A Hierarchical Sociohydrological Model Incorporating Spacial Heterogeneity for Flood Risk Management

Flood risk management is shaped by complex feedbacks between hydrological processes and social responses, yet many existing sociohydrological models treat society as a homogeneous entity. This study develops a hierarchical sociohydrological model that explicitly represents socioeconomic heterogeneity by incorporating multiple disaster-vulnerable social groups. The study area is divided into three groups based on topography and socioeconomic characteristics, and group-specific dynamics are modeled by accounting for population movements within and beyond the region, as well as differences in flood memory loss, preparedness levels, and mobility.

 

Key model parameters are estimated using household survey data collected in San Mateo City, the Philippines. Using this empirically grounded model, we evaluate the impacts of alternative flood management strategies through numerical simulations, focusing on variations in levee height and the frequency of disaster preparedness education. The model is applied to contrasting policy scenarios with and without levee protection to assess their differential effects on flood losses across social groups.

 

The results reveal that under a no-levee scenario, flood losses become increasingly uneven over time, with widening disparities among social groups, indicating the amplification of social inequality. In contrast, levee-based scenarios reduce inter-group disparities in cumulative flood losses; however, they also lead to substantially larger losses per event when extreme floods occur. These findings highlight a trade-off between reducing chronic inequality and increasing vulnerability to rare but catastrophic events.

 

By explicitly integrating socioeconomic heterogeneity into sociohydrological modeling, this study demonstrates the importance of distributional analysis in flood risk assessment and adaptation planning. The proposed framework provides a quantitative basis for evaluating equity–efficiency trade-offs in flood management policies and supports the design of more just and effective flood adaptation strategies.