Journal of Water Resources Planning and Management 

About: Journal of Water Resources Planning and Management is an academic journal published by American Society of Civil Engineers. The journal publishes majorly in the area(s): Water resources & Water supply. It has an ISSN identifier of 0733-9496. Over the lifetime, 3043 publications have been published receiving 103224 citations. The journal is also known as: ASCE journal of water resources planning & management & American Society of Civil Engineers water resources planning and management.

Optimal Operation of Multireservoir Systems: State-of-the-Art Review

Abstract: With construction of new large-scale water storage projects on the wane in the U.S. and other developed countries, attention must focus on improving the operational effectiveness and efficiency of existing reservoir systems for maximizing the beneficial uses of these projects. Optimal coordination of the many facets of reservoir systems requires the assistance of computer modeling tools to provide information for rational management and operational decisions. The purpose of this review is to assess the state-of-the-art in optimization of reservoir system management and operations and consider future directions for additional research and application. Optimization methods designed to prevail over the high-dimensional, dynamic, nonlinear, and stochastic characteristics of reservoir systems are scrutinized, as well as extensions into multiobjective optimization. Application of heuristic programming methods using evolutionary and genetic algorithms are described, along with application of neural networks and fuzzy rule-based systems for inferring reservoir system operating rules.

Optimization of Water Distribution Network Design Using the Shuffled Frog Leaping Algorithm

Abstract: Shuffled Frog Leaping Algorithm (SFLA) is a meta-heuristic for solving discrete optimization problems. Here it is applied to determine optimal discrete pipe sizes for new pipe networks and for network expansions. SFLA is a population based, cooperative search metaphor inspired by natural memetics. The algorithm uses memetic evolution in the form of infection of ideas from one individual to another in a local search. The local search is similar in concept to particle swarm optimization. A shuffling strategy allows for the exchange of information between local searches to move toward a global optimum. This paper summarizes the development of SFLANET, a computer model that links SFLA and the hydraulic simulation software EPANET and its library functions. Application of SFLANET to literature network design problems is then described. Although the algorithm is in its initial stages of development, promising results were obtained.

Genetic Algorithms for Least-Cost Design of Water Distribution Networks

Abstract: This paper describes the development of a computer model GANET that involves the application of an area of evolutionary computing, better known as genetic algorithms, to the problem of least-cost design of water distribution networks. Genetic algorithms represent an efficient search method for nonlinear optimization problems; this method is gaining acceptance among water resources managers/planners. These algorithms share the favorable attributes of Monte Carlo techniques over local optimization methods in that they do not require linearizing assumptions nor the calculation of partial derivatives, and they avoid numerical instabilities associated with matrix inversion. In addition, their sampling is global, rather than local, thus reducing the tendency to become entrapped in local minima and avoiding dependency on a starting point. Genetic algorithms are introduced in their original form followed by different improvements that were found to be necessary for their effective implementation in the optimization of water distribution networks. An example taken from the literature illustrates the approach used for the formulation of the problem. To illustrate the capability of GANET to efficiently identify good designs, three previously published problems have been solved. This led to the discovery of inconsistencies in predictions of network performance caused by different interpretations of the widely adopted Hazen-Williams pipe flow equation in the past studies. As well as being very efficient for network optimization, GANET is also easy to use, having almost the same input requirements as hydraulic simulation models. The only additional data requirements are a few genetic algorithm parameters that take values recommended in the literature. Two network examples, one of a new network design and one of parallel network expansion, illustrate the potential of GANET as a tool for water distribution network planning and management.

Genetic algorithms compared to other techniques for pipe optimization

Abstract: The genetic algorithm technique is a relatively new optimization technique. In this paper we present a methodology for optimizing pipe networks using genetic algorithms. Unknown decision variables are coded as binary strings. We investigate a three-operator genetic algorithm comprising reproduction, crossover, and mutation. Results are compared with the techniques of complete enumeration and nonlinear programming. We apply the optimization techniques to a case study pipe network. The genetic algorithm technique finds the global optimum in relatively few evaluations compared to the size of the search space.

The New Blue and Green Water Paradigm: Breaking New Ground for Water Resources Planning and Management

Abstract: The production of biomass for direct human use—e.g., as food and timber—is by far the largest freshwater-consuming human activity on Earth. However, water policy and development concentrate on a fraction of the water for food challenge, namely, irrigated agriculture, which uses an estimated 25% of the global water used in agriculture, and on the industrial and domestic water supply, which corresponds to less than 10% of direct human water requirements considering only water for food, domestic use, and industry . The reason that biomass production so strongly outclasses other water-dependent processes is that water is one key element involved in plant growth. Simultaneous with the photosynthesis process, when stomata in the foliage open to take in carbon dioxide, large amounts of water are being consumed as transpiration flow and released as vapor from the plant canopy. Furthermore, this productive flow of vapor is accompanied by nonproductive evaporative losses of water from soil, ponded water, and intercepted water from foliage surfaces . Together, vapor fluxes as evaporation and transpiration, here defined as green-water flow, constitute the total consumptive water use in biomass production. Addressing the millennium development goal MDG of halving the proportion of malnourished people in the world by 2015, today amounting to a shocking 800 million people, is thus not only a tremendous agricultural endeavor but is also the world’s largest water-resource challenge. Hunger alleviation will require no less than a new Green revolution during the next 30 years, particularly in sub-Saharan Africa. As stated by Conway 1997 , the challenge is to achieve a green-green revolution, which compared with the first green revolution that lifted large parts of Asia out of an imminent hunger crisis in the 1960s and 1970s, will have to be founded on principles of environmental sustainability. As suggested by Falkenmark and Rockstrom 2004 , there is a third green dimension to a new agricultural revolution, since the focus will have to be on upgrading rain-fed agriculture, which entails increasing the use of the portion of rainfall that infiltrates the soil and is accessible by plants to generate vapor flow in support of biomass growth. This triply green revolution will require huge quantities of freshwater as vapor flow from the soil, through plants to the atmosphere. It raises the question of what eradicating hunger will in fact imply for water-resources planning and management.