Salt marshes have received considerable scientific attention in recent years due to a combination of factors. Salt marshes host important ecosystems and store large quantities of carbon in their soils (Fagherazzi et al. 2004; Mudd et al. 2009). Currently salt marshes are endangered by accelerated sea-level rise triggered by global warming (Kirwan et al. 2010). A sharp reduction in sediment supply caused by the damming of rivers is also jeopardizing marsh survival along many coasts (Weston 2014). As a result, there is a need to determine the fate of marshlands in different settings in order to inform government and local communities and implement protection strategies. To this end, numerical models are playing an increasingly important role, because they can easily provide future scenarios of marsh conditions under different forcings. However, the evolution of salt marshes as a function of sea-level rise and sediment supply is relatively complex, because of feedbacks among hydrodynamics, sediment transport, and vegetation (Fagherazzi et al. 2012). As a result, marshes are continuously adjusting to a changing environment, in ways often difficult to predict. This intrinsic complexity has generated a flurry of numerical models, each emphasizing a different aspect of salt marsh evolution. It is thus becoming more and more accepted by the scientific community that a comprehensive model of salt marsh evolution is not feasible, given the number and variety of physical and biological processes at play. A detailed approach, based on the description of all possible processes acting at different spatial and temporal scales, has been slowly replaced by a more practical approach, in which separate models are built to address key important processes or to capture specific dynamics.