Gully erosion is the major source of sediment across the Great Barrier Reef Catchment Area (GBRCA) contributing an estimated 54% of the total sediment generated from landscape processes. It would stand to reason therefore that any effort to reduce the load of sediment delivered from the GBRCA to the receiving waters of the Great Barrier Reef would focus on the remediation of gully erosion to some extent. To this end, the Australian and Queensland Governments are directing significant investment on projects aimed at reducing gully erosion. Mathematical gully erosion models can be useful for predicting the behaviour and evolution of gully initiation and growth to provide estimates of sediment export to the wider environment. Models can also be used to investigate various gully rehabilitation scenarios to quantify the potential mitigatory impacts of proposed projects and to help optimise their outcomes. MERGE (Modelling Erosion Resistance for Gully Erosion) is one such model that can quantify sediment loads resulting from gully erosion processes. MERGE is process-based and can be used to model the impacts of actions taken to rehabilitate gullies and reduce erosion to inform decisions related to gully remediation projects to protect coastal ecosystems. To gain some insight into the behaviour MERGE we conduct global sensitivity analyses on a range of model gully scenarios with distinctive characteristics. Sensitivity assessment has become a standard procedure for exploring the factors influencing model output quantities of interest. The credibility and utility of MERGE depends on knowledge of how important each variable (parameter and model input) is. The objective of sensitivity analysis is to quantify the incremental change in model response to incremental change in model variables. We find that the relative sensitivity of MERGE model parameters can vary significantly between different scenarios. A practical consideration arises from observing how the hierarchy of parameter influence on model response changes depending on the scenario. For example the more important variables may need refinement, and identifying those with little influence on model outputs may lead to model structure improvements and possibly simplifications. Furthermore, improved understanding of which gully process dominate the generation and transport of sediment may assist in designing engineering solutions for limiting erosion in the environment.