Journal of Water Resources Planning and Management

Water allocation under conditions of water scarcity is a looming issue that threatens the economic well being and quality of life of many of the world’s people. Although the causes of water scarcity are varied, many assert the inefficiencies and failures of water allocation by the public sector are to blame. One solution offered by proponents is to privatize the water allocation process, thereby allowing the efficiencies of the market place to resolve most issues. The thesis of this paper is that while privatization of many aspects of the water allocation process may bring increased efficiencies, certain core functions must remain with the public sector. These core functions include the ultimate decision making authority over the assignment of water rights as well as oversight authority to protect and secure both the rights of third parties and those private and public activities and values that may depend on existing uses. While the legal right to the use of water may be placed in the hands of the private sector, these rights must be closely controlled and managed by public institutions.

The work presented in the paper intends to solve the problem of analyzing a looped network taking into account the expected peak flows in the links. Usually, models are based on averaged demands based on the customers’ billings. In some cases, demands are corrected with global peak coefficients. The writers propose a new approach for analyzing water supply networks under peak demand situations. This method is based on individual peak coefficients for each link. After that, a new method for demand load allocation is described in order to satisfy the continuity equation in nodes. The procedure is iterative and was implemented using the hydraulic solver used by EPANET. Two case studies complete the paper. The first case study consists of a very simple network and allows one to describe the method. The second one is a small, real network and demonstrates the applicability to bigger networks.

Optimal sewer design aims to find cost-effective solutions for designing sewer networks, and genetic algorithms (GAs) are one of the state-of-the-art optimization techniques that have been applied to this problem. However, finding good quality solutions by using a GA can be prohibitively time consuming, especially when designing large networks. This paper introduces an efficient and robust hybrid optimization method, which deals with the design task in a multiobjective optimization manner using two consecutive stages. A localized approach based on cellular automata principles is applied at the first stage to obtain a set of preliminary solutions, which are then used to seed a multiobjective genetic algorithm (MOGA) at the second stage. Two large real sewer networks are tested for case studies. Results clearly show that the hybrid approach can surpass the standard MOGA in terms of optimization efficiency and quality of solutions.

The problem of deploying sensors in a large water distribution network is considered, in order to detect the malicious introduction of contaminants. It is shown that a large class of realistic objective functions—such as reduction of detection time and the population protected from consuming contaminated water—exhibits an important diminishing returns effect called submodularity. The submodularity of these objectives is exploited in order to design efficient placement algorithms with provable performance guarantees. The algorithms presented in this paper do not rely on mixed integer programming, and scale well to networks of arbitrary size. The problem instances considered in the approach presented in this paper are orders of magnitude (a factor of 72) larger than the largest problems solved in the literature. It is shown how the method presented here can be extended to multicriteria optimization, selecting placements robust to sensor failures and optimizing minimax criteria. Extensive empirical evidence on the effectiveness of the method presented in this paper on two benchmark distribution networks, and an actual drinking water distribution system of greater than 21,000 nodes, is presented.

Planned (e.g., regular maintenance) and unplanned (e.g. pipe burst) interruptions occur regularly in water distribution systems leading to their reduced performance. This paper presents an extended period simulation model capable of assessing system’s performance under these conditions. The extended period simulation model is based on the recently developed steady-state pressure driven hydraulic model and is capable of calculating pressures, flows, and hence actual water demands delivered under modified network topology conditions (caused by the use of isolation valves). The model is accompanied by several reliability indicators which can be used to assess system’s performance under interruptions. The above-mentioned methodology is demonstrated on a real-life case study in Italy. The role of isolation valve design and uncertainty in valve operability is analyzed and discussed. The case study results obtained demonstrate that the least cost design/rehabilitation of water distribution systems is likely to result in unreliable systems if the actual network configurations obtained by closing isolation valves in abnormal working conditions are not taken into account.

Optimization for water resources management typically requires many simplifying assumptions about the definition and characteristics of the policy or design application in order to express decision makers’ criteria as mathematical objectives and constraints. However, real-world applications often involve important subjective information that cannot be reflected in mathematical expressions accurately or completely. This can result in mathematically optimized solutions that are less meaningful or desirable to decision makers. To address this issue, this paper presents the standard interactive genetic algorithm (SIGA) methodology that enables human decision makers to effectively analyze subjective information that is not easily quantifiable and make decisions about the quality of a design based on their preferences. These decisions are used as continuous run-time subjective feedback, along with the mathematically defined objectives and constraints, to search for optimal designs that reflect both quantitative and qualitative objectives. Although this interactive optimization methodology is applicable for any water resources planning and management problems, this paper focuses on exploring the benefits of such an approach within the domain of groundwater monitoring design. Systematic procedures and guidelines for designing a SIGA are presented, along with proposed strategies for improving the performance of SIGA. The SIGA approach is also compared with a noninteractive genetic algorithm strategy for a real-world application, and the advantages and limitations of the interactive strategy are examined.

Municipal storage tanks are used to balance differences in supply and demand. Tanks have traditionally been sized based on deterministic criteria for balancing, fire, and emergency storage components. In this paper a stochastic analysis method is proposed to model both the deterministic and probabilistic components of consumer demand, fire demand, and pipe failures in water distribution systems. The method estimates a number of tank reliability criteria as functions of tank capacity, which provide a site-specific way of determining the required tank capacity based on user-defined reliability criteria. The method is illustrated by applying it to a “typical” water supply system. It was found that the tank failure duration follows a Weibull distribution. The tank failure rate was found to be very sensitive to tank capacity and can be described with an exponential distribution. It is proposed that one failure in $10\text{years}$ under seasonal peak conditions is used as a design criterion for tank sizing. In many cases this will result in substantially smaller tanks than is currently specified by design guidelines.

Following the events of September 11, 2001, in the United States, world public awareness for possible terrorist attacks on water supply systems has increased dramatically. Among the different threats for a water distribution system, the most difficult to address is a deliberate chemical or biological contaminant injection, due to both the uncertainty of the type of injected contaminant and its consequences, and the uncertainty of the time and location of the injection. An online contaminant monitoring system is considered as a major opportunity to protect against the impacts of a deliberate contaminant intrusion. However, although optimization models and solution algorithms have been developed for locating sensors, little is known about how these design algorithms compare to the efforts of human designers, and thus, the advantages they propose for practical design of sensor networks. To explore these issues, the Battle of the Water Sensor Networks (BWSN) was undertaken as part of the 8th Annual Water Distribution Systems Analysis Symposium, Cincinnati, Ohio, August 27–29, 2006. This paper summarizes the outcome of the BWSN effort and suggests future directions for water sensor networks research and implementation.