The research investigates the synergies arising from the integration of tools belonging to different fields of knowledge into a single methodological framework, to characterise, incorporate and communicate the uncertainty in the assessment of adaptation strategies to the impacts of sea level rise (SLR), focussing on a specific area of study: the lagoon of Grado and Marano, in the North East of Italy. Two different processes of expert judgment elicitation are applied, firstly to categorise the main factors of the system into a shared conceptual model and then to create and populate a Bayesian decision network (BDN) model, representing the relationships between SLR scenarios, adaptation alternatives, and direct and indirect impacts of SLR. The model helps to make predictions on the effects of alternative adaptation options in different scenarios of SLR. The stability of the results is assessed through uncertainty analyses. The proposed methodology moves beyond the incorporation of uncertainty in climate change analysis and accounts for learning, supporting an adaptive management approach, to structure an informed and trasparent decision making process.