Evolutionary multiobjective optimization in water resources: The past, present, and future

Reed, Patrick M.; Hadka, David; Herman, Jonathan D.; Kasprzyk, J. R.; Kollat, Joshua B.

doi:10.1016/j.advwatres.2012.01.005

Cited by 449 publications

(296 citation statements)

References 59 publications

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“…Since we were not able to interact with the real decision makers involved in the problem, the weights were selected to ensure that the shape of the front was reasonably represented. Alternative methods exist for effectively dealing with many objective problems, including the Borg multiobjective evolutionary algorithm [Hadka and Reed, 2012;Reed et al, 2013].…”

Section: Resultsmentioning

confidence: 99%

Assessing the value of cooperation and information exchange in large water resources systems by agent‐based optimization

Giuliani

Castelletti

2013

Water Resources Research

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[1] Many large-scale water resources systems, especially in transboundary contexts, are characterized by the presence of several and conflicting interests and managed by multiple, institutionally independent decision makers. These systems are often studied adopting a centralized approach based on the assumption of full cooperation and information exchange among the involved parties. Such a perspective is conceptually interesting to quantify the best achievable performance but might have little practical impact given the real political and institutional setting. In this work, we propose a novel decision-analytic framework based on multiagent systems to model and analyze different levels of cooperation and information exchange among multiple decision makers. The Zambezi River basin is used as a case study. According to the proposed agent-based optimization approach, each agent represents a decision maker, whose decisions are defined by an explicit optimization problem considering only the agent's local interests. The economic value of information exchange is estimated comparing a noncooperative setting, where agents act independently, with the first basic level of cooperation, i.e., coordination, characterized by full information exchange. The economic value of cooperation is also estimated by comparison with the ideal, fully cooperative management of the system. Results show that coordination, obtained with complete information exchange, allows the downstream agents to better adapt to the upstream behaviors. The impact of information exchange depends on the objective considered, and we show coordination to be particularly beneficial to environmental interests.Citation: Giuliani, M., and A. Castelletti (2013), Assessing the value of cooperation and information exchange in large water resources systems by agent-based optimization, Water Resour. Res., 49,[3912][3913][3914][3915][3916][3917][3918][3919][3920][3921][3922][3923][3924][3925][3926]

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Section: Resultsmentioning

confidence: 99%

Assessing the value of cooperation and information exchange in large water resources systems by agent‐based optimization

Giuliani

Castelletti

2013

Water Resources Research

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“…Linked groundwater models and surface water simulation can now be linked to single or multi-objective global search algorithms (Reed et al 2013;Matrosov et al 2015); this new way to seek efficient solutions opens up many possibilities, including simultaneously considering non-economic objectives. Recent efforts (Yang et al 2009;Giuliani and Castelletti 2013;Erfani et al 2013) to move beyond deterministic optimization to represent more realistic behavioral modeling of water users are relevant here.…”

Section: Challenges Benefits and Future Directionsmentioning

confidence: 99%

Hydroeconomic Models as Decision Support Tools for Conjunctive Management of Surface and Groundwater

Pulido-Velázquez

Marques

Harou

et al. 2016

Integrated Groundwater Management

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Conjunctive use (CU) of surface and groundwater storage and supplies is essential for integrated water management. It is also a key strategy for supporting groundwater-dependent ecosystems, and for adapting water systems to future climate and land use changes. CU has become increasingly sophisticated and integrated with other innovative and traditional water management techniques, such as water transfers, water reuse, demand management, and aquifer remediation. CU adds value for society (increasing average yield and reliability) but can also induce costs to some parties, such as damaging senior water rights of surface water users when pumping from the aquifer reduces streamflow. Groundwater overexploitation also can produce a host of undesirable economic and environmental impacts. Successful CU implementation typically requires changes in infrastructure and operations, but also changes in institutions and institutional arrangements to offset potential third party costs and protect ecosystems. This chapter analyses first the management and economic implications of CU,

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“…Reviews of optimization applications for groundwater management (Reed et al 2013;Singh 2012) reveal that the use of traditional optimization and global search techniques have been applied to support decisions related to quantity and quality problems. For example, the groundwater decision support system (GWDSS) presents a hybridized example for water allocation that includes both simulation-optimization and lumped parameter modelling tools Pierce et al 2006).…”

Section: Applications Of Decision Support To Groundwater Casesmentioning

confidence: 99%

Decision Support Systems and Processes for Groundwater

Pierce

Sharp

Eaton

2016

Integrated Groundwater Management

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Information and knowledge management challenges abound in groundwater sciences. Groundwater problems of interest to society are characteristically complex and exceed our ability to solve them without the aid of computational analysis. Yet discipline specific problems that are of interest to hydrogeologists frequently do not directly address the immediate decision making needs of policy makers, groundwater managers, and stakeholders. It is the immediate societal needs that drive the demand for science-based information for common problems in which groundwater figures as a prominent element. Integrated Assessment and Modeling (IAM) presents an approach for merging discipline and case-specific knowledge, such as those in hydrogeological sciences, with social drivers for use in decision support applications. Moreover, decision support systems (DSS) that are constructed and applied using integration as a guiding principle and design ethic can advance groundwater DSS beyond passive support toward active and, eventually, proactive support for implementations to achieve real world integrated groundwater management. IntroductionGroundwater is a critical water resource that must be managed effectively while meeting the demands of society. The behavior and response of groundwater systems to natural and human influences are best understood through scientific analyses using data and models. In groundwater resource management, as with all water resources, disputes can be compounded by misconceptions about the meaning of data and scientific models, as well as social and political misunderstandings among the various interests. The complexity of groundwater management creates the need for computational assistance to support reasoned consideration of available scientific knowledge in conjunction with the preferences of the resource users.Decision support systems (DSS) are computational systems that use data and models interactively to aid in the formulation, analysis, and selection of management strategies. The design, architecture, and implementation of DSS are extensive, highly variable, and, ultimately driven by the needs of the decision problem and instance that is under evaluation. At the simplest levels, DSS may provide repositories of data and information in accessible formats and could offer tools to search and discover repository content. At the other end of the spectrum, DSS may incorporate sophisticated simulations, link with optimization algorithms, or other intelligent systems components to enhance decision making. Regardless of the level of sophistication, DSS are well suited for application to integrated groundwater problems because they can provide a set of applications, methodologies, and tools to cope with the inherent complexity and uncertainty. They can also be part of an Integrated Assessment and Modelling (IAM) process (Jakeman and Letcher 2003) providing distinct advantages for facilitating the IAM process, its transparency and its legacy. Indeed if constructed appropriately, DSS can provide ways o...

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Evolutionary multiobjective optimization in water resources: The past, present, and future

Cited by 449 publications

References 59 publications

Assessing the value of cooperation and information exchange in large water resources systems by agent‐based optimization

Assessing the value of cooperation and information exchange in large water resources systems by agent‐based optimization

Hydroeconomic Models as Decision Support Tools for Conjunctive Management of Surface and Groundwater

Decision Support Systems and Processes for Groundwater

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