Journal of Water Resources Planning and Management

The Midwest is the largest agricultural area of the United States. Historically, the climate there has been suitable for unirrigated farming. However, the specter of climate change has created concerns about the future of Midwestern agriculture, regional fresh water resources and the relationship between the two. Implications of climate change for the agricultural Midwest are revealed in a recent study on two typical agricultural Midwestern watersheds, the Mackinaw River Basin and the upper Sangamon River Basin of central Illinois. Generally in this study a future climate with more frequent droughts is envisioned based on the outcome of one of the major general circulation models, the Canadian Climate Centre model. The climate change impacts on agricultural productivity, low flow frequencies of streams, and the profitability of irrigation, which could be triggered by the climate change, are evaluated. This study shows that the changes in climatic factors of temperature and precipitation tend to reduce crop yields, induce irrigation, and increase low flow frequencies. However, such adverse effects may well be counteracted by the effects of elevated ${\mathrm{CO}}_2$ concentration in atmosphere. Thus, the opposing effects of climate change could very well leave agriculture in central Illinois more or less unchanged.

The total maximum daily load approach currently used by the USEPA to restore an impaired stream by allocating allowable loads to the polluters does not mandate any economic consideration. The need for a cost-effective allocation process has long been identified but no single best way to accomplish this has yet been developed. This paper describes how the most economical load allocation scenario may be determined through an optimal placement of control measures within an agricultural watershed. The proposed optimization approach is applied to the bacterially impaired Roses Creek watershed located in the Commonwealth of Virginia. The cost-effectiveness relationships were established for vegetative buffer strips, streamside fencing, pet waste management, and septic system repair and installation to illustrate the methodology. Similar relationships may be established for other control measures provided their load reduction efficiencies are known.

Many cities in water-stressed environments are seeking sustainable alternatives to traditional solutions such as supply augmentation and water restrictions. One alternative is to upgrade urban water systems in an integrated manner. Design of an integrated urban water system (IUWS) requires an understanding of the risk of the IUWS failing to deliver sustainable outcomes. We present a rationale for enhancing well-established risk assessment and management tools with concepts of ecosystem resilience. Although traditional risk assessment focuses on the states of controls that operate on specific system components and the likelihood and consequences of control failure, resilience theory addresses whole-of-system behavior. In identifying critical controls, risk management focuses on the ability to prevent failure and stabilize a certain system state, whereas resilience focuses on the “uncontrollable” to identify pathways for managing system adaptation to change. Based on conceptual analysis of two key resilience metaphors, the “stability landscape” and the “adaptive cycle,” we investigate pathways toward risk-based IUWS design and management that explicitly include system resilience as an overarching measure of sustainability. Areas for future research include development of methodologies for measuring system adaptive capacity, and identifying and quantifying emerging thresholds. The challenge for the risk assessment community is to reconsider what “risk” is: In a resilience context, events traditionally seen as risky are not necessarily bad, and may become opportunities. The challenge for the resilience community is to identify thresholds and the system’s proximity to them.

The optimization of looped water distribution networks (WDN) implies achieving the best tradeoff between reliability and cost. Many works have dealt with minimizing the cost, but few have considered both cost and reliability. This paper aims to evaluate the performance of several multiobjective metaheuristics (MOMHs) to optimize the design of looped water distribution networks, taking into consideration two objective functions: Minimizing costs and maximizing the resilience index. The MOMHs used are: Strength Pareto Evolutionary Algorithm 2 (SPEA2), Pareto Archived Evolution Strategy, Pareto Envelope-based Selection Algorithm, Pareto Simulated Annealing, and Multiobjective Simulated Annealing and Tabu Search. These algorithms are tested and compared by applying them to two case studies: The first is a small well-known benchmark network (Hanoi), whereas the second one is a larger looped irrigation network (Balerma). Results of this work show that SPEA2 outperforms the remaining methods in terms of Pareto dominance.

