Flood risk management via collaborative modelling

The European Directive for Flood Risk Management (FRM) requires a demand-driven approach in which policy-makers work together with practitioners and the general public in preparation of FRM plans and actions. In that context, the DIANE-CM project (Decentralised Integrated Analysis and Enhancement of Awareness through Collaborative Modelling and Management of Flood Risk), funded by the 2nd ERANET-CRUE initiative, proposes an innovative approach which brings the conventional modelling procedures in a participative environment. In these conditions the decision-making process is directed towards a consensus among all involved parties, which legitimises the decisions and enhances their successful implementation. This MSc thesis is developed within the framework of the DIANE-CM project. Its main focus is on the methodology for supporting the above stated project goals by the implementation of a web-based collaborative platform (CP) for shared understanding of flood risk and the execution of a Collaborative Modelling Exercise (CME). This CME is developed with three modules: Individual profile, group profile and collaboration and negotiation stage. These modules lead towards preferred ranking of proposed alternatives for FRM by individual stakeholders (SHs) and by the group as a whole, which are based on a background technique adapted from the TOPSIS Method (Technique for Order Preference by Similarity to Ideal Solution). The thesis report highlights the main findings and lessons learned from the implementation of the web collaborative modelling tools within common stages for two case studies, different in magnitude and time scale: the Cranbrook catchment (UK case study focused only on a small urban catchment for flood event management) and the River Alster catchment (German case study that covered the long-term planning within the whole catchment for improved flood management). This set-up allows comparisons in the process and feedback sharing between the two case studies, which enable drawing conclusions and recommendations for replicating the developed methodologies in different areas across Europe. The main conclusions from this work are that collaborative modelling approaches are appreciated by involved SHs and that the tools like CP and CME are contributing for shared understanding of flood risk. Appropriate filtering and formatting of the provided information to different categories of SHs and up-scaling of the collaborative modelling approach to broader categories of social actors, including the general public, are main challenges for wider adoption of the proposed approach