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Applications of Bayesian Networks as Decision Support Tools for Water Resource Management under Climate Change and Socio-Economic Stressors: A Critical Appraisal

Phan, T. D., Smart, J. C. R., Stewart-Koster, B., Sahin, O., Hadwen, W. L., Dinh, L. T., Tahmasbian, I. and Capon, S. J. (2019) Applications of Bayesian Networks as Decision Support Tools for Water Resource Management under Climate Change and Socio-Economic Stressors: A Critical Appraisal. Water, 11 (12). p. 2642. ISSN 2073-4441

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Article Link(s): https://doi.org/10.3390/w11122642

Publisher URL: https://www.mdpi.com/2073-4441/11/12/2642

Abstract

Bayesian networks (BNs) are widely implemented as graphical decision support tools which use probability inferences to generate “what if?” and “which is best?” analyses of potential management options for water resource management, under climate change and socio-economic stressors. This paper presents a systematic quantitative literature review of applications of BNs for decision support in water resource management. The review quantifies to what extent different types of data (quantitative and/or qualitative) are used, to what extent optimization-based and/or scenario-based approaches are adopted for decision support, and to what extent different categories of adaptation measures are evaluated. Most reviewed publications applied scenario-based approaches (68%) to evaluate the performance of management measures, whilst relatively few studies (18%) applied optimization-based approaches to optimize management measures. Institutional and social measures (62%) were mostly applied to the management of water-related concerns, followed by technological and engineered measures (47%), and ecosystem-based measures (37%). There was no significant difference in the use of quantitative and/or qualitative data across different decision support approaches (p = 0.54), or in the evaluation of different categories of management measures (p = 0.25). However, there was significant dependence (p = 0.076) between the types of management measure(s) evaluated, and the decision support approaches used for that evaluation. The potential and limitations of BN applications as decision support systems are discussed along with solutions and recommendations, thereby further facilitating the application of this promising decision support tool for future research priorities and challenges surrounding uncertain and complex water resource systems driven by multiple interactions amongst climatic and non-climatic changes. View Full-Text

Item Type:Article
Business groups:Animal Science
Additional Information:Animal Science
Keywords:climate change; decision support tools; optimization-based approaches; scenario-based approaches; management measure categories; socio-economic stressors
Subjects:Science > Statistics > Statistical software
Agriculture > Agriculture (General) > Agricultural meteorology. Crops and climate
Technology > Technology (General)
Deposited On:28 Jul 2020 05:48
Last Modified:28 Jul 2020 05:48

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