Integrating Household Risk Mitigation Behavior in Flood Risk Analysis: An Agent-Based Model Approach

Area of Science:

• Environmental science
• Climate change adaptation
• Socioeconomic modeling

Background:

• Climate change and socioeconomic trends are increasing global flood risks.
• Previous flood risk studies often assume constant human behavior, neglecting crucial human-environment interactions.
• This omission leads to significant misrepresentations of actual flood risk.

Purpose of the Study:

• To present an agent-based model (ABM) integrating human decision-making into flood risk analysis.
• To examine household investment in loss-reduction measures under different economic decision models.
• To demonstrate the impact of dynamic human behavior on flood risk assessment.

Main Methods:

• Developed an agent-based model incorporating human decision-making.
• Compared three economic decision models: expected utility theory, prospect theory, and Bayesian updating prospect theory.
• Analyzed household investments in loss-reducing measures.

Main Results:

• Neglecting human behavior can lead to considerable misestimation of future flood risk (overestimation by a factor of two in the case study).
• Behavioral models can support flood risk analysis under various behavioral assumptions.
• Dynamic adaptive behavior of households, insurers, and governments is essential for accurate flood risk assessment.

Conclusions:

• Dynamic human behavior significantly influences flood risk.
• Agent-based models incorporating adaptive human decision-making are crucial for accurate flood risk assessment.
• The presented method provides a robust framework for analyzing human behavior and its impact on low-probability/high-impact risks.