Journal of Water Resources Planning and Management

Forum papers are thought-provoking opinion pieces or essays founded in fact, sometimes containing speculation, on a civil engineering topic of general interest and relevance to the readership of the journal. The views expressed in this Forum article do not necessarily reflect the views of ASCE or the Editorial Board of the journal.

Forum papers are thought-provoking opinion pieces or essays founded in fact, sometimes containing speculation, on a civil engineering topic of general interest and relevance to the readership of the journal. The views expressed in this Forum article do not necessarily reflect the views of ASCE or the Editorial Board of the journal.

Forum papers are thought-provoking opinion pieces or essays founded in fact, sometimes containing speculation, on a civil engineering topic of general interest and relevance to the readership of the journal. The views expressed in this Forum article do not necessarily reflect the views of ASCE or the Editorial Board of the journal.

Isolation valves are a fundamental element of water distribution systems because they provide the ability to disconnect sections of the network, which is essential to address routine maintenance and emergency conditions. In order to have a more accurate assessment of the distribution network and consider the role of valves, reliability and resilience assessment methods based on segments (i.e., the smallest set of pipes that can be isolated by the available valves in the distribution network) should be favored. This paper presents a general procedure that uses a standard EPANET network file structure to identify such segments, their elements, and unintended isolations resulting from shutdowns. This procedure is then tested on a set of real water distribution networks.

Real-time monitoring of drinking water in a water distribution system (WDS) can effectively warn of and reduce safety risks. One of the challenges is to identify the contamination source through these observed data due to the real-time, nonuniqueness, and large-scale characteristics. To address the real-time and nonuniqueness challenges, we propose an adaptive multipopulation evolutionary optimization algorithm to determine the real-time characteristics of contamination sources, where each population aims to locate and track a different global optimum. The algorithm adaptively adjusts the number of populations using a feedback learning mechanism. To effectively locate an optimal solution for a population, a coevolutionary strategy is used to identify the location and the injection profile separately. Experimental results from three WDS networks show that the proposed algorithm is competitive in comparison with three other state-of-the-art evolutionary algorithms.

In order to plan for future water resource development, estimating sustainable levels of water supply and demand is essential to ensure that available water can be used in a way that satisfies all sectors. Different indices have been used to assess the sustainability of water supply-demand within a catchment. The most important elements of water sustainability in a region are its water supply-demand, environmental, and socio-economic attributes. In this paper, an index called PI-Plus (P for Paydari as it is an indigenous term for sustainability) is extended, and its interdependencies with another index called sustainability group index are taken into account. A water balance platform is used that utilizes hydrologic cycle attributes and could be considered as a systems approach to sustainability evaluation. A hypothetical case study is selected that has the components of a real-world problem. A time series of water balance data is synthesized by utilizing basic climatic and hydrologic data from a real watershed. This could be considered as a contribution and a practical engineering solution to generate water balance data in the developing regions. PI-Plus consists of five indicators representing the estimations of gross annual available water (using the physical input-output table approach), economic efficiency of delivered water, system’s performance in the context of reliability of supply, and maintaining aquifer storage and river instream flow requirements. Furthermore, a framework for considering a new 5th indicator for social aspects is developed by employing the Nash bargaining theory. Unlike many previous studies of water-related indices, a platform is developed that can fine-tune the assessment of water system performance of different elements and components in a watershed and water cycle scale. Then, by applying uncertainty analysis, the margins of errors in estimating the indicators are determined. The results also present the extent of indicators’ improvement that could be achieved. This study could provide a basis for water balance studies and the implementation of different triggers that are socially sensitive and technically feasible to measure sustainability in the developing regions.

This paper proposes a methodology to increase the level of water distribution equity in intermittent water distribution networks (WDNs) with users equipped with private tanks. The methodology makes it possible to identify optimal valve locations and settings to improve the distribution of water among users by rearranging the flow circulation in the network. Two optimization schemes based on the use of NSGA II were developed. The first scheme aims at maximizing the global distribution equity of a WDN through installation of valves fully closed. The second scheme looks also at the levels of supply of the individual nodes of a WDN and includes optimization of both locations and settings of control valves. The two optimization schemes are applied to the case study of a WDN in northern Italy considering a scenario of water shortage. The EPA’s Storm Water Management Model software was used for the pressure-driven simulation of an intermittent WDN. Results of the application of the two optimization schemes highlight the potential for an increase in the global equity of the WDN by installation of a few valves. However, some nodes of the WDN were penalized by the new flow circulation as obtained by solutions provided by the first scheme. In fact, these nodes unacceptably worsen their condition compared to the no-valve scenario. Conversely, solutions obtained with the second scheme allowed demand satisfaction levels to not worsen compared to the no-valve scenario for all nodes.

