When Recovery Becomes Infeasible: A Markov Model of Housing Abandonment Risk in Flood-Prone Areas

Floods can undermine long-term community viability by depressing housing markets and triggering property abandonment cycles. This study estimates the risk of housing abandonment by integrating traditional flood-risk frameworks with the concept of sub-replacement–a condition where the cost of repairing a house exceeds its market value. We propose a new risk metric that identifies whether a house enters a sub-replacement condition within a given time horizon. Our stochastic model is a time–homogeneous, discrete-time Markov process that incorporates flood hazard, housing exposure, physical vulnerability, and housing market dynamics. We apply the model to two U.S. communities–Pascagoula, Mississippi, and McGregor, Florida. These two communities exhibit similar flood hazard, exposure, and building vulnerability, but markedly different housing market conditions. Despite comparable Average Annual Losses (AAL), the number of houses expected to experience sub-replacement within the next three decades is twenty five times larger in Pascagoula than in McGregor. We also find that the FEMA 50\% rule–which mandates elevation when repair costs exceed 50\% of a home’s market value–reduces AAL by approximately 70\%, but increases sub-replacement risk in areas with depressed housing markets. This risk is especially concerning in Pascagoula, where lower housing prices increase the number of houses expected to enter sub-replacement in the next three decades by a factor of eight. Our findings show that incorporating housing market conditions into flood risk analysis is important for anticipating long-term recovery trajectories and prevent downward spirals of disinvestment and population loss.