Over the past year, I have been collaborating with the Graham Sustainability Institute’s Water Center on qualitative research focused on improving the quality and relevance of analysis conducted as part of their project “Watershed Assessment of Detroit River Nutrient Loads to Lake Erie.” This project seeks to better understand the causes of harmful algal blooms in Lake Erie, and is engaging a diverse group of bi-national stakeholders to improve the quality of the collaborative science.
One paper resulting from this collaboration has been published online. We hope it demonstrates a method which will be valuable in other impact assessment projects, as well as providing a needed empirical application of a popular theoretical framework in the field. Here’s the abstract:
The topic of uncertainty is of growing interest in the impact assessment (IA) field, due to increases in contextual uncertainty and the awareness of the complexity of advanced analysis. IA practitioners can now draw on maturing theoretical frameworks to manage uncertainty, but questions remain about whether these frameworks align with stakeholder concerns and how their use can benefit IA projects. This article reports on an empirical application of the leading framework for organizing IA uncertainty proposed by Walker et al. in 2003. Twenty-two stakeholders involved in a large water quality modeling project in the U.S. Great Lakes region were interviewed, and their uncertainty-related statements were categorized according to the Walker dimensions. Overall, the framework’s three primary dimensions performed well and allowed for the analysis of differences in uncertainty perceptions among the stakeholder groups. In addition, the analysis resulted in useful insights for the project, such as identifying top scenario uncertainties to use for modeling as well as highlighting specific concerns about the assumptions, data, and modeling approach for further exploration. In addition to encompassing the variety of uncertainty concerns raised in the case, the paper illustrates how the Walker framework can support IA practices like stakeholder collaboration and scenario construction which may improve IA outcomes.
> Access article: “Analyzing stakeholder’s perceptions of uncertainty to advance collaborative sustainability science: Case study of the watershed assessment of nutrient loads to the Detroit River project” (Free access until 8/11/16, obtain through a library after that date)