Journal of Water Resources Planning and Management

The number of isolation valves installed in a water distribution pipe network is typically based on conservative rules of thumb that have been propagated throughout the water industry. However, little work has been done on assessing the valve density’s impact on customer service during pipe failure and repair. This study investigates the impact of valve density on a realistic network’s service metrics. Water distribution network (WDN) service level is quantified using nodal and system severity (ratio of supply to demand during the analysis period) under single pipe failures and customer risk of being out of service (product of likelihood of pipe failure and number of customers out of service). As a baseline for comparison, a WDN is created for a $23.3\text{-}{\mathrm{km}}^2$ ($9\text{-}{\mathrm{mi}}^2$) residential area in Tucson, Arizona, following common US design criteria. The impact of the number of valves is assessed for alternative numbers of valves that are placed at random locations. These results are compared with the N and N−1 valving rules. Tradeoffs between system performance and the number of isolation valves are then examined for different network topologies and the levels of connectivity between the transmission and distribution networks.

In recent years, there have been multiple incidents of drinking water contamination reported in major US cities. A critical part of the response to such an emergency is the distribution of bottled water to affected residents via points of distribution (PODs). However, in all of these instances the locations of the PODs and the limited transportation options of the residents meant that some residents had less accessibility to the PODs to obtain the clean water they needed. Unfortunately, current policies and regulations fail to consider spatial equity in determining placement of PODs. Thus, this study investigates the effectiveness of POD locations from the perspectives of spatial equality and spatial equity. We present a binary linear programming model that considers travel distance–based and time-based accessibility measurements simultaneously to find the optimal location of capacitated public facilities. The proposed model is applied to the Flint, Michigan, water crisis. Our results show the effects of POD locations and census block groups assigned to PODs on spatial equality and spatial equity, and the model’s ability to improve accessibility measurements. In particular, the proposed model is able to decrease travel time–based assessment and distance-based assessment by up to 12.5% and 12.24% respectively. Also, our results demonstrate the combined impact of different levels of capacity and numbers of PODs with different allowable levels of accessibility on an efficient emergency water distribution system. The results of this study offer emergency agencies and policy makers an avenue toward better guidelines and policies for an effective emergency drinking water distribution system.

Water companies are expected to deliver high-quality water services to their customers that include, among others, continuity of water supply. Unplanned water supply interruptions (UWSI) indicate a cost for the water companies and a deterioration in the quality of service for the customers. Thus, it is essential to quantify the cost of reducing UWSI, i.e., the cost of improving the quality of service to customers. This study aims to estimate the marginal cost of reducing UWSI using a stochastic frontier model, which also enabled us to estimate cost efficiency, economies of scale, and economies of density. The empirical approach focused on a sample of 21 Chilean water companies over the period 2007–2017, embracing full private, concessionary, and public water companies. The results indicate that the average marginal cost for reducing UWSI is $€2.703/\mathrm{h}$. This cost is lower for concessionary water companies compared to full private and public water companies. The study’s findings can aid regulators in designing effective policies to ensure that companies are rewarded (or penalized) for better (or worse) performance and to eliminate any welfare losses due to lower levels of service quality.

Water and energy audits in water distribution networks have been developed to assess water losses and energy losses, respectively. However, no study has considered a water quality audit. This study proposes a concept of free residual chlorine (FRC) mass audit to quantify FRC losses as a tool for water quality management. The components defined in the FRC mass balance are analogous to the components in the International Water Association water balance. The FRC mass balance metric can show (1) the loss of FRC mass through water losses, (2) the decay of FRC by chemical reactions, and (3) the amount of FRC that reaches customers. Applying this concept to a real network, it is found that the percentage of FRC mass losses is higher than the percentage of water losses due to decay by reactions. Three performance indicators are proposed to assess the FRC losses, safety, and reliability of water distribution systems in terms of water quality.

Aesthetic considerations of tap water do not necessarily indicate public health threats. If consumers notice the taste or odor of their tap water, however, they are likely to think differently of the water provider. The source of the problem is often nuisance chemicals, and although these chemicals can be measured, their detection is relative and may vary based on a person’s sociodemographics. This study aims to identify the sociodemographic and geographic parameters that influence users’ recognition of select tap water aesthetic issues. To do so, a bivariate binary probit model is used. Enabling this study is a household survey conducted in 2016 in Austin, Texas. Results indicate that the drivers of noticing odor and taste occur at the individual, household, and regional levels. By identifying factors that influence people’s perceptions of aesthetic considerations, water providers may develop outreach campaigns and make decisions that address the groups revealed in this analysis (e.g., users who pay their water bill). Additionally, this study demonstrates how joint modeling can be used to more accurately capture relationships in the water sector.

