Exploring equity weighting at the household level for flood risk assessment: a case study at Charleston, United States

Abstract

Flood risk management is essential in water resource planning to reduce potential damages and losses in flood-prone areas. Traditional risk assessments often focus on monetary values and ignore equity, leading to unequal distribution of protective measures. The equity weighting method has been implemented in past studies, but at certain administrative levels, it may not capture the income heterogeneity within those areas. This research investigates how accounting for income heterogeneity within administrative areas affects equity-weighted risk and impact estimates and explores practical ways to implement this approach, given privacy-related data limitations.

The study focuses on Charleston County, South Carolina, using disaggregated methods at the household level to integrate detailed socioeconomic data into equity-weighted flood risk assessments. The methodology involves assuming an equal distribution of income within predefined brackets and optimizing upper and lower bounds for open income brackets. Additionally, a linear relationship is assumed between the structure value and household income, allowing for the spatial allocation of income within census block groups.

The results demonstrate that the disaggregated method identifies more vulnerable households and shows significant differences in equity-weighted damage (EWD) and equity-weighted expected annual damage (EWEAD) metrics compared to the aggregated method. These findings suggest that the disaggregated method provides useful evidence for considering the importance of taking into account income heterogeneity when assessing flood risks, particularly in areas with significant income inequality.

Sensitivity and uncertainty analyses indicate that the income distribution parameters show both low sensitivity and low uncertainty when using a fitted log-normal distribution, suggesting that this distribution is a good fit for the data and provides stable results. In contrast, in the spatial allocation of income with structural values, the analysis results show high sensitivity and significant uncertainty, which means small changes in structure values lead to substantial variations in equity weight estimates.

The study concludes with recommendations for stakeholders to adopt household-level analysis and incorporate equity weights in cost-benefit analyses. Future research should explore additional socioeconomic factors, develop dynamic risk assessment models, and apply the methodology to diverse geographic and economic contexts.