Abstract/Summary

Storylines are plausible descriptions of past or future events and can be used to characterise uncertainty through discrete possible futures. They thereby bridge the gap between global-scale future projections and local-scale impacts, providing decision-makers with useful information about potential impacts in multivariate systems despite large swathes of missing data. Here we demonstrate the storyline approach using the case of household food security in the Caprivi region of Namibia, an example of a complex system with multiple interacting drivers. We develop a network characterising influences on household food security, highlighting drivers that are affected by the local weather (with climate understood to constitute the collection of possible weather states). The network is used to understand the storyline leading to household impacts in 2013-14, a consumption year affected by flooding, and the effects of a range of interventions across wealth groups. Counterfactual storylines are also developed to characterise potential impacts under different local and national conditions. Through this we demonstrate how a storyline approach can embed local contextual information to provide decision-makers with comprehensible and assessable information about possible futures and interventions. We also highlight the importance of identifying common drivers, in this case the local weather, in producing plausible impact storylines.