Traditionally, the design and the rehabilitation of water distribution networks (WDNs) have been addressed as separate problems. Here, a comprehensive approach to address both the design and rehabilitation of WDNs is proposed, considering the evolution of urban areas and the aging phenomena that typically involve WDNs. The search for the design and rehabilitation intervention schedule, in terms of installation of new, parallel, and replacement pipes, is addressed as a multiobjective optimization problem in which the solutions represent the trade-off between the system cost and its hydraulic resilience. A modified version of NSGA-II in combination with a pressure driven version of the EPANET 2 software was used to find optimal solutions. Application of the methodology to a literature case study indicates that it leads to a dramatic reduction in the failure costs, through a marginal increase in the investments in the short term, thanks to a farsighted intervention schedule. Also, a sensitivity analysis to the different aging phenomena was performed in order to understand which ones mostly affect the rehabilitation needs and long-term management of WDNs.

The resilience of water distribution systems (WDSs) has gained increasing attention in recent years. Various performance loss and recovery behaviors have been observed for WDSs subject to disruptions. However, a model for their characterization, which could provide further insight for resilience assessment and enhancement, is still lacking. Here, the authors develop a recovery function to model WDS performance over time following a disruption. This function is useful to compare system responses under different disruption and recovery scenarios and supports the identification of areas for improvement within various aspects of the resilience of a WDS. The proposed model was applied to two benchmark networks. Different scenarios were analyzed in which one node at a time was disrupted and two recovery strategies were implemented. It was found that the developed model supports the implementation of tailored strategies to improve WDS resilience according to the location of the disruption, therefore enhancing the efficient allocation of resources.

This paper explains and demonstrates how increasing a sampling period in pressure control may worsen a system’s performance and lead to instability. The notion of stability of continuous-time and discrete-time systems is briefly introduced and applied to a simple closed-loop inertial system. It is then demonstrated how the stability of dynamic systems depends on a sampling period as well as on gain. Subsequently, the analysis is applied to a model of an electronically controlled pressure-reducing valve (PRV) coupled with a transient model of a water distribution network (WDN). The occurrence of instabilities at overly long sampling periods is demonstrated. Practical recommendations on the appropriate choice of sampling times are put forth based on simulation results and control engineering rules of thumb given the closed-loop system’s dynamics. Performance of a theoretical pressure control scheme is then simulated under time-varying demands and with controllers designed to work at different sampling frequencies.

Quantitative predictions of urban domestic water consumption are of great significance for the planning and management of water resources. Aimed at the uncertainty in the process of water consumption forecasting, the kernel density estimation-fractional order reverse accumulative gray model was proposed. Based on the residual error of the fractional order reverse accumulative gray model, the kernel density estimation method was employed for the frequency analysis. According to the design value of residual error at different confidence levels and the predicted value of the fractional order reverse accumulative gray model, the prediction interval of the future water consumption was constructed. The model was validated using the annual urban domestic water consumption data in Beijing, Chongqing, and Qingdao. To test the performance of the model, the model was compared with the gray model with respect to the kernel density estimation—fractional order forward accumulative, kernel density estimation—first-order reverse accumulative, upper and lower bounds partition method—fractional order reverse accumulative and linear model with interval autoregression model. The technique for order of preference by similarity to the ideal solution (TOPSIS) was used to select the optimal model. The results show that the proposed model demonstrates the best performance regarding urban domestic water consumption prediction and can provide powerful decision support for addressing regional urban water consumption forecast issues in the water source sector. The proposed model also provides a new method for the prediction of urban domestic water consumption and other water consumption predictions.

The aim of this study is to develop a framework for the optimal conjunctive use of surface and groundwater in a case study of the Zayandehrud river basin in Iran. The basis of the framework is an integrated simulation-optimization model that can be used to optimize a number of decisions, including (1) the operation of a reservoir, (2) allocations of water to irrigation canals, and (3) withdrawals from the river and groundwater sources. A water evaluation and planning system (WEAP) model is coupled with the nondominated sorting genetic algorithm II (NSGA-II) optimization algorithm to optimize the following two criteria: (1) a fuzzy sustainability criterion, and (2) the normalized shortfall of supply compared to demand. Each point on the generated Pareto front corresponds to a set of releases from the reservoir and allocations from surface and groundwater resources to the various agricultural regions. A compromise solution is selected from the Pareto front using an established method. The total sustainability of the compromise solution is 26% higher than that obtained previously by using the simulation model alone. It also represents an increase in the sustainability of the reservoir by 37% and the sustainability of the aquifers by 16%.