The preponderance of evidence in the scientific community supports the premise that global climate is changing. The precise impacts of climate change on natural and man-made systems remain less certain. Municipal water supplies, particularly those that rely on summer snowmelt to augment storage capacity, may experience significant changes in their flow regimes in the future. This paper presents an evaluation of climate change impacts on a water resource system using a three-stage modeling approach: General circulation models (GCMs) to simulate global climate, basin scale hydrology models, and water resource system simulation models. This approach is applied to two river basins in the Puget Sound Region of the Pacific Northwest: The Cedar and South Fork Tolt Rivers, which are the principal sources of water for the Seattle metropolitan region. The greatest source of uncertainty associated with climate change impacts arises from the range of future scenarios produced by GCMs. This uncertainty is addressed by incorporating multiple climate models at every stage of the process and using the values produced to generate an ensemble average that quantifies the most likely impact. The ensemble average is characterized by an envelope of uncertainty based on the range and spread of the individual GCM ensemble members. Hydrologic impacts of climate change such as alteration of historic streamflow patterns and snow accumulation are explored, as well as impacts to the water supply system’s yield.

This paper describes the development of an optimization model for the management and operation of a large-scale, multireservoir water supply distribution system with preemptive priorities. The model considers multiobjectives and hedging rules. During periods of drought, when water supply is insufficient to meet the planned demand, appropriate rationing factors are applied to reduce water supply. In this paper, a water distribution system is formulated as a network and solved by the GAMS modeling system for mathematical programming and optimization. A user-friendly interface is developed to facilitate the manipulation of data and to generate graphs and tables for decision makers. The optimization model and its interface form a decision support system (DSS), which can be used to configure a water distribution system to facilitate capacity expansion and reliability studies. Several examples are presented to demonstrate the utility and versatility of the developed DSS under different supply and demand scenarios, including applications to one of the largest water supply systems in the world, the São Paulo Metropolitan Area Water Supply Distribution System in Brazil.

Water resources management presents a large variety of multiobjective problems that require powerful optimization tools in order to fully characterize the existing trade-offs. Different optimization methods, based on mathematical programming at first and on evolutionary computation more recently, have been applied with various degrees of success. This paper explores the use of a relatively recent heuristic technique called particle swarm optimization (PSO), which has been found to perform very well in a wide spectrum of optimization problems. Many extensions of the single-objective PSO to handle multiple objectives have been proposed in the evolutionary computation literature. This paper presents an implementation of multiobjective particle swarm optimization (MOPSO) that evaluates alternative solutions based on Pareto dominance, using an external repository to store nondominated solutions, a fitness sharing approach to promote diversity, and a mutation operator to improve global search. The MOPSO solver is used on three applications: (1) test function for comparison with results of other MOPSO and other evolutionary algorithms reported in the literature; (2) multipurpose reservoir operation problem with up to four objectives; and (3) problem of selective withdrawal from a thermally stratified reservoir with three objectives. In the test function application, standard performance metrics were used to measure closeness to the true Pareto front and evenness of coverage of the nondominated set. Results for the other two applications are compared to Pareto solutions obtained using the $\epsilon$ -constraint method with nonlinear optimization ( $\epsilon$ -NLP). MOPSO performed very well when compared with other evolutionary algorithms for the test function and also provided encouraging results on the water management applications with the advantage of being much simpler than the $\epsilon$ -NLP approach.

Six water authorities share the Sefidrud watershed in the northwestern region of Iran and resolving the conflict among them is one of the major challenges of the water division of the government. In this paper a group decision support system will be developed for identifying the criteria and their weights, needed for ranking water resource projects in this watershed. This model will be based on extending the ordered weighted averaging (OWA) as an aggregation operator. The order weights of this operator will be determined first by using the minimal variability method. Second, a new measure will be developed to quantify consensus among the stakeholders. It guides the supervisor of the group decision making problem to negotiate with stakeholders effectively in the conflict resolution process. Using extended OWA, 13 water resources projects in the Sefidrud watershed will be ranked. A simulation study will also be reported, where the dependence of the optimal decision on the uncertainty level is examined. In addition, a new sensitivity analysis model will be introduced for the combined goodness measures of the projects with respect to the optimistic degree of the supervisor. A new composite measure of goodness will also be defined to obtain reliable solutions.

