Journal of Water Resources Planning and Management

Water distributions systems must reliably supply water for fire-fighting needs as well as everyday demands but are vulnerable to a range of failure types that can compromise both functions. A methodology is presented integrating failure probability, risk analysis, and optimization of risk that can be used to assess system vulnerabilities and potential mitigation actions. To demonstrate multiple failure mode analysis, three failure types are included: accidental failure due to soil-pipe interaction, accidental failure due to a seismic event, and malevolent attack. A risk-optimization algorithm is implemented using dynamic programming to identify the failure scenarios having the greatest consequences and probability rather than focusing on just one aspect of vulnerability. Finally, potential mitigation strategies are assessed in a benefit-cost-risk reduction analysis. The methodology is intended as a practicable means for infrastructure managers to assess and address system vulnerabilities in a realistic and cost-effective manner.

Reducing water loss through bursts is a major challenge throughout the developed and developing world. Currently burst lifetimes are often long because awareness and location of them is time- and labor-intensive. Advances that can reduce these periods will lead to improved leakage performance, customer service, and reduce resource wastage. In water-distribution systems the sensitivity of a pressure instrument to change, including burst events, is greatly influenced by its own location and that of the event within the network. A method is described here that utilizes hydraulic-model simulations to determine the sensitivity of potential pressure-instrument locations by sequentially applying leaks to all potential burst locations. The simulation results are used to populate a Jacobian matrix, quantifying the different sensitivities. This matrix may then be searched to identify different instrument locations to achieve required goals: maximising overall sensitivity to all potential events or selective sensitivity to events in different network areas. It is shown here that by searching this matrix to optimize such selective sensitivity, while minimising instrument numbers, it is possible to provide useful burst-localization information. Results are presented from field studies that demonstrate the practical application of the method, showing that current standard network models can provide sufficiently accurate quantification of differential sensitivities and that, once combined with event-detection techniques for data analysis, events can effectively be localized using a small number of instruments.

This paper reviews policy and research initiatives that have begun to address three major challenges to incorporate regional environmental impacts in the design and optimization of drinking water distribution systems. These challenges are to (1) develop a regulatory framework to limit the environmental impacts linked to upgrades and operation of water networks; (2) select indicators and develop models to quantify energy use, environmental impacts, and emissions for the design and operation of water distribution systems; and (3) develop decision support systems to integrate environmental sustainability objectives into the decision-making process for utilities. This paper concludes by discussing realistic steps that water utilities can take to reduce the environmental impact of their business operations.

This paper reports the use of many-objective optimization for water distribution system (WDS) design or rehabilitation problems. The term many-objective optimization refers to optimization with four or more objectives. The increase in the number of objectives brings new challenges for both optimization and visualization. This study uses a multiobjective evolutionary algorithm termed the epsilon Nondominated Sorted Genetic Algorithm II ($\epsilon$-NSGAII) and interactive visual analytics to reveal and explore the tradeoffs for the Anytown network problem. The many-objective formulation focuses on a suite of six objectives, as follows: (1) capital cost, (2) operating cost, (3) hydraulic failure, (4) leakage, (5) water age, and (6) fire-fighting capacity. These six objectives are optimized based on decisions related to pipe sizing, tank siting, tank sizing, and pump scheduling under five different loading conditions. Solving the many-objective formulation reveals complex tradeoffs that would not be revealed in a lower-dimensional optimization problem. Visual analytics are used to explore these complex tradeoffs and identify solutions that simultaneously improve the overall WDS performance but with reduced capital and operating costs. This paper demonstrates that a many-objective visual analytics approach has clear advantages and benefits in supporting more informed, transparent decision-making in the WDS design process.

This study addresses the management of a water supply system under uncertainty. Water is taken from sources that include aquifers and desalination plants and conveyed through a distribution system to consumers under constraints of quantity and quality. The replenishment into the aquifers is stochastic, whereas the desalination plants can produce a large and reliable amount, but at a higher cost. The cost is stochastic because it depends on the realization of the replenishment into the aquifer. A new implicit mean-variance approach is developed and applied. It utilizes the advantages of implicit stochastic programming to formulate a small size and easy to solve convex external optimization problem (quadratic objective and linear constraints) that generates the mean-variance tradeoff without the need to solve a large-scale problem. The results are presented as a tradeoff between the expected value versus the standard deviation. At one end of the tradeoff curve, dependence on the aquifer results in low expected cost and higher cost variability. At the other end, when all of the water is taken from desalination, the cost is high with no variability (deterministic).

