Fuzzy Sets and Systems
Aggregation operators for soft decision making in water resources
Fuzzy Sets and Systems - Special issue on soft decision analysis
Business Dynamics
Possibility theory: Conditional independence
Fuzzy Sets and Systems
Short communication: Modeling climate change uncertainties in water resources management models
Environmental Modelling & Software
A methodology for the design and development of integrated models for policy support
Environmental Modelling & Software
Eliciting Preferences on Multiattribute Societies with a Choquet Integral
Computational Economics
Innovative approaches to integrated global change modelling
Environmental Modelling & Software
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In this article we propose an innovative approach to support a participatory modelling process for the exploratory assessment of vulnerability within the broad context of climate change adaptation. The approach provides a simplified dynamic vulnerability model developed within a conceptual model adopted - but very rarely made operational - by many international organisations such as the Intergovernmental Panel for Climate Change, the European Union. We propose a procedure in which disciplinary experts and local actors interact for the identification of the most relevant issues with reference to a specific vulnerability problem. Local actors (e.g. representatives of public administrations, business, NGOs) identify the most relevant issues related to the various dimensions of vulnerability, to be considered as input variables to contextualise the generalised model in the study case. Quantitative indicators are provided by disciplinary experts to describe past and future trends of variables, and their trajectories are combined to explore possible future vulnerability trends and scenarios. A non additive aggregation operator is proposed to allow experts and actors to pro vide their preferences through ad hoc questionnaires, thus overcoming the oversimplifications of most of the current vulnerability indices, which are usually either additive (fully compensatory) or multiplicative (non compensatory), and providing transparent and robust management of subjectivity and analysis of the deriving variability and uncertainty in model outputs. Input data for the demonstration of the model derive from the European Project Brahmatwinn, with reference to the Assam State in India.