Journal of Water Resources Planning and Management

This study present an efficient graph-theoretical method for automatic design of district metered areas (DMAs) in water distribution networks (WDNs). The proposed method consists of two main parts, WDN partitioning and DMA connection, and is tested on a real-life WDN for which three spectral partitioning methods, multiple weight cases, and two clustering criteria are compared. The efficiency of the proposed DMA connection algorithm with respect to the traditional combinatorial approach is shown for different numbers of established DMAs. The final solution is selected according to a multicriteria evaluation model, which was developed in order to reduce the subjective influence in the selection process and considers hydraulic, cost, and topological criteria. The results show that all three tested spectral partitioning methods, i.e., the ratio cut, normalized cut, and newly proposed generalized normalized cut, are suitable for WDN partitioning and that the quality of the obtained solutions can be further improved by considering appropriate topological and cost-based WDN information in the partitioning process.

This paper addresses leak detection in the presence of measurement noise using the inverse transient method (ITM). The unknown leak parameters are determined by optimizing a merit function, which fits the numerically modeled pressures to measurements. Traditionally, the fitting is accomplished by a least-square (LS) objective function that minimizes the L2 distance between the model and data. However, in practical problems where the environment is noisy, the minimum L2 distance may result in some fictitious leaks. This paper proposes an alternative objective function, known as matched-filter (MF) in the literature, which is expected to produce a more robust localization in a noisy environment because it maximizes the signal-to-noise ratio (SNR). This function is then compared with the conventional LS approach by assessment of leak-detection accuracy. It was proved that the MF estimator has smaller mean square error of leak localization than LS when signals have high noise level ($\mathrm{SNR}\le 3\mathrm{dB}$). For a low noise level, the two estimators converge to the same results. The conclusions were supported by numerical and experimental case studies.

The integration of large-scale uncontrollable renewable power greatly affects the security and reliability of power system operations. An effective way of coping with this challenge is to employ traditional dispatchable generation to buffer the uncontrollable power. This study focuses on the coordinated operation of a hydro-wind-solar system. The Yunnan power grid with 62.4 GW hydropower capacity and 10.8 GW wind and solar power capacity is selected as an example. A methodology for the generation scheduling of a hydrodominated provincial system with large-scale wind and solar power is developed. This methodology introduces additional positive reserve, negative reserve, and ramping response constraints to handle the forecast errors of wind and solar power. Moreover, the methodology merges renewable power into the original loads to determine an equivalent load curve for hydropower plants. An optimization model with a peak-shaving objective is formulated and solved by a two-phase approach. The first phase uses knowledge rules to check and adjust the generation schedules of hydropower plants with predetermined schedules or dispatching modes. The second phase presents a multidimensional search method to optimize other major plants to respond to peak loads. The methodology is demonstrated by day-ahead scheduling of the given provincial system, which includes 397 plants. The obtained generation schedules provide a reasonable reserve capacity for buffering wind and solar power fluctuations and meet the peak demands of the power grid. A detailed sensitivity analysis for different dates is presented to illustrate the seasonal characteristics of renewable power.

The “curse of dimensionality” is the main problem in flood control in multireservoir systems. This paper proposes a novel method of alleviating the “curse of dimensionality” by reducing the number of reservoirs for flood control joint operation. First, a criteria system for identifying effective reservoirs is established. Then an intelligent reasoning method is proposed to identify effective reservoirs according to dynamic information on the flood control situation. Finally, a multireservoir real-time flood control hybrid operation (MRFCHO) model is established dynamically and adaptively, in which the effective reservoirs are operated jointly and the noneffective reservoirs are operated separately. The proposed method is applied to a multireservoir system consisting of 14 reservoirs in the Huaihe River basin in China. The results show that the proposed method can identify effective reservoirs accurately in different flood control situations. The number of reservoirs for joint operation is lower than 50% of the total number of reservoirs under the premise of ensuring similar flood control effects, which reduces the dimensionality of the model and the complexity of decision making.

A methodology for determining system operation resilience is presented for the real-time operation of water distribution systems (WDS) under critical conditions of limited water or electrical energy resulting from extreme drought or electric grid failure. Resilience for water distribution systems is defined as how quickly the WDS recovers or bounces back from emergency to normal operations. The algorithm for operational resilience was interfaced with an optimization–simulation model for the real-time optimal operation of water distribution systems. The resilience methodology considered both demand and water quality requirements of both the municipal WDS and the power plant cooling systems. The optimization–simulation modeling approach interfaced a genetic algorithm optimization procedure with the WDS hydraulic and water quality simulator (EPANET) in the framework of an optimal control problem. The interfacing of the genetic algorithm in MATLAB and the EPANET model was implemented using a MATLAB–EPANET toolkit. An example WDS including two cities, five power plants, and reclaimed water from a wastewater treatment plant was used to demonstrate the application of system operation resilience concepts to assess the performance. The resilience computation methodology presented in this study is applicable to both short-term and long-term failures of WDS. For the purposes of this study, the methodology was applied to three scenarios of short-term (2–6 h) power outages for the example WDS. A sensitivity analysis was performed for resilience of example WDSs under varying degrees of long-term system-level power and water shortages. Applications of the methodology are used to illustrate improved operation resilience of the system.