Real-time modeling of water distribution systems (WDSs) has received much attention in WDS operation and management. As the model input, nodal water demand must be calibrated in a timely manner. However, for the large-scale WDSs, real-time calibration of nodal water demand can become very computationally expensive, as the computation complexity of the Hessian matrix inversion grows exponentially with the increasing number of nodal water demands. To address the difficulty, an efficient algorithm to calibrate the nodal water demand is developed. The algorithm can solve the Hessian matrix inversion based on the iterative Sherman–Morrison formula. By adopting parallel programming, the developed approach can efficiently shorten the computation time. The performance of the algorithm is evaluated by a set of networks with the number of nodal water demands ranging from 31 to 12,523. Results show that this approach can accurately calibrate the nodal water demand and the computation efficiency is significantly improved, especially when the number of measurements is far less than the number of nodal water demands. This approach is expected to improve modeling accuracy and computational efficiency for the real-time modeling of WDSs.

Agricultural water use is the leading cause of groundwater overdraft in California. However, agencies tasked with managing groundwater resources do not have access to accurate and reliable measurements of groundwater extraction. Previous studies identified a relationship between pump energy consumption and groundwater extraction and indicated that the efficiency lift method (ELM) can produce reliable estimates of groundwater extraction if based on reliable data. Recent advances in the availability of electricity and pump operating condition data have made the ELM viable for estimating large-scale groundwater extraction. This study considered the feasibility of using the ELM to estimate groundwater extractions from both individual wells and larger areas and identified the best data sources available for such estimates. Researchers found mean error rates of 5% at the individual well level and 3.3% for collections of wells when using the most specific data sources available, such as pump test reports and spatial groundwater level datasets. This research suggests that the ELM is a reasonable approach for estimating groundwater extraction on a large scale.

In recent years, many researchers have recognized pressure reducing valves (PRVs) as potential microhydropower (MHP) sites, aiming to improve the efficiency of water networks. Pump-as-turbines (PATs) have been pointed out as the most suitable technology because of their favorable cost. Most of the methodologies available in the literature for selection of a PAT to replace a PRV follow a traditional approach that is based on scaling aprototype data using affinity curves, thus restricting the solution space only to these curves. The optimization-based methodology presented in this paper uses the classical hydraulic regulation scheme with the Nedler–Mead simplex direct search algorithm to search for the optimal solution within space that is constrained only by the boundaries of available centrifugal PATs on the market. The methodology also defines the PAT’s operation limits based on the PAT’s relative mechanical power. Improvements gained by using the novel methodology have been demonstrated on real-world case studies from Ireland and Italy that were previously used in the literature. The results of the considered sites also suggest that the maximal global plant’s efficiency is around 80% of the maximal efficiency of the theoretically optimal PAT. The paper also examines effects of different objective functions and different PATs’ operation limits on the selection of the optimal PAT.

Because consideration of segments and valves is essential for evaluating the reliability and resilience of water distribution networks (WDNs) when shutdowns are required, a quick method of identifying critical and vulnerable segments and valves would benefit utilities. While the importance and vulnerability of segments can best be evaluated by extensive hydraulic analysis, hydraulic analyses can be time consuming. It can also be challenging to visualize the segments of a water distribution network and their associated valves. To address these limitations, this study develops a method based on graph theory to identify important and vulnerable segments without hydraulic calculations. The method generates a matrix that represents how reachable water sources are from segments when a given segment must be isolated while distinguishing between continuous water sources and ephemeral storage. This study also applies measures from graph theory to determine the number of valves to operate to isolate a segment and provides a rigorous proof to support the intuitive equation. A method to visualize the connectivity of segments with the graph-theory measures is demonstrated. The developed methods are applied to multiple valving scenarios of a case study and two real WDNs. Correlations between graph-theory based measures derived from the segment-valve topology and hydraulic simulation-based criticality are higher than in previous studies that apply graph theory to the pipe-junction topology of WDNs ($r\ge 0.6$). Results indicate that the developed methods can be used by utilities as a preliminary screening to eliminate the need for some hydraulic simulations. These findings are expected to provide decision support for utilities.

