The interest in landscape evolution models (LEMs) that simulate multiple landscape processes is growing. However, modelling multiple processes constitutes a new starting point for which some aspects of the set up of LEMs must be re-evaluated. The objective of this paper is to demonstrate the practical significance of, and possibilities for such re-evaluation. We first discuss which simplifications must be made to set up LEMs. Then, simplifications of particular interest to the modelling of multiple processes are identified. Finally, case studies from New Zealand, Belgium and Croatia explore the performance of different model versions under several common choices for model and data simplifications. In these case studies we illustrate methods to make the choices, typically by i) comparing the results of different model versions, ii) assessing model validity or iii) indicating the sensitivity of models for different simplifications. The results indicate that LEM performance is strongly dependent on multi-process related choices, and that performance indicators can be used for ex-post testing of the influence of these choices. In particular, we demonstrate the significance of simplifications regarding the number of processes, presence of sinks and temporal resolution.