since groundwater resources are already depleted, and thus adaptive measures need to be taken.