Although reclaimed water—municipal wastewater treatment plant effluent—can serve as a locally sustainable alternative water resource, this additional consumptive use of reclaimed water may cause impacts downstream. This paper seeks to quantitatively assess these impacts by employing scenario analysis coupled with a two-sample $t$-test to evaluate the statistical significance of streamflow alteration. Further, the potential for lower volumes of streamflow is linked to impacts on downstream stakeholders through the use of stakeholder performance metrics. To demonstrate the applicability of this approach, two diverse regions are evaluated: (1) the Illinois River downstream from the greater Chicago, Illinois, area, and (2) the Middle Rio Grande River downstream from Albuquerque, New Mexico. In Illinois, impacts to barge transportation are marginal and decrease with distance downstream of effluent consumption. In the Rio Grande, impacts to the Rio Grande silvery minnow worsen downstream such that a proposed consumption would be unlikely to be established under federal regulations. The extent of downstream impacts is important in legal and policy contexts regarding the sustainability of reclaimed water projects.

Failure of a buried water pipeline can have an adverse effect on neighboring infrastructure, especially road networks. The impact of the failure of water pipelines on road networks and water distribution systems (WDSs) significantly increases the economic and social consequences of such failure. This paper presents a risk-informed decision support framework for WDSs considering the risk and the criticality of components to aid maintenance prioritization. The probability of water pipe failure is estimated using a physical probabilistic approach. The economic, operational, environmental, and social consequences of the failure of the integrated water and road segments are evaluated using 14 factors. The economic, operational, environmental, and social consequences are combined using fuzzy hierarchical inference to determine the overall consequence of the failure of each integrated segment (road and water network sharing the same geographical space). The risk of assets is determined by utilizing two approaches: risk equation and risk matrix. A shortest path–based network efficiency metric is then used to identify the impact of the failure of water pipelines on both infrastructure systems. The final decision alternatives are prepared by combining the outputs from the risk analysis and the network efficiency metric to prioritize maintenance tasks. A geospatial model is used to identify dependent road and collocated water segments sharing the same geographical space. The water and road networks of the Rancho Solano Zone III area of the city of Fairfield, California, are used to illustrate the proposed framework. The results show that the failure of a critical segment can have a significant impact on the efficiency of both networks. In the considered case study, the failure of a critical segment can result in about 7.5% and 9.6% system efficiency loss in the water and road networks, respectively. The proposed model is expected to assist in integrated municipal asset management decision-making.

Water demands are the main random factor that conditions flow variability within drinking water supply systems. The importance of using high-resolution demands in distribution mains is already well known, but there is little knowledge of how the temporal scale (i.e., sampling frequency) affects the ability of a metering or monitoring system to explain network performance. The aim of this paper is to analyze the variability (i.e., information) that is lost because of not using a more frequent sampling rate to characterize water demands. For such purpose, a novel analytical approach based on a conceptualization of the microcomponent-based model SIMDEUM, which stands for SIMulation of water Demand, an End-Use Model, is presented. This methodology provides the statistical properties of water demands over different sampling frequencies. It is here applied to the Benthuizen case study (Netherlands) to further explore the effect of temporal and spatial scaling laws under realistic conditions. Results are of major importance for monitoring design because they highlight the need for properly combining measurements with different levels of resolution. Moreover, they enable assessment of the impact of the sampling selection on the potential characterization level of monitored demands within urban water modeling applications.

This technical note presents a technique for the pressure-driven analysis (PDA) of water distribution networks with flow- and pressure-regulating valves. The technique is a combination of a PDA method based on adding artificial components (a pipe with a check valve, a flow control valve, and an emitter) to each demand node and a hybrid simulator that models valves as pipes of variable resistance in cases where the EPANET 2.0 valve treatment heuristics fails. The examples considered demonstrate that the proposed PDA technique may be an alternative to EPANET 2.2, the latest version of EPANET 2.0 with a PDA option, in cases where the latter is not applicable or fails to compute the correct solution.