In 2009, we set out to study how complex systems simulations could support collaborative water planning. We hypothesized that, by allowing participants to see the hidden effects of land- and water-use decisions on water flow, such tools could provide a platform for collective and innovative solution-building to complex environmental problems. We first adopted a developmental and collaborative agent-based approach, where groups of stakeholders learned how to inform and use models to assess the impacts of different implementation strategies. Despite their improved understanding and enhanced exploration of solutions, participants resisted policy innovation beyond familiar strategies. We refined our approach towards facilitated interaction with complex systems models and additional interfaces to help stakeholders provide direct input to the simulations, comprehend model outputs, and negotiate tradeoffs. Participants challenged outdated and false assumptions and identified novel solutions to their water woes. Nevertheless, at times the dissonance between simulation outputs and participants’ expectations was too great to accept and own. We share some stories of the obstacles encountered and offer suggestions to overcome them: keep models and interfaces simple, make both biophysical processes and values visible and tangible, and explicitly structure the social aspects of the simulation’s use. We draw on our experiences to show what aspects of visualization can support participatory planning.
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- Zellner, M; Lyons, L.; Milz, D.; Shelley, J.; Hoch, C.; Massey, D.; Radinsky, J. (Forthcoming). “Participatory Complex Systems Modeling for Environmental Planning: Opportunities and Barriers to Learning and Policy Innovation.” In Innovations in Collaborative Modeling; edited by Porter, Zhao, Scmitt Olabisi, and McNall; Michigan State University Press.
- Radinsky, J.; Milz, D.; Zellner, M.L.; Pudlock, K.; Witek, C.; Hoch, C.; Lyons, L.; 2016. “How Planners and Stakeholders Learn With Visualization Tools: Using Learning Sciences Methods to Examine Planning Processes.” Journal of Environmental Planning and Management, 1-28.
- Zellner, M.; Massey, D.; Minor, E.; Gonzalez-Meler, M.; 2016. “Exploring the Effects of Green Infrastructure Placement on Neighborhood-Level Flooding via Spatially Explicit Simulations.” Computers, Environment and Urban Systems 59 (2016): 116-128.- Hoch, C. J.; Zellner, M. L.; Milz, D. C.; Radinsky, J.; Lyons, L.; 2015. “Seeing is not believing: cognitive bias and modelling in collaborative planning.” Planning Theory and Practice 16 (3): 319-335.
- Zellner, M.L., Lyons, L.; Hoch, C. J.; Weizeorick, J.; Kunda, C.; Milz, D.; 2012. “Modeling, Learning and Planning Together: An Application of Participatory Agent-Based Modeling to Environmental Planning.” URISA Journal, GIS in Spatial Planning Issue, 24 (1): 77-92.
- Zellner, M. L.; 2008. “Embracing Complexity and Uncertainty: The Potential of Agent-Based Modeling for Environmental Planning and Policy.” Planning Theory & Practice 9 (4): 437-457.