Journal of Water Resources Planning and Management

State estimation (SE) techniques are being applied to different network systems in order to convert system measurements into real information about the network state. SE applications to water systems are relatively novel, but these techniques have been implemented in other fields for decades. In those applications, observability analysis (OA) is required prior to application of SE techniques with different purposes: (1) to identify redundant information, (2) to detect elements that make no contribution in the subsequent SE process, or (3) to identify observable islands. However, no discussion has been found in the pertinent literature regarding any interest in applying OA to water networks, with there being only a few basic applications. The aim of this paper is twofold: first, to present the implementation of a novel algebraic OA approach to water networks, which is based on the application of a Gauss elimination technique to the measurement Jacobian matrix, and to discuss and justify the interesting aspects of implementing an OA in water transport networks (WTN) prior to using SE while also presenting the issues that this technique may resolve. The results obtained highlight the algorithm potential for real supply systems, improving the knowledge of what information provided by supervisory control and data acquisition (SCADA) systems is really worth compiling.

This paper considers the operation of hydro plants, tackles the problem of daily hydro-generation scheduling (DHGS), and obtains the optimal hourly operation of cascade hydropower reservoirs. To meet the practical operational demands of power grid, an improved benefit-maximization model in which the peak shaving demands are taken as constraints is proposed for DHGS, and the joint peak load regulation (JPLR) method is applied to the proposed model. The model can enhance the power-generation efficiency and reduce the water spillage significantly under the condition of peak load regulation. Meanwhile, a hybrid method that combines discrete differential dynamic programming with progressive optimality algorithm is proposed to solve the JPLR problem. The complicated constraints can be handled by the proposed algorithm effectively. Moreover, the hydro-unit-commitment problem is solved by a rapid searching algorithm based on equal incremental principle and empirical methods. With this unit-commitment strategy, the computation speed can be accelerated and approximate optimal solutions can be obtained in a reasonable time frame. The proposed model and methods are applied to the DHGS of cascade hydro plants in Zagunao River in China and achieve good performance.

Partial blockages are commonly formed in water supply pipelines due to many factors, such as deposition, biofilm, and corrosion in the natural water supply process, as well as valve throttle in the artificial construction and operation process, which may cause additional energy losses and serious water supply accidents in the system. Recently, a transient-based frequency domain method (TBFDM) has been developed by the author for extended partial blockage detection, and it was found to be efficient, nonintrusive, and inexpensive to apply. While this method has been validated and applied for numerical and laboratory experiments in previous studies for a variety of blockage and hydraulic conditions, the application results revealed that the accuracy of the TBFDM may be easily affected by uncertainties in the experimental process. This paper investigates the sensitivity of the developed TBFDM to different uncertainty factors that commonly exist in water pipeline systems, with perspective to better understand and use this efficient and economic method in practice. The methods of first-order second-moment analysis and Monte Carlo simulation are adopted in this paper for the investigation. The obtained results are discussed for the validity range and limitations of current TBFDM for practical applications.

In the event of contamination in a water distribution network (WDN), source identification (SI) methods that analyze sensor data can be used to identify the source location(s). Knowledge of the source location and characteristics are important to inform contamination control and cleanup operations. Various SI strategies that have been developed by researchers differ in their underlying assumptions and solution techniques. The following manuscript presents a systematic procedure for testing and evaluating SI methods. The performance of these SI methods is affected by various factors including the size of WDN model, measurement error, modeling error, time and number of contaminant injections, and time and number of measurements. This paper includes test cases that vary these factors and evaluates three SI methods on the basis of accuracy and specificity. The tests are used to review and compare these different SI methods, highlighting their strengths in handling various identification scenarios. These SI methods and a testing framework that includes the test cases and analysis tools presented in this paper have been integrated into EPA’s Water Security Toolkit (WST), a suite of software tools to help researchers and others in the water industry evaluate and plan various response strategies in case of a contamination incident. Finally, a set of recommendations are made for users to consider when working with different categories of SI methods.