In the long-term management of large hydropower systems, operators generally have to maximize the benefits from energy production while ensuring they satisfy a minimal energy profile throughout the year. Enhanced hydrological information can be critical to improving the operations of the system. This need encourages the use of a more complex representation of inflow series. Stochastic dual dynamic programming (SDDP) is a commonly used method for optimizing multireservoir operations of hydropower systems. Within SDDP, inflow uncertainty is usually modeled using statistical time-series models such as the family of periodic autoregressive (PAR) models, which have the required linear structure to implement SDDP. Although often used in hydrological modeling for its ability to represent long-term spatiotemporal relationships, periodic autoregressive and moving average (PARMA) has yet been little used in a SDDP framework. The additional moving average component of PARMA models over PAR models provides PARMA with a deeper memory than PAR, thanks to a more complex correlation structure. This paper compares policies generated by PARMA and PAR to manage the Manicouagan hydropower system in Quebec, Canada. The comparison is made between PAR and PARMA models of the same autoregressive order to illustrate the advantages of including the moving average component. Simulations over historical scenarios are performed and reveal that PARMA derives policies that can better manage the interannual capacity present in the system.

This paper presents an analytical algorithm for simultaneous least-cost design and operation of looped water distribution systems (WDSs). This method could be used to replace evolutionary methods (which are typically used to solve the design-operation problem), or it can be used in conjunction with evolutionary algorithms to enhance their performance (i.e., a hybrid approach). Unlike previous studies that propose analytical methods for split-pipe or continuous diameter design, the developed method addresses a more realistic case in which the pipe design is restricted to commercially available discrete diameters. The analytical approach consists of three stages. In the first stage, a reformulated linear programming (LP) method is used to find the least-cost design of a WDS for a given set of flow distribution while allowing a pipe-split in the solution. In the second stage, the equivalent pipe diameters of the split-pipe design are calculated and modified to discrete pipe diameters by applying a rounding-up strategy to the next commercially available pipe diameter. In the third stage, a nonlinear programming (NLP) method is used to find a new flow distribution that reduces the cost of the WDS operation given the design of the second stage. It is shown in this study that the results produced by the analytical method outperform the results of evolutionary methods when compared to previously published studies. Moreover, when a hybrid approach is adapted, the analytical method can be used to initialize the evolutionary algorithm to gain enhanced performance. The results of the hybrid approach fine-tune those obtained from the analytical method and demonstrate a substantial improvement when compared to a standard evolutionary algorithm initialized with a randomly generated initial population.

This technical note introduces a robust and transparent way of measuring the United States’ water infrastructure performance. The unique characteristics of the proposed Water Infrastructure Performance Index (WIPI) is that it is constructed based on public data, which consider the three components: (1) supply, (2) quality of service, and (3) utilization of the water infrastructure. A series of stakeholder workshops identified a diverse set of important attributes, such as the waterborne diseases and storm sewer overflow events. The WIPI scores track the annual performance of the US water infrastructure systems. It is anticipated that the proposed WIPI could serve as a transparent and replicable performance measurement tool that supports developing reliable investment strategies and regulations that can support economic competitiveness.

Linear and nonlinear optimization models are common in hydropower reservoir modeling to aid system operators and planners. Different modeling techniques have their advantages and shortcomings. Linear optimization models are faster but less accurate, and nonlinear models are slower with better system representation. A hybrid linear and nonlinear hydropower energy reservoir optimization (HERO) model is introduced, where a hybrid optimization model sequentially solves the overall nonlinear hydropower optimization problem first with a faster-running linear programming (LP) approximation to improve an initial solution for a nonlinear programming (NLP) solution to significantly reduce NLP iterations and run time. The hybrid model is applied to six hydropower plants of California, with capacities of 13.5 to 714 MW. LP and NLP decisions are compared, and run time benchmarks of the LP, NLP, and hybrid LP-NLP models with different numbers of decision variables are presented. The hybrid model reduces the NLP run time by 79% to 88%, depending on model size, but still requires much more run time than the LP solution. For short-term operations with good inflow and energy price forecasts, where accuracy matters more and uncertainties are modest, the hybrid LP-NLP model has advantages. For long-term hydropower planning and management with many more decision variables and greater inflow uncertainty, the LP model, with its greater speed and sensitivity analysis, or stochastic models, representing some uncertainties, will often be preferred.

Water distribution networks face a pressure-deficient condition during component failure and during the addition of fire-fighting demand. Prediction of performance of water distribution networks under pressure-deficient conditions is important for network design. The demand-driven analysis method did not have the ability to simulate the pressure-deficient network, and hence many pressure-driven analysis methods have been developed. A simplified revised method to analyze the pressure-deficient condition of water distribution networks was developed and is reported here. The revision reduces the number of artificial elements added to the demand nodes for simulating the pressure-deficient condition in a single iteration. A new resilience indicator was developed and applied to a network to demonstrate its application to pressure-deficient networks. Estimating a meaningful resilience performance was facilitated by the new indicator.