  Computational aspects increasingly shape environmental sciences. Actually,
transdisciplinary modelling of complex and uncertain environmental systems is
challenging computational science (CS) and also the science-policy interface.
Large spatial-scale problems falling within this category - i.e. wide-scale
transdisciplinary modelling for environment (WSTMe) - often deal with factors
(a) for which deep-uncertainty may prevent usual statistical analysis of
modelled quantities and need different ways for providing policy-making with
science-based support. Here, practical recommendations are proposed for
tempering a peculiar - not infrequently underestimated - source of uncertainty.
Software errors in complex WSTMe may subtly affect the outcomes with possible
consequences even on collective environmental decision-making. Semantic
transparency in CS and free software are discussed as possible mitigations.
