Causal Loop Diagrams for supporting Nature Based Solutions participatory design and performance assessment

The contribution of Nature Based Solutions (NBSs) for supporting climate change adaptation and water-related risks reduction is becoming increasingly relevant for policy and decision-makers, compared to ‘grey infrastructures’, thanks to their capability to jointly deal with a multiplicity of societal and environmental challenges, producing several co-benefits besides limiting the impacts of water-related risks. Nevertheless, their mainstreaming is still limited by several barriers, which are often related to socio-institutional (e.g. limited cooperation and stakeholders' involvement, limited awareness about NBSs impacts) rather than to technical aspects. In this context, innovative tools for NBSs planning, design, implementation and assessment are required, along with effective processes capable of supporting stakeholders' participation. The present research aims to propose a shift in the approach to NBSs design, based on the early stakeholders' involvement in the identification, modelling and performance assessment in terms of benefits and, particularly, co-benefits production. A multi-step methodology was implemented for the purpose, combining both individual and participatory activities. Reference is made to one of the case studies of the NAIAD project, namely the Balta Potelu Pond Area (Lower Danube, Romania). Causal Loop Diagrams (CLDs) were used to describe the system in terms of causal connections and mutual influences, incorporating stakeholders' views and ideas. Inputs from both institutional (e.g. ministries and municipalities) and non-institutional stakeholders (e.g. NGOs and members of the local communities) were integrated. This allowed a comparative assessment of multiple NBSs, based on the analysis of benefits and co-benefits produced, as well as the identification of trade-offs among different stakeholders (e.g. the increase of agricultural production versus biodiversity conservation) and potential side effects. CLDs were then coupled with a Performance Matrix (a basic feature of Multi-Criteria Decision Analysis) and fuzzy logic to help decision-makers identify the most suitable NBSs for the area. The whole process was aimed at facilitating the process of NBSs selection and analysis, while considering the multiple impacts associated with their implementation.