Group Model Building to Assess Local Knowledge of Nature Based Solution Implementation

Nature-Based Solutions (NBS) are increasingly adopted as measures for enabling climate change mitigation and adaptation, for reducing flood risks and for enhancing urban ecosystems. However, several barriers hinder the implementation of NBS in urban areas, in planning activities and strategies. These include the inadequacy of some existing methods based on hard and top-down approaches, the complexity and uncertainty associated with the network of citizens involved and the structuring of the knowledge deriving from that, in urban strategies. References emphasized the need to take citizens and their local knowledge into account when assessing the effectiveness of NBS implementation in planning strategies. Local knowledge could help to understand the success or failure of actions designed only by expert knowledge. Furthermore, shared local knowledge could increases social justice and the consequent livability of urban context. To this aim, this paper proposes a bottom-up methodological approach to assess the effectiveness of NBS implementation in spatial planning strategies, starting from local knowledge. The methodology was applied experimentally by involving high school students in the city of Brindisi (IT). Group Model Building (GMB) aimed at the exchange, generation, acquisition and dissemination of local knowledge of students involved, about NBS implementation in territorial planning strategies. Specifically, the GMB exercise used (i) Fuzzy Cognitive Maps to build a knowledge model of the students involved, (ii) geographic maps to define specific urban areas requiring NBS implementation, (iii) scenario building to define the benefits and possible shortcomings of NBS implementation in the urban context and spatial planning strategies.