Neglecting Human Response Leads to Biased Distributional Flood Risk Outcomes

Flood-risk assessments increasingly consider how flood risk is distributed across populations. However, future flood risk is subject to a number of uncertainties related to flood hazard, exposure, vulnerability, and human response, which are often not fully considered in such assessments. These uncertainties can be amplified by the finer scales required for distributional analyses. To better understand which uncertainties are relevant for distributional impacts, we perform a large-scale uncertainty characterization experiment using a calibrated agent-based model over the course of a multi-decadal simulation. We find that failing to account for key uncertainties, particularly related to flood damage estimation and human response, results in major biases in future flood losses and recovery. Furthermore, the relative importance of these uncertain factors vary depending on the population of interest. For example, we find that behavioral risk factors towards flooding are the most influential in shaping high-income population recovery, but factors related to housing preference and affordability are the most influential in shaping low-income recovery. Our results highlight the need to systematically account for multiple sources of uncertainty to better understand the distribution of flood risks.