Effective management of aquatic fauna requires knowledge of the ways in which populations in different catchments and sub-catchments are connected. A powerful way to estimate this is using genetic markers, which provide information on the average amount of genetic connectivity among populations over generations. Although many studies of genetic connectivity have appeared in the literature, there are innumerable species that have not been studied. This study explores whether it is possible to make broad generalisations about population connectivity, based on readily available information in the form of species life history and architecture of the aquatic habitat. A number of models have been proposed to explain the pattern of connectivity shown by aquatic species with different life-history characteristics, for example, the stream hierarchy model, Isolation by Distance, the Death Valley Model, the headwater model and panmixia. In this study, we propose a dichotomous key to assign species to different models of potential connectivity. The key is based on a few very simple questions about the life history of the species and the geographical arrangement of study sites. We then assessed the performance of the key with 109 data sets of Australian fish and macroinvertebrates, using genetic data to provide an estimate of realised connectivity. The realised connectivity fitted the proposed potential connectivity model in over 70% of cases, and we suggest this might be a useful initial approach for managers where empirical data are lacking.