Journal of Water Resources Planning and Management

The delivery of large quantities of turbidity-causing particles over relatively brief intervals of high stream flow and the complexity of the resulting turbidity ($T_n$) patterns imparted to receiving lakes and reservoirs requires the use of innovative technologies to fully resolve both the driving signals and the resulting signatures in the receiving waters. The design and implementation of a robotic monitoring network to address the problem of high $T_n$ events in reservoirs of New York City’s multireservoir unfiltered water supply are described. The evolution of the role of these technologies in supporting management of the system related to the $T_n$ issue is described, including (1) resolution of cause and effect relationships between tributary inputs and in-reservoir patterns; (2) insights into mediating processes; and (3) critical support for the development, testing, and application of mechanistic mathematical models. The contemporary robotic monitoring network of eleven tributary and reservoir deployments continues to support management deliberations of alternatives to minimize the effect of major runoff events as they occur. These data streams are being integrated into a forthcoming near-real-time decision support tool that will provide automated guidance in the context of multiple factors and objectives for this complex water supply.

Accurate and up-to-date peak demand data are essential to ensure that future mains water supply networks reflect current usage patterns and are designed efficiently from an engineering, environmental, and economic perspective. The aim of this paper was to identify the water end-uses that drive peak day demand and to examine their associated hourly diurnal demand patterns based on over 18 months of water consumption data obtained from high-resolution smart meters installed in 230 residential properties across South East Queensland, Australia. Peak day (PD) to average day (AD) ratios between 1 and 1.5 were driven by both external and internal end-uses. However, as the PD:AD ratio increased above 1.5, demand was driven largely by external water usage (i.e., lawn and garden irrigation). Peak hour ratios (i.e., PHPD:PHAD) ranged from 1.3 to 3.0 for the four peak demand days. At the end-use level, the individual end-use category PHPD:PHAD ratios were in the range of 0.7–3.3 for all end-uses, with the exception of external or irrigation. The ratio for this latter end-use category was typically very high, at over 10 times the average irrigation demand. Comparisons with historically based, but currently used, peaking factors used for network distribution modeling suggest that the degree and frequency of high peaking factors are lower now, due to the high penetration of water-efficient technology and growing water conservation awareness by consumers.

The Battle of the Water Networks II (BWN-II) is the latest of a series of competitions related to the design and operation of water distribution systems (WDSs) undertaken within the Water Distribution Systems Analysis (WDSA) Symposium series. The BWN-II problem specification involved a broadly defined design and operation problem for an existing network that has to be upgraded for increased future demands, and the addition of a new development area. The design decisions involved addition of new and parallel pipes, storage, operational controls for pumps and valves, and sizing of backup power supply. Design criteria involved hydraulic, water quality, reliability, and environmental performance measures. Fourteen teams participated in the Battle and presented their results at the 14th Water Distribution Systems Analysis conference in Adelaide, Australia, September 2012. This paper summarizes the approaches used by the participants and the results they obtained. Given the complexity of the BWN-II problem and the innovative methods required to deal with the multiobjective, high dimensional and computationally demanding nature of the problem, this paper represents a snap-shot of state of the art methods for the design and operation of water distribution systems. A general finding of this paper is that there is benefit in using a combination of heuristic engineering experience and sophisticated optimization algorithms when tackling complex real-world water distribution system design problems.

A multiobjective model with chance constraints is proposed to obtain hedging rules for hydropower reservoirs based on initial reservoir operating rules derived using stochastic dynamic programming. In the model, hedging rules are evaluated through simulations and the maximizations of minimum powers in simulation horizon of hydropower reservoirs are taken as objectives. The maximum-minimum objectives are substituted by aggregated functions. A genetic algorithm is used to solve the model, with a fuzzy optimal method evaluating the individuals. A case study shows that the proposed approach is feasible and efficient to produce a series of hedging rules with different reliability levels, and valuable to balance the magnitudes of generation below firm power and the chances of such events.

Land use changes driven by urban development impose immediate threats to watershed health and sustainability of water resources. Municipalities can implement various land use controls to direct future urban development that has long lasting impacts on water resources. Hydrologically sensitive areas (HSAs) are the areas in landscapes that most actively contribute to runoff generation. This study establishes the connection between land use controls at a municipal level and protection of healthy watersheds through the concept of HSAs and assesses the effectiveness of five land use controls in protecting HSAs from future urban development in three selected municipalities in New Jersey. The five land use controls are steep slope ordinance, stream corridor ordinance, open space and farmland preservation, and wetlands protection. The results indicate the five land use controls protect 44–64% of municipal HSAs, which are only about 22–26% of the total area protected from urban development by those land use controls. The stream corridor ordinance is the most areally extensive, but wetlands protection is the most effective land use control in protecting HSAs in the three municipalities. These land use controls have significant potential to protect HSAs if additional protection criteria are incorporated into their implementation. The assessment provides practical guidance to land use planners and water resource managers who manage landscapes for water resource protection and environmental quality improvement.

A novel approach on quantifying the value of an incremental surface water–use permit in an integrated water resources system consisting of groundwater, surface water, off-stream reservoir, and desalinated seawater sources is presented. First, a stochastic framework that accounts for demand uncertainties and variations in climatic parameters was used to generate regional demand and supply realizations. Second, a linked optimization-simulation model was used to navigate through complex system constraints and sustainable operational constraints. The resulting decision variables were then used to calculate system performance metrics, demonstrating the benefit of an increase in surface-water withdrawals at high flows. The Monte Carlo–based model took advantage of distributed computing capabilities on a private cloud computing system to significantly reduce the total run time. The model codes were developed in two different software environments, executed on different platforms, in which information was exchanged through an inter-process communication (IPC) protocol. The major contribution of this research is toward the practical use of stochastic-based integrated surface/groundwater–use permit application for a complex water resources system. The approach is demonstrated using Tampa Bay Water’s integrated water resources system.

Most of the energy consumed by a water company is used to operate pumping systems. Identifying the optimal schedule for such systems in near real time will drastically reduce energy costs. The pump scheduling problem comprises three main elements: the pumping system, the tank, and the water demand to be satisfied. In this paper, a mathematical programming model and techniques used to solve this problem are presented. This study analyzed a parallel programming paradigm to solve this problem by introducing stochastic programming techniques (scenario tree evaluation) and multisite problems. Numerical experiments were designed and completed on parallel computers combining classical mathematical programming techniques and parallel tools. As a result, the parallel programming strategy was experimentally proven to be a useful technique for near-real-time pump scheduling applications.