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Robust global sensitivity analysis under deep uncertainty via scenario analysis
journal contribution
posted on 2016-02-01, 00:00 authored by L Gao, Brett BryanBrett Bryan, M Nolan, J D Connor, X Song, G ZhaoComplex social-ecological systems models typically need to consider deeply uncertain long run future conditions. The influence of this deep (i.e. incalculable, uncontrollable) uncertainty on model parameter sensitivities needs to be understood and robustly quantified to reliably inform investment in data collection and model refinement. Using a variance-based global sensitivity analysis method (eFAST), we produced comprehensive model diagnostics of a complex social-ecological systems model under deep uncertainty characterised by four global change scenarios. The uncertainty of the outputs, and the influence of input parameters differed substantially between scenarios. We then developed sensitivity indicators that were robust to this deep uncertainty using four criteria from decision theory. The proposed methods can increase our understanding of the effects of deep uncertainty on output uncertainty and parameter sensitivity, and incorporate the decision maker's risk preference into modelling-related activities to obtain greater resilience of decisions to surprise.
History
Journal
Environmental modelling and softwareVolume
76Pagination
154 - 166Publisher
ElsevierLocation
Kidlington, Eng.Publisher DOI
ISSN
1364-8152eISSN
1873-6726Language
engPublication classification
C Journal article; C1.1 Refereed article in a scholarly journalCopyright notice
2015, ElsevierUsage metrics
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global sensitivity analysisrobust sensitivity analysiseFASTdecision theoryland use changedeep uncertaintyScience & TechnologyTechnologyLife Sciences & BiomedicinePhysical SciencesComputer Science, Interdisciplinary ApplicationsEngineering, EnvironmentalEnvironmental SciencesWater ResourcesComputer ScienceEngineeringEnvironmental Sciences & EcologyLAND-USE CHANGEECOSYSTEM SERVICESDECISION-MAKINGCLIMATE-CHANGEINTEGRATED ASSESSMENTMODELSIMULATIONMANAGEMENTAUSTRALIASYSTEMS
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