DISADIST-ABM

Climate change is transforming natural disaster risks, creating increasingly complex challenges for vulnerable communities. Our research project seeks to develop a sophisticated analytical approach that reveals how different socioeconomic groups experience the economic impacts of climate-related events. Natural disasters do not affect all populations uniformly. Economic vulnerabilities are geographically and demographically concentrated, yet traditional research methods have struggled to capture these nuanced distributional effects. Our project aims to address this critical knowledge gap. Leveraging advanced computational modeling techniques, we will: Develop a comprehensive digital representation of the Austrian population Reconstruct intricate business supply chain networks Integrate spatially precise disaster risk information for environmental hazards like floods, droughts, and storms By utilizing state-of-the-art machine learning and agent-based modeling, we can simulate precise economic disruption scenarios across diverse population segments. Our approach is deeply rooted in model validation using so-called back-testing methods. This means that we will feed historical data on natural disasters into our model and test how well our model would have predicted economic impacts during those episodes. Our approach will: Investigate localized and demographic-specific economic vulnerabilities Identify populations most susceptible to climate disaster impacts Generate actionable policy recommendations for targeted community support This research represents a significant advancement in climate adaptation strategies, offering policymakers and community leaders a more granular understanding of economic resilience and vulnerability.

No additional funding sources recorded.