This paper presents a novel methodology for optimizing simultaneously the installation of control valves and the creation of district metered areas (DMAs) in water distribution networks (WDNs). This methodology was developed through the multiobjective approach, by considering, as decisional variables, the sites for control valve installation and isolation valve closure. The proposed algorithm is based on the hybrid combination of three algorithms, a multiobjective genetic algorithm, which is entrusted with valve site search, and two embedded algorithms, the first based on iterated linear programming (LP) and the second based on graph theory, aimed at searching for the optimal settings of control valves and at partitioning the WDN into DMAs, respectively. The hybrid algorithm attempts to find optimal solutions in the trade-off between the following objective functions to be optimized simultaneously: total installation cost, daily leakage volume, and demand uniformity across DMAs. The applications to a small Lebanese WDN proved that the methodology can find, especially for high values of the total installation cost, effective control valve installations, and isolation valve closures in terms of leakage abatement while obtaining a uniform distribution of demands across DMAs.

Deficit irrigation, or the deliberate underirrigation of a crop, is a way to save farm water and allocate it to uses such as municipal, industrial, or agricultural expansion. Research on this practice has focused on profitability, but with conflicting results. The feasibility of deficit irrigation involves more than economic concerns, and agronomic and legal aspects are also important in improving farm operations. The feasibility of deficit irrigation depends to a large extent on context, and a case involving the water law system of the State of Colorado in the western United States was examined to provide a real-world instance to study the institutional and technical challenges of implementing it. Colorado has experienced extensive transfers from agriculture to urban areas and is interested in employing deficit irrigation to free more irrigation water for use in the future. Based on the results, the paper suggests practical methods for implementation of deficit irrigation in Colorado, with possible implications for similar regions with irrigated agriculture.

Stormwater green infrastructure (GI) practices are implemented in urban watersheds to control stormwater runoff, reduce pollution, and adapt to climate change. This study evaluated the robustness of a watershed with stormwater GI and a watershed with traditional stormwater controls in Clarksburg, Maryland, to future climate change. The USDA Soil and Water Assessment Tool (SWAT) was calibrated to USGS daily streamflow data from 2011 to 2016 to evaluate watershed-scale daily and seasonal runoff responses to multiple future climate and management scenarios. The stormwater GI watershed had less runoff than the traditional management watershed in climate change scenarios for most days with rainfall ($>98\%$ of days). However, the climate change scenarios resulted in increased seasonal fall and winter runoff compared to current conditions in both watersheds. Simulated expansion of GI implementation reduced runoff in both watersheds under future climate scenarios. This study assesses climate robustness of existing stormwater GI at a watershed scale and confirms previous evaluations of hypothetical stormwater GI effectiveness for adapting watersheds to climate change.

Managing stormwater continues to be a priority for many urban regions across the United States due to environmental and public health regulations. At the same time, stormwater is becoming increasingly important as a potential source of local water supply in semiarid regions. In these drier climates, urban stormwater runoff often provides base flow in urban streams. In its raw form, this can be an environmental health hazard but also can provide beneficial uses (e.g., aquatic ecology, recreation, and irrigation water) once treated. The goal of the current work is to understand how implementing stormwater best management practices (BMP) to achieve water quality compliance standards affects the flow regime of an urban river. The Los Angeles River (LAR) is used as a case study because it represents a highly urbanized, semiarid system where engineered infrastructure defines the drainage system and compliance with federal water quality standards is a widespread issue. The US Environmental Protection Agency’s system for urban stormwater treatment and analysis integration (SUSTAIN) model with a stormwater management model (SWMM) hydrologic core is used to simulate scenarios of low-impact development (LID) BMPs to meet compliance. Results show that in order to meet requirements for metals in the LAR using BMPs, the following impacts on streamflow may result when utilizing LID BMPs: a reduction in dry-weather flows by about 45%, a reduction in peak flows by 10%–25% compared with recent historical values, and changes in the seasonal flow distribution. These findings have direct policy implications for optimizing beneficial uses of the LAR while meeting water quality standards necessary for public health.

This technical note presents a hybrid simulator designed for water distribution networks with control valves. The simulator is a modification of EPANET 2 that can handle valves using both the EPANET 2 heuristics and a recently proposed alternative method that models valves as pipes whose resistance is adjusted to meet the valve setting. The method copes with cases where the EPANET 2 heuristics fails, but it requires a larger number of iterations. The hybrid simulator starts with running the EPANET 2 heuristics and switches to the alternative method only if the former fails (cannot find a solution or produces incorrect results), thus using to advantage the fast convergence of the EPANET 2 heuristics and the more stable yet slower convergence of the alternative method. Verification tests demonstrated the ability of the hybrid simulator to deal with ill-posed problems and large networks with thousands of nodes, pipes, and valves.