Scenario Storyline Discovery for Planning in Multi-Actor Human-Natural Systems Confronting Change
January 1, 2024 - Hadjimichael, Antonia; Reed, Patrick M.; Quinn, Julianne D.; Vernon, Chris R.; Thurber, Travis
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Abstract: Scenarios have emerged as valuable tools in managing complex human-natural systems, but the traditional approach of limiting focus on a small number of predetermined scenarios can inadvertently miss consequential dynamics, extremes, and diverse stakeholder impacts. Exploratory modeling approaches have been developed to address these issues by exploring a wide range of possible futures and identifying those that yield consequential vulnerabilities. However, vulnerabilities are typically identified based on aggregate robustness measures that do not take full advantage of the richness of the underlying dynamics in the large ensembles of model simulations and can make it hard to identify key dynamics and/or storylines that can guide planning or further analyses. This study introduces the FRamework for Narrative Storylines and Impact Classification (FRNSIC; pronounced forensic): a scenario discovery framework that addresses these challenges by organizing and investigating consequential scenarios using hierarchical classification of diverse outcomes across actors, sectors, and scales, while also aiding in the selection of scenario storylines, based on system dynamics that drive consequential outcomes. We present an application of this framework to the Upper Colorado River Basin, focusing on decadal droughts and their water scarcity implications for the basin's diverse users and its obligations to downstream states through Lake Powell. We show how FRNSIC can explore alternative sets of impact metrics and drought dynamics and use them to identify drought scenario storylines, that can be used to inform future adaptation planning.Scenario analysis is a useful tool for assessing the impacts of future conditions or alternative strategies. Focusing on a small number of predetermined scenarios can, however, limit our understanding of key uncertainties, and fail to represent diverse stakeholder impacts. Approaches such as exploratory modeling have been developed to address these issues by exploring a wide range of possible futures and system perspectives. These approaches often involve large simulation experiments with their own interpretability challenges. So, on one hand, we recognize the need to utilize large ensembles of hypothesized changes, but on the other hand, each additional dimension considered makes it more difficult to convey actionable insights. We introduce the FRamework for Narrative Storylines and Impact Classification (FRNSIC; pronounced forensic), a scenario discovery framework that helps users identify scenario storylines that capture key system dynamics and as well as important outcomes. We demonstrate its application to the Upper Colorado River Basin, focusing on decadal droughts and their water scarcity implications for the basin's diverse users and its obligations to downstream states through Lake Powell. We explore alternative impact metrics and dynamics, identifying scenario storylines with significant impacts, which can be used in future planning efforts to adapt to these stressed conditions.Introduce framework for discovery of scenario storylines describing diverse stakeholder impacts and consequential dynamics Demonstrate the framework in the Upper Colorado River Basin with hundreds of stakeholders and complex human-natural system interactions The framework improves understanding and selection of drought scenario storylines through their effects on user- and basin-scale impacts
Type of Publication: Article
