Using Panel Data to Understand the Dynamics of Human Behavior in Response to Flooding

Area of Science:

• Environmental Psychology
• Disaster Risk Management
• Sociology

Background:

• Effective flood risk management requires understanding human behavior dynamics.
• Current understanding is limited by cross-sectional surveys, hindering insights into risk perception, attitudes, and recovery.
• Longitudinal data is essential for analyzing changes in human behavior post-flooding.

Purpose of the Study:

• To investigate the dynamics of human behavior, risk perception, and recovery over time following a flood event.
• To analyze adaptive intentions and behaviors using panel survey data.
• To inform integrated flood risk management strategies and human behavior modeling.

Main Methods:

• Conducted a panel survey with 227 individuals affected by the 2013 flood in Germany over four years and three waves.
• Utilized repeated-measures ANOVA to analyze changes in attitudes and risk perceptions.
• Employed latent class growth analysis (LCGA) to identify heterogeneous recovery and adaptation trajectories.

Main Results:

• Attitudes, such as perceived responsibility in flood risk management, remained stable over the study period.
• Risk perceptions showed some changes, while individual recovery and intentions for risk-reducing measures exhibited significant changes.
• Latent class growth analysis identified distinct, heterogeneous trajectories for individual recovery and adaptation.

Conclusions:

• Human behavior dynamics post-flooding are complex and evolve over time, with significant variations in recovery and adaptation.
• Policies supporting individual recovery and societal preparedness must account for these heterogeneous trajectories.
• Further longitudinal panel studies are vital for deeper insights into flood risk-related human behavior and protective factors.