Integrating Societal Development into Flood Damage Models

This workingpaper examines three methodological approaches for incorporating socio-economic and land-use dynamics into future flood-damage calculations: (1) sorting models that describe spatial equilibrium outcomes arising from household and firm location choices, (2) agent-based models that simulate adaptive behavior and interaction among heterogeneous agents, and (3) predictive models that use empirical and machine-learning techniques to project land-use and socio-economic change. We undertake a theoretical synthesis to evaluate the conceptual foundations, data requirements, and modelling implications of each approach. The motivation for this work lies in the limitations of current Danish flood damage models, which largely treat exposure and vulnerability as static, even though ongoing urbanization, demographic shifts, and behavioral adaptation are reshaping spatial patterns of risk. Without explicit representations of societal development, future flood-risk estimates may mischaracterize both the scale and distribution of expected damages. The paper’s contribution is twofold. First, it evaluates the methodological trade-offs across predictive, equilibrium-based, and agent-based approaches, highlighting where each paradigm is limited and where it offers unique leverage for representing socio-economic change. Second, by providing a coherent economic–spatial–hazard framework, the paper establishes the conceptual foundations for incorporating dynamic exposure into future risk calculations. Looking ahead, the analysis sets an agenda for developing land-use change modelling frameworks that can support long-term climate-resilience planning and strengthen the alignment between spatial development and adaptation policy.