Climate driven disasters are increasing in frequency, intensity, and severity, driven by shifts in hazard distribution, changes to population exposure, and social vulnerability. As these impacts intensify, there is an need to develop methods that can address the heterogeneous ways people experience them. Over the past 30 years there has been growing agreement that bottom-up, community-based, and participatory approaches to risk governance can lead to more effective, longer-lasting approaches to mitigating to disaster risk. This dissertation explores three ways that incorporating social heterogeneity derived from risk governance principles can enhance the application of decision making under deep uncertainty-based analyses of disasters (DMDU). It does so through three diverse case studies that make methodological extensions to existing approaches to risk governance and DMDU. All three identify key themes that risk reduction practitioners, planners, and policymakers need to address in work to reduce risk due to climatologically driven disasters.
Paper 1 enhances representation of beliefs using the tools of DMDU - scenario discovery and robustness, applied to the case of global carbon taxes and SLR adaptation. It finds that addition of explicit representation enables comparison of decision options on socially contentious policy areas. Paper 2 extends the modeling of flood losses by analyzing flood impacts at household level and considers impacts of uncertainty in future climate change and intervention cost at a subnational level in Argentina. It finds that we can identify complementary policies for flood risk reduction by expanding metrics used in analysis. Paper 3 contributes to methods for analyzing participation in risk governance through an application to a DMDU analysis with deliberation process for landslide warning system design. It finds that this disaggregation helps understand barriers and opportunities for specific system design choices.
Taken together, these papers find that looking across social and governance scales, enhancing the representation of social heterogeneity can improve both the analytic tools and engagement processes used in decision-making under deep uncertainty. It also highlights that there remain scalar challenges to integrating these tools and the decision processes that offer rich opportunities for future research.
Table of Contents
Incorporating Heterogenous World Views in Climate Policy
Using Welfare Metrics to characterize Flood Impacts in Argentina and Identify Robust Responses
Disaggregating Community Engagement in Participatory Governance: the Case of Warning System Design for Landslide Hazard in Sitka, AK
Policy Implications and Recommendations
Carbon Taxes and Se Level Rise
Argentina Flood Risk
Sitka Landslide Warning System