scholarly journals Resilience, Decision‐making, and Environmental Water Releases

2018 ◽  
Vol 6 (6) ◽  
pp. 777-792 ◽  
Author(s):  
Long Chu ◽  
R. Quentin Grafton ◽  
Michael Stewardson
Keyword(s):  
Decision Making ◽  
Environmental Water

Bayesian Belief Networks for the metamodeling of simulation-optimization model to identify optimum water allocation scenario, Application in Miyandoab plain, Urmia Lake basin, Iran

2021 ◽  
Author(s):  
Amirhossein Dehghanipour ◽  
Gerrit Schoups ◽  
Hossein Babazadeh ◽  
Majid Ehtiat ◽  
Bagher Zahabiyoun
Keyword(s):  
Decision Making ◽  
Optimization Model ◽  
Water Demand ◽  
Simulation Optimization ◽  
Bayesian Belief Networks ◽  
Environmental Water ◽  
Lake Basin ◽  
Decision Making Models ◽  
Validation Tests ◽  
Urmia Lake Basin

<p>In this study, decision-making models in uncertain conditions are developed to identify optimal strategies for reducing competition between agricultural and environmental water demand. The decision-making models are applied to the irrigated Miyandoab Plain, located upstream of endorheic Lake Urmia in Northwestern Iran. Decision-making models are conceptualized based on static and dynamic Bayesian Belief Networks (BBN). The static BBN evaluates the effects of management strategies and drought conditions on environmental flow and agricultural profit at the annual scale, while the dynamic BBN accounts for monthly dynamics of water demand and conjunctive use. The reliability and performance of BBNs depend on the quantity and quality of data used to train the BBN and create conditional probability tables (CPTs). In this study, simulated outputs from a multi-period simulation-optimization model (Dehganipour et al., 2020) are used to populate the CPTs in each BBN and reduce the BBN training error. Cross-validation tests and sensitivity analysis are used to evaluate the effectiveness of the resulting BBNs. Sensitivity analysis shows that drought conditions have the most significant impact on environmental flow compared to other variables. Cross-validation tests show that the BBNs are able to reproduce outputs of the complex simulation-optimization model used for training, and therefore provide a computationally fast alternative for decision-making under uncertainty.</p><p><strong>Reference:</strong> Dehghanipour, A. H., Schoups, G., Zahabiyoun, B., & Babazadeh, H. (2020). Meeting agricultural and environmental water demand in endorheic irrigated river basins: A simulation-optimization approach applied to the Urmia Lake basin in Iran. Agricultural Water Management, 241, 106353.</p>

An Impossible Prescription: Why Science Cannot Determine Environmental Water Requirements for a Healthy Murray-Darling Basin

2017 ◽  
Vol 03 (03) ◽  
pp. 1650037 ◽  
Author(s):  
Samantha J. Capon ◽  
Timothy R. Capon
Keyword(s):  
Decision Making ◽  
Water Policy ◽  
Environmental Water ◽  
Management Scenarios ◽  
Water Requirements ◽  
Political Dimension ◽  
Murray Darling Basin ◽  
Alternative Water ◽  
Ecological Objectives ◽  
Ecological Science

The concept of environmental water requirements (EWRs) is central to Australia’s present approach to water reform. Current decision-making regarding environmental water relies strongly on the notion that EWRs necessary to meet targets associated with ecological objectives for asset sites can be scientifically defined, thus enabling the ecological outcomes of alternative water management scenarios to be evaluated in a relatively straightforward fashion in relation to these flow thresholds or targets. We argue, however, that the ecological objectives and targets currently underpinning the development of EWRs in the Murray-Darling Basin are insufficient to permit the identification of exact water requirements or flow thresholds. Because of the dynamic and heterogeneous nature of the Murray-Darling Basin and the myriad ways in which it is valued by people, we also assert that it is unlikely that adequate ecological objectives and targets from which to determine EWRs could ever be formulated. We suggest that the current emphasis on the concept of EWRs in environmental water planning conflates science and values, perpetuating a “how much is enough?” myth whereby the significance of the social, cultural and political dimension in environmental decision-making is diminished. We support an alternative paradigm in which the contribution of ecological science to water policy and management decisions focuses on understanding ecological responses of water-dependent ecosystems and their biota to alternative management scenarios and linking these responses to the ecosystem services and human values which they support.

Discarding optimality: Throwing out the baby with the bathwater?

2018 ◽  
Vol 41 ◽  
Author(s):  
Patrick Simen ◽  
Fuat Balcı
Keyword(s):  
Decision Making ◽  
Perceptual Decision Making ◽  
Reward Rate ◽  
Perceptual Decision ◽  
Standard Observer ◽  
Rate Maximization ◽  
Reward Rate Maximization ◽  
Descriptive Standard ◽  
Observer Model

AbstractRahnev & Denison (R&D) argue against normative theories and in favor of a more descriptive “standard observer model” of perceptual decision making. We agree with the authors in many respects, but we argue that optimality (specifically, reward-rate maximization) has proved demonstrably useful as a hypothesis, contrary to the authors’ claims.

LPCD framework: Analytical tool or psychological model?

2018 ◽  
Vol 41 ◽  
Author(s):  
David Danks
Keyword(s):  
Decision Making ◽  
Analytical Tool ◽  
Mathematical Framework ◽  
Bayesian Decision ◽  
Perceptual Decision Making ◽  
Psychological Model ◽  
Psychological Reality ◽  
Psychological Theories ◽  
Target Article ◽  
Bayesian Decision Making

AbstractThe target article uses a mathematical framework derived from Bayesian decision making to demonstrate suboptimal decision making but then attributes psychological reality to the framework components. Rahnev & Denison's (R&D) positive proposal thus risks ignoring plausible psychological theories that could implement complex perceptual decision making. We must be careful not to slide from success with an analytical tool to the reality of the tool components.

Elaborating the role of reflection and individual differences in the study of folk-economic beliefs

2018 ◽  
Vol 41 ◽  
Author(s):  
Kevin Arceneaux
Keyword(s):  
Decision Making ◽  
Individual Differences ◽  
Cognitive Processes ◽  
Evolutionary History ◽  
Behavioral Responses ◽  
History Of ◽  
Economic Beliefs

AbstractIntuitions guide decision-making, and looking to the evolutionary history of humans illuminates why some behavioral responses are more intuitive than others. Yet a place remains for cognitive processes to second-guess intuitive responses – that is, to be reflective – and individual differences abound in automatic, intuitive processing as well.

The primacy of conscious decision making – ERRATUM

2014 ◽  
Vol 38 (01) ◽  
pp. 46
Author(s):  
David R. Shanks ◽  
Ben R. Newell
Keyword(s):  
Decision Making ◽  
Conscious Decision
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