Multi-actor, multi-impact scenario discovery of consequential narrative
storylines for human-natural systems planning
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 narrative storylines that can guide
planning or further analyses. This study introduces the FRamework for
Narrative Scenarios 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 narrative 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 narrative
drought storylines, that can be used to inform future adaptation
planning.