Integrated assessment of sea-level rise adaptation strategies using a Bayesian decision network approach

• Authors: Michela Catenacci;Carlo Giupponi
• Venue: Environmental Modelling & Software
• Year: 2013

The exposure to sea-level rise (SLR) risks emerges as a challenging issue in the broader debate about the possible consequences of global environmental change for at least four reasons: the potentially serious impacts, the very high uncertainty regarding future projections of SLR and their effects on the environmental and socio-economic system, the multiple scales involved, and the need to take effective management decisions in terms of climate change adaptation. Unfortunately, mechanistic models generally demonstrated a limited ability to characterise in appropriate detail how complex coastal systems and their constituent parts may respond to climate change drivers and to possible adaptation initiatives. The research reported here develops an innovative methodological framework, which integrates different research areas - participatory and probabilistic modelling, and decision analysis - within a coordinated process aimed at decision support. The effectiveness of alternative adaptation measures in a lagoon in north-east Italy is assessed by means of Bayesian Decision Network (BDN) models, developed upon judgments elicited from selected experts. A concept map of the system was first developed in a group brainstorming context and was later evolved into BDN models, thus providing a simplified quantitative structure. Conditional probabilities, quantifying the causal links between the direct and indirect consequences of SLR on the area of study, are elicited from the experts. The proposed methodological framework allows the integrated assessment of factors and processes belonging to different domains of knowledge. Moreover, it activates an informed and transparent participatory process involving disciplinary experts and policy makers, where the main risk factors are considered together with the expected effects of the adaptation options, with effective treatment and communication of the uncertainty pervading the SLR issue. Finally, the framework shows potentials for being further developed and applied to consider new evidences and/or different adaptation strategies, and it results sufficiently flexible to be adopted and effectively reused in other similar case studies.