The stochastic modeling of water demand requires knowledge of the statistical features of the demand time series at different spatial and temporal aggregations. The observation of real data has revealed the presence of a nontrivial scaling of the second-order moments with the number of customers. The main objective of this paper is to analyze the spatial and temporal features of the demand at different spatial aggregation scales and sampled with different temporal resolutions, deriving appropriate scaling laws for the first- and second-order moments. In this context the analytical expressions of the scaling laws are first derived, pointing out the role of the space–time correlation. Then the scaling laws are empirically derived for two data sets of real indoor water demand data of two different case studies, sampled with different metering techniques. This enables the evaluation of the relevance of this effect on real data. A further analysis is carried out to understand how the sampling time affects the scaling properties of water demand. Finally some examples are reported on the use of these findings in some practical applications.

The present study investigates solute mixing phenomena at various flow rates within a cross junction, which is commonly found in municipal drinking water distribution systems. Simulations using computational fluid dynamics are employed to model the solute concentrations leaving the junction when one inlet is comprised of clean water while the other inlet carries a solute at $\mathsf{R}>\mathrm{10,000}$ . For a few exemplary cases, the resulting velocity vectors and contours of dimensionless concentration are presented to explain the detailed mixing mechanisms at the impinging interface. The turbulent Schmidt number $\left({\mathsf{Sc}}_t\right)$ , an important scaling parameter, is also evaluated. Experimental results were used to assess values of ${\mathsf{Sc}}_t$ for various flow conditions that accurately captured the detailed mixing processes within the junction. The present study clearly indicates that mixing at pipe cross junctions is far from “perfect.” Incomplete mixing results from bifurcating inlet flows that reflect off one another with minimal contact time. Improving the existing water quality model based on accurate mixing data and simulations is important not only to predict concentrations of chemical species such as chlorine in water distribution systems, but also to prepare for potential intentional and accidental contamination events.

The present experimental study focuses on the characterization of complex mixing phenomena at pipe intersections within pressurized water distribution networks. To examine the complete mixing assumption at a cross junction, a series of experiments were conducted in the turbulent regime $(\mathsf{R}>\mathrm{10,000})$ . The experimental setup consists of a cross junction with various sensors, pumps, and a data acquisition system to accurately measure solute concentration. Selected experimental results are compared to computational fluid dynamics (CFD) results. In addition, the water quality model associated with a standard water distribution network simulator (EPANET) was reevaluated based on CFD and experimental data. Corrections based on experimental results are incorporated into EPANET (AZRED 1.0) for use in a case study. The study concludes that the complete mixing assumption can potentially create considerable errors in water quality modeling. Further, severe errors are likely to occur in systems with many cross type junctions due to bifurcation of the incoming flows.

Control and design problems of water distribution systems rely on simulation models for predicting the system behavior under dynamic boundary conditions. A detailed network model may result in thousands to tens of thousands of pipelines and nodes, making the system hydraulics and water quality analysis a complicated task. In this manuscript a methodology and application of a conjunctive hydraulic and water quality model for water distribution systems aggregation is presented. The model outcome provides a reduced network with fewer nodes and links which resembles the original system performance in both the hydraulics (i.e., quantities and pressures) and water quality (i.e., concentrations) at high accuracy. The proposed methodology is demonstrated using the three example applications of EPANET.

The development of a mathematical model for chance constrained optimal design of trapezoidal channels is presented. The developed model maximizes the probability of channel capacity being greater than the design flow, and minimizes the probable cost of the channel. The developed model is demonstrated for optimal design of channels having composite and uniform roughness.

In communities where flood frequency data are unavailable, rainfall-runoff-routing models can estimate flood impacts of dam removal. We used the federal TR-20 model with PEST calibration software and NEXRAD radar rainfall data to study dam removal in the $186{\mathrm{km}}^2$ section of New York’s Onondaga Creek. The NEXRAD calibrated TR-20 simulated dam controlled flow for 100-year frequency $24\text{-}\mathrm{h}$ duration rainfall, and the predicted peak discharge of $97{\mathrm{m}}^3{\mathrm{s}}^{-1}$ was within 1% of flood frequency estimates. TR-20 predicted a peak discharge of $270{\mathrm{m}}^3{\mathrm{s}}^{-1}$ for the same 100-year, $24\text{-}\mathrm{h}$ rainfall with the dam removed, which was 4% higher than regional regression estimated peaks for an unregulated watershed. HEC river analysis system analysis of TR-20 floods showed naturalized flood peaks for events of 10 years or greater would leave the channel. This note reports on how radar rainfall and automated calibration are incorporated into TR-20 by managers and planners to enhance watershed restoration analysis.