Population increase and requirements as well as water resource limitations reveal the necessity for the optimal operation of water distribution networks (WDNs), especially during shortage events. Because WDNs directly affect lifestyles, operational plans that take into account abnormal conditions are necessary. Under such circumstances, some possible solutions, such as transferring water from other basins or using recycled waters, may be inapplicable or insufficient, as continuous operation of WDNs would not be possible anymore. This paper proposes hedging or intermittent water supply as a contrasting way against a water shortage juncture. In this method of operation and in a specific time span during the operational period, the amount of water supplied to each consumer could be different even if their demands are equal. Thus, the selection of a policy that guarantees equity in supplying consumers’ demands has to be considered. In addition, supplying demands with sufficient pressure would promote consumers’ satisfaction. Hence, this method of operation needs a planning methodology that takes into account equity, satisfaction, available water, consumption fluctuations, and other social constraints besides hydraulic parameters influencing the behavior of WDNs and the interaction between them. The quantification of the aforementioned parameters and constraints requires mathematical models that simulate the behavior of networks and optimize the mentioned goals. In this paper, the operation of two networks is examined. The honey-bee mating optimization (HBMO) algorithm is used as the optimization tool linked to EPANET 2, which is the hydraulic simulator of the networks. To compare various methods of facing water shortage, WDN performance criteria are also calculated. Results show that a 100% resiliency criterion for hedging and intermittent water supply is 25–50% more favorable than other methods. In addition, a nodal resiliency criterion of water allocated under various operational methods and irrespective of initial storage volume of the reservoir show the superiority of intermittent water supply compared with other approaches, indicating the efficient management of available water allocated in the operational period.

The pressure-discharge relation used in continuity equations is one of the most important components of hydraulic models based on head-driven simulation method, as it has a great impact on the accuracy of the results of these models. Several pressure-discharge relations have been proposed and used in head-driven simulation method, but there are no laboratory and field studies available regarding the accuracy and correctness of these relations. In this research a laboratory set up and a field investigation in some parts of a real water distribution network are used to collect the required data. Flow discharge data from different faucets, based on laboratory and field measurements, are used to compare the proposed pressure-discharge relationships. Furthermore, in this paper, a new pressure-discharge relation is proposed for volumetric and human-based demands that is more reasonable than some previous relations and can be used in pressure-dependent models.

Even in relatively water-rich regions, withdrawal and consumption of water has the potential to create instream freshwater ecosystem water scarcity, especially at seasonal and local scales. Water resource policy must balance consumptive uses of water against corresponding ecosystem impacts of flow depletion. In this study, the concept of an adverse resource impact threshold, as established by the Michigan Water Withdrawal Assessment Process, is applied in conjunction with a water use database to identify the cause, location, and scale in space and time of instream freshwater ecosystem water scarcity caused by consumptive uses of water. The study results show that there is a strong multiscalar linear relationship between freshwater consumption, adverse resource impact ecological flow thresholds, and spatial scale. On average and at the whole-watershed scale, water scarcity does not exist in this watershed, but water scarcity does occur on a localized basis, especially in the summer and at small watershed scales of less than $300{\mathrm{km}}^2$, because of a combination of irrigation withdrawals, concentrated urban withdrawals, and low ecological flow thresholds. The aggregated effects of localized flow depletion also affect $800–\mathrm{2,000}{\mathrm{km}}^2$ scale catchments. Management of water scarcity in water-rich areas should therefore focus on the spatio-temporal locations where the impacts occur and where an average pattern of water abundance yields to localized scarcity, in this case during late summer months in subwatersheds smaller than $300{\mathrm{km}}^2$. This analysis informs integrated water resources management approaches, contributes to a better understanding of the relationship between scale and environmental impact as water is shared among competing uses, and sheds light on the use of adverse resource impact ecological flow thresholds to define water scarcity in relatively water-rich regions. These results may be generalized to inform the implementation of the Michigan Water Withdrawal Assessment Process and similar processes throughout the Great Lakes region and in water-rich locations around the world where water is generally abundant but localized water scarcity is becoming an increasingly important issue.

In groundwater-quality monitoring it is important to consider that groundwater-contaminant concentration can vary vertically. To find the actual concentration of contaminants in a groundwater plume, it may be necessary to sample at different depths at the same location. This can be expensive due to the initial cost of the wells and the costs of multiple chemical analyses for each round of sampling. A sampling optimal design in three dimensions (3D) allows identifying the contaminant-concentration variations in all spatial directions at a minimum cost. The objective of this paper is to extend a methodology for the optimal design of groundwater-quality sampling networks previously introduced by the first author of this paper, to include the selection of measurements at different depths. The method is based on the application of a version of the ensemble smoother, a stochastic transport model, and a sequential optimization method. The method is demonstrated for the design of 3D groundwater-monitoring networks in two hypothetical problems.

The design of urban drainage systems consists of solving two subproblems: (1) generating the layout and (2) sizing the sewers. The latter includes pipe diameters, installation depths, and pumping facilities, all of which are significantly influenced by the layout configuration. This work aims at introducing a method to solve the layout subproblem based on the graph theory. For a given city, all possible sewer lines and manholes are considered for the sewer network so that an undirected looped graph is initially formed. Next, an adaptive procedure entitled the loop-by-loop cutting algorithm is developed to create feasible sewer layouts from the base graph. Using this algorithm, all constraints of the sewer layout subproblem are systematically handled. By defining an objective function, the optimum layout is achieved by employing a simple genetic algorithm. After the sewer layout is determined, the specifications for pipes and pumps are designed by using a discrete differential dynamic programming model. A benchmark sewer system is also considered from the literature to be optimized. The results are discussed and compared with previous studies. It is concluded that the loop-by-loop cutting algorithm is especially useful for the design of urban drainage systems in flat areas. The method is also computationally efficient and easy to implement and add to optimization solvers.

