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dc.contributor.authorPhan, Thuc D
dc.contributor.authorSmart, James CR
dc.contributor.authorCapon, Samantha J
dc.contributor.authorHadwen, Wade L
dc.contributor.authorSahin, Oz
dc.description.abstractBayesian belief networks (BBNs) are probabilistic graphical models that can capture and integrate both quantitative and qualitative data, thus accommodating data-limited conditions. This paper systematically reviews applications of BBNs with respect to spatial factors, water domains, and the consideration of climate change impacts. The methods used for constructing and validating BBN models, and their applications in different forms of decision-making support are examined. Most reviewed publications originate from developed countries (70%), in temperate climate zones (42%), and focus mainly on water quality (42%). In 60% of the reviewed applications model validation was based on the expert or stakeholder evaluation and sensitivity analysis, and whilst in 27% model performance was not discussed. Most reviewed articles applied BBNs in strategic decision-making contexts (52%). Integrated modelling tools for addressing challenges of dynamically complex systems were also reviewed by analysing the strengths and weaknesses of BBNs, and integration of BBNs with other modelling tools.
dc.relation.ispartofjournalEnvironmental Modelling & Software
dc.subject.fieldofresearchNatural resource management
dc.titleApplications of Bayesian belief networks in water resource management: A systematic review
dc.typeJournal article
dc.type.descriptionC1 - Articles
dc.type.codeC - Journal Articles
gro.facultyGriffith Sciences, Griffith School of Environment
gro.hasfulltextNo Full Text
gro.griffith.authorCapon, Samantha J.
gro.griffith.authorHadwen, Wade L.
gro.griffith.authorSahin, Oz
gro.griffith.authorSmart, Jim C.
gro.griffith.authorPhan, Thuc D.

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