Models for Adaptation Planning

Monday, 17 February 2014
Grand Ballroom E (Hyatt Regency Chicago)
Laura Schmitt-Olabisi , Michigan State University, East Lansing, MI
Participatory modeling (that is, scientists and stakeholders working together to construct a model jointly) has been used in a variety of fields for several decades, and is becoming increasingly popular to address environmental problems. However, its application to climate change adaptation remains underdeveloped, in spite of the many potential benefits participatory modeling might offer in a decision-making context that involves complexity and uncertainty. Here, I discuss building a participatory system dynamics model to address the problem of extreme heat in urban areas and its impacts on human health. Climate change models have predicted an increase in the frequency, duration and severity of deadly heat events globally. Hot weather kills more people in the United States annually than any other type of natural disaster, and the impacts of heat on human health will be a major climate change adaptation challenge for urban planners, health officials, and emergency managers. There are biophysical, socio-economic, and behavioral components to the health impacts of extreme heat, but the interactions among these types of variables are rarely examined. We developed a system dynamics modeling framework that incorporates biophysical, socio-economic, and behavioral aspects of extreme heat risk in Michigan, and are in the process of extending the model application to other cities in the northern U.S. We developed the model with the participation of partners in decision-making positions at the county and state level in Michigan. Using a participatory system dynamics model to address a climate change adaptation problem allowed stakeholders to test options for mitigating the effects of heat on human health using the model, and to observe the interactions among various modeled components. The model revealed some important limitations of previous approaches to reducing deaths and hospitalizations caused by extreme heat, which have tended to prioritize educational efforts and cooling centers. Overall, we found this participatory system dynamics modeling approach to be a powerful tool for illuminating the systemicity of the problem of extreme heat in urban areas, and for identifying the best ways to help vulnerable populations. The model could be even more powerful if linked with spatial information about heat risk.