×G2. Modelling complex human-natural systems under uncertainty: advances of participatory and computational approaches

Modelling is a crucial approach for analysing the behaviour of coupled human-natural systems for understanding their past and for exploring their future states. However, the presence of inherent complexity within these systems and various forms of uncertainty arising from the imperfect and contested knowledge we put in models challenges the status of inferences from modelling results.

New approaches to modelling human-natural systems have emerged—within social science disciplines—recently which relay on a participatory view and the inclusion of alternative perspectives to model development, model validation, and model use. Participatory approaches assist in modelling under uncertainty by bridging disciplines and organisational expertise of stakeholders for better identifying potential disruptors of the future and for creating collective decisions to proactively respond to these disruptors. Another group of computational approaches, called ‘exploratory modelling’, have also emerged to cope with uncertainties and complexities. The central idea of these computational approaches is to see models as thinking aids, where one tries to capture the relevant uncertainties by enumerating possible assumptions and systematically exploring the implications of these possible assumptions through large numbers of computational experiments.

Researchers' awareness about potential values of engaging stakeholders in the modelling process and recent advances in high-performance computing have led to growing interest in the use of participatory and computational approaches to modelling human-natural systems under uncertainty. This session invites submissions which are related to these approaches in the following areas:

Key topics: Socio-ecological systems, Participatory modelling, Uncertainty analysis, Exploratory modelling