Exploring scientific information for policy making under deep uncertainty. (December 2016)

• Record Type: Journal Article
• Authors: Forni, Laura G.; Galaitsi, S.E.; Mehta, Vishal K.; Escobar, Marisa I.; Purkey, David R.; Depsky, Nicholas J.; Lima, Nilo A.
• Is Part Of: Environmental modelling & software. Volume 86(2016)
• Page Start: 232
• Page End: 247
• Publication Date: 2016-12
• Subjects: Robust decision making -- Decision support tools -- Decision space visualizations -- Scenario modeling -- Water resource -- Uncertainty; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2016.09.021
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: Each actor evaluating potential management strategies brings her/his own distinct set of objectives to a complex decision space of system uncertainties. The diversity of these objectives and uncertainties requires detailed and rigorous analyses that respond to multifaceted challenges. The utility of this information depends on the accessibility of scientific information to decision makers. This paper demonstrates data visualization tools for presenting scientific results to decision makers in two case studies, La Paz/El Alto, Bolivia, and Yuba County, California. Visualization output from the case studies combines spatiotemporal, multivariate and multirun/multiscenario information to produce information corresponding to the objectives and uncertainties described by key actors. These tools can manage complex data and distill scientific information into accessible formats. Using the visualizations, scientists and decision makers can navigate the decision space and potential objective trade-offs to facilitate discussion and consensus building. These efforts can help identify stable negotiated agreements between different stakeholders. Highlights: We present a Decision Space Visualization (DSV) that condenses model results to tackle complex water management challenges. DSV enables comparisons between potential management options against many uncertainties. It allows exploring results in meaningful formats for decision makers that answers their most pressing questions. The case studies presented suggests that DSV stimulates active engagement from stakeholders.