Facing uncertain future conditions, flood-damage-reduction alternatives with large positive expected net benefits may be accompanied with high uncertainty. In decision-making under uncertainty, not only failure probability and failure consequences but also the cost of lost opportunity should be considered so as to enhance risk-informed decision-making for hydrosystem design, planning, and management. This paper proposes a risk measure, i.e., the expected opportunity loss (EOL), in a risk-based framework for flood-damage-reduction project design. The opportunity loss for a chosen alternative is the difference between the payoffs of this alternative and the best payoff of all alternatives. The risk measure of EOL can quantify the adverse consequences associated with making a wrong decision due to the uncertain state of nature and it can also capture the correlation effect of the net benefits of two competing design alternatives. Using EOL, alternatives can be ranked by the minimax regret principle. The acceptable risk of the decision maker is conceptually compatible with EOL and can be used to test the feasibility of the design alternatives under consideration. An example based on a case study for flood damage reduction is used to demonstrate the application of the proposed risk-based decision-making model. The example application shows that the uncertainty of the project net benefits is significant, and thus the explicit consideration of tradeoffs between the project risks and net benefits is essential. Furthermore, the example also shows that the uncertainty and correlation between the net benefit in different projects can have a significant influence on the ranking of alternatives.

Reservoir management strategy optimization requires benefit calculations based on reservoir storage, which is variable because of sedimentation. It is therefore necessary to express reservoir benefits as a function of reservoir storage. For planning purposes, a need for rapid benefit calculation techniques often exists. Such a calculation model is developed in this paper, quantifying annual water supply, power generation, and flood control benefits as a function of reservoir storage. The calculation model sets up a relationship among reservoir storage, reliability, water inflow, and flood characteristics and annual average water supply, power generation, and flood control benefits. The Gould-Dincer approach is adopted to calculate annual average water supply and storage hydropower generation benefits and relate them to reservoir storage and reliability. The property damage avoided (PDA) method is used to quantify annual average flood control benefits. The results obtained using the rapid assessment technique are compared to those obtained from other more detailed quantification methods executed for a number of power generation scenarios for the Three Gorges Reservoir, and are found to be of satisfactory calculation accuracy for planning purposes. Because of the lack of data, the annual average flood control benefit calculation method was tested for the Three Gorges Reservoir with assumed flood loss data, illustrating the flood control benefit at different flood storages.

The Mekong River supports unique biodiversity and provides food security for over 60 million people in the Indo-Burma region, yet potential changes to natural flow patterns from hydropower development are a major risk to the well-being of this system. Of particular concern is the ongoing and future development of 42 dams in the transboundary Srepok, Sesan and Sekong (3S) basin, which contributes up to 20% of the Mekong’s annual flows and provides critical ecosystem services to the downstream Tonle Sap Lake and the Mekong Delta. To assess the magnitude of potential changes, daily flows were simulated over 20 years using the HEC ResSim and SWAT models for a range of dam operations and development scenarios. A 63% increase in dry season flows and a 22% decrease in wet season flows at the outlet of the 3S basin could result from the potential development of new dams in the main 3S rivers under an operation scheme to maximize electricity production. Water-level changes in the Mekong River from this scenario are comparable with changes induced by the current development of Chinese dams in the Upper Mekong Basin and are significantly higher than potential flow changes from the proposed 11 mainstream dams in the Lower Mekong Basin. Dams on the upper sub-tributaries of the 3S basin have very little effect on seasonal flow regimes because most of those projects are run-of-the-river dams and have small reservoir storages. The effects on hourly flow changes resulting from intra-daily reservoir operations, sediment movement, water quality, and ecology require further study. Strategic site selection and coordinated reservoir operations among countries are necessary to achieve an acceptable level of development in the basin and to mitigate negative effects in seasonal flow patterns, which sustain downstream ecosystem productivity and livelihoods.

An integrated land and water management model incorporating inexact framework is developed for sectorwise and seasonwise planning in the canal subcommand area. The gray systems theory is utilized for defining system parameters and decision variables within the inexact framework. The model considers the objective of maximizing the net annual return subject to optimal allocation of land and water resources for given imprecise information on net return of crop, available resources (land, surface water, and groundwater), and water demand in the cultivable subcommand area. Gray linear programming (GLP) is utilized for solving the optimization problem. The developed model is applied to the Hirakud canal subcommand area of western Odisha, India. The model is evaluated for different scenarios with inexact bounds on available natural resources (land and water) for different crops. The model results show its usefulness in evolving crop-specific land utilization levels and quantities of surface water and groundwater resources for deriving maximum benefit. The model also provides season-specific crop-scheduling information. The evaluation results show potential applicability of the developed methodology.