Realizing the potential of community-led, science-driven participatory modeling: A case in green infrastructure planning

Participatory modeling (PM) is particularly well-suited to address complex socio-environmental problems like climate hazards and their implications on sustainable resource management and landscape planning. Despite its potential to inform planning and policy, particularly in conflictive contexts, PM has yet to become a mainstream practice for decision-making. While most of the PM research and development has focused on modeling tools and engagement techniques, multiple other dimensions must be recognized and articulated for impactful planning support. I present a PM platform, Fora.ai, that is supportive of the iterative steps in PM: problem definition and goal setting, preference elicitation, collaborative scenario-building, simulation, tradeoff deliberation, and solution-building. I demonstrate the platform’s effectiveness when embedded in a stakeholder-led process that integrates diverse knowledge, data sources, and values in pursuit of impactful green infrastructure (GI) planning to address flooding. I show how the combination of specific facilitation practices and platform features leveraged the power of data, computational modeling, and social complexity to contribute to collaborative learning, creative and convergent solution-building for urban sustainability and climate resilience.