We performed global sensitivity analyses of a land use model under deep uncertainty.

Deep uncertainty was characterised by internally consistent global change scenarios.

The influence of scenarios on output uncertainty and parameter sensitivity was significant.

Sensitivity indicators robust to deep uncertainty were calculated using four decision criteria.

Our methods can better inform efforts to improve model outputs under deep uncertainty.