The simulation sessions provide a wealth of qualitative (and some quantitative) insights into stakeholder behavior in a complex and changing environment. To evaluate the effectiveness of potential intervention options (WP 5) in such complex environments, agent-based models (ABMs) will be developed. ABMs can explore the effects of a wide range of assumptions, future scenarios and possible (policy) interventions, in this case aimed at achieving local adaptation measures on climate change and water efficiency. The project’s Agent-Based Models (ABMs) will be composed of: (i) various types of actors, including individual tourists, managers and decision-makers; (ii) interrelated and weighted variables; (iii) attitudes and profiles from urban water demand; (iv) scenarios and decision-making heuristics; and (v) learning rules and guidelines to identify water and social variables involved in coastal mass-tourism destinations. Achieving objective 6 requires the integration of information about water availability, consumption and scarcity (obj. 1, 2, 3), social (power) relations (obj. 4) and behavior (obj. 5). The Agent-Based Model will be set up in such a way that various types of policies can be evaluated, including qualitative and quantitative restrictions, conditions and rules, taxes and levies. These policies are modelled as exogenous factors, represented by buttons and levers in the model interface. Policy effectiveness will be measured in terms that are meaningful to stakeholders. These terms will be further specified in consultation with the stakeholders during the project, but likely candidates include water consumption, water efficiency (water consumption per tourist/room/unit of income/unit of energy used/etc.) and water scarcity. Rather than providing point estimates, the model simulations will produce distributions of potential outcomes, reflecting the large inherent uncertainties in complex systems.