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This Scenario Planning Guide outlines how the Urban Resilience to Extremes Sustainability Research Network (UREx SRN) supports ongoing efforts in its nine network cities in conducting participatory workshops. The Scenarios Working Group team, together with students, researchers, and collaborators across the network, have synthesized the co-produced visions from Workshop I. City-leads, practitioners, network participants, and participating institutions are encouraged to use the quantitative and qualitative outputs to further develop resilient, equitable, and sustainable transition pathways to help bring about their envisioned futures.

The primer begins with a brief description of the UREx SRN, before introducing the innovative framework applied to participatory scenario workshops. This is followed by an outline of the social-ecological-technological systems (SETS) approach that is applied throughout the project. A general explanation of scenarios is given, and a detailed description is provided of why scenario planning is applied, and the types of scenarios produced. The main portion of the primer focuses on the scenario workshops with detailed information provided on pre-workshop events, workshop activities and post-workshop data analysis and product synthesis.


ACKNOWLEDGEMENTS We would like to thank all our partner institutions and organizations, workshop participants, facilitators, notetakers, designers, and photographers. A special note of gratitude to Angela Grobstein for her unwavering support.

This material is based upon work supported by the National Science Foundation Cooperative Agreement #1444755, the Urban Resilience to Extremes Sustainability Research Network (UREx SRN) and the SETS Convergence GCR-Growing Convergence Research under Grant #1934933. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.


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Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.