Harvested stormwater is now being considered as an alternative water source in a number of cities because of concerns over water scarcity and population growth. However, the availability of this source varies as a result seasonality and climate change. This paper introduces an approach for optimizing the design of a stormwater harvesting scheme including aquifer storage and recovery that explicitly takes into account future climate change and its impact on the optimal design of the scheme. The proposed approach also accounts for the externalities associated with the use of harvested stormwater. The approach is applied to a specific case study in South Australia, considering four possible climate scenarios for planning horizons of 2030 and 2050 and the additional benefits of reducing withdrawals from the river source and the salinity of the water supplied. Results show that climate change will reduce the yield and the net present value (NPV) of the optimal stormwater scheme. They also indicate that there is a trade-off between the average NPV and the variation of the NPV across the different climate scenarios: smaller basins and a smaller wetland are selected to maximize the average NPV, while, to minimize the range of the NPV values, larger harvesting basins and smaller wetlands are implemented. For the case study, the externalities considered have a small impact on the overall cost-effectiveness of the solutions.

The current paper aims at the establishment and validation of reference cost functions for different types of assets of water supply systems based on known hydraulic (e.g., flow, pump head, pump power) and physical (e.g., volume, material, nominal pressure, diameter) characteristics of the assets. A five-step methodology was followed: (1) database construction and asset characterization; (2) present cost value calculation; (3) key parameters and cost function establishment; (4) model specification; and (5) model testing and validation. A sample of cost and infrastructure data from several Portuguese water utilities has been used. Multiple linear regression analysis has been carried out to obtain cost functions. Cost modeling also includes the estimation of prediction bands to describe cost uncertainty. Developed cost functions have been tested and validated using 10% of randomly selected data.

Components of a water resource system (WRS) can be assessed and evaluated by employing simulation and optimization techniques. In general, simulation models are used to evaluate the behavior and function of systems under existing conditions. This paper presents a generic formulation for simulating reservoir systems at the watershed scale. The formulation is based on the continuity equation and can be used for every type of simulation or optimization problem that addresses reservoir systems by considering existing priorities of resource allocation and demand supply. The developed formulation can simulate reservoir systems using both operation policies, the standard operation policy (SOP) and a rule curve. Also, different outlets with their elevation can be considered in each reservoir for water release to supply various objectives. The concept of integrated management has been used in this formulation so that the effects of different system factors on each other, including various resources and consumptions, are considered in the reservoir system simulation. The developed formulation is applied in a two-reservoir system, producing results that are logical and acceptable.

Hydraulic analysis schemes for water distribution networks can be divided into demand-driven analysis (DDA) and pressure-driven analysis (PDA) according to the ways of calculating available outflow at nodes based on the assumption of nodal withdrawal estimation. Gradient algorithm-based numerical analysis schemes are generally used for these two types of hydraulic analysis. However, in abnormal conditions where hydraulic conditions rapidly change due to pipe damages or sudden increases in demands, the numerical solutions often derive unrealistic results that could lead to decision-making errors. In this study, the problems that may occur in hydraulic analysis of abnormal conditions were identified through sample cases using DDA and PDA models; then, the modification techniques resolving the simulation problems, the negative pressure in DDA and the total head reverse in PDA, were suggested. The proposed methods were verified by applying them to sample case study simulations. The application results reveal that the proposed approaches derive more realistic results under abnormal conditions, while the existing DDA and PDA tools produce unacceptable results, such as negative pressure and total head reverse occurrence. The scheme is further investigated for water network reliability evaluations and realistic ranges of demand supply under abnormal conditions were obtained.

Aided by the rapid development of multiple geospatial data sets for topography, hydrology, and existing energy-water infrastructures, reconnaissance-level hydropower resource assessment can now be conducted using geospatial models in all regions of the United States. The updated techniques can be used to estimate the total undeveloped hydropower potential across all regions, and they may eventually help to identify additional hydropower resources that were previously overlooked. To enhance the characterization of higher power–density stream reaches, this paper explored how the degree of geospatial resolution affects the identification of hydropower stream reaches, using the geospatial merit matrix–based hydropower resource assessment (GMM-HRA) model. GMM-HRA model simulation was conducted at eight different spatial resolutions on six USGS eight-digit hydrologic units with terrains classified as flat, mild, and steep. The results showed that more hydropower potential from higher power–density stream reaches can be identified with increasing spatial resolution. Both flat and mild terrains exhibited lower impacts from resolution differences than did the steep terrain. The findings indicate that greater care should be taken in selecting the discretization resolution for hydropower resource assessments in future studies.