This research generates single-family home flood risk estimates to derive apportionment factors (AF; i.e., homeowners’ proportion of average annual loss (AAL)). Flood loss events are modeled at the individual building level using a Monte Carlo simulation, in which the flood hazard is characterized by the Gumbel extreme value distribution function. A depth-damage function (DDF) from the United States Army Corps of Engineers (USACE, 2000) is used, to estimate the loss of each flood event. The losses are allocated to the homeowner or the insurer based on insurance parameters (i.e., coverage and deductible). The homeowner or insurer AAL portion and the AF are calculated by averaging the homeowner or insurer loss for all flood events and dividing the homeowner AAL portion by the total AAL, respectively. Two case studies are presented here to demonstrate the methodology. The first is for a hypothetical one-story home located in Metairie, Louisiana. The second includes the spatial heterogeneity in building analysis where the buildings in Special Flood Hazard Area (i.e., SFHA) are considered. For both cases, the AF is estimated using different coverage, deductible, and freeboard (i.e., elevation of the first floor above the base flood elevation) scenarios. The effect of coverage and deductible on the AF is examined. Furthermore, the effect of the freeboard on the estimated AAL is also evaluated.

The contribution of this paper is novel characterization of AF for homeowner-borne annual flood risk based on flood insurance deductible and coverage values. Researchers will find utility from this method to better estimate the impacts of floods experienced by homeowners. Results from this work will greatly enhance webtools and education/outreach materials for the general public, realtors, homebuilders, and community leaders. Educational information derived from this research will assist individual homeowners in making more informed decisions regarding the purchase of flood insurance and the selection of insurance coverage and the associated deductible.

The method consists of characterizing the flood hazard at a defined location using the Gumbel extreme value distribution and estimating flood AAL using Monte Carlo simulation. The simulation generates random flood event probabilities, and the corresponding losses are calculated using an appropriate DDF, with damage apportioned to either the homeowner or the flood insurer for each flood event based on insurance coverage and deductible scenarios. The apportioned losses are averaged over all flood events to estimate the AAL for the homeowner and flood insurer.

The specific findings of the single-building case study are:

• The homeowner is accountable to bear the overall building and contents AAL for uninsured homes. But, for insured homes, a large portion of AAL is borne by the flood insurer, particularly for building loss, which translates into lower flood risk associated to homeowners.
• For all combinations of coverage and deductible, the homeowner building AF is less than 50%; while at low values of flood deductible (e.g., $1,000), the homeowner building AF is approximately 5% for all coverage levels.
• For all combinations of coverage and deductible, the homeowner contents AF is less than 70%; while at low values of flood deductible (e.g., $1,000), the homeowner contents AF is approximately 10% for all coverage levels.
• The AF are relatively insensitive to coverage, especially for higher coverage values. The AF for each deductible decreases when the coverage value increases from basic coverage amount and remains essentially constant for coverage values exceeding $100,000 and $50,000 for building and contents, respectively.
• The deductible is a statistically significant (𝑝 < 0.05) explanatory variable for the AF, with a higher deductible resulting in higher homeowner building and contents AF.
• The AF is relatively insensitive to freeboard; however, freeboard decreases total (building and contents) and homeowner AAL exponentially. Both the total and homeowner portions of AAL approach minimal values with a freeboard of 2 feet and above.

The specific findings of the spatial heterogeneity case study are:

• The flood hazard parameter (α) has a significant impact on the total AAL ($), homeowner AAL ($), and AF. Extremely lower α values align with deductible values, influencing the homeowner's portion of the risk.
• Results show a limited impact of coverage on AAL and AF values, a significant influence of deductibles on homeowner AAL and AF, and the effect of unit replacement cost on total AAL and AF.
• The multiple linear regression (MLR) model provides reasonable results but struggles to capture nonlinear behavior.
• The classification and regression tree (CART) model significantly improves performance.

The findings of this research are very promising, as a subsequent study might find that homeowner AAL proportion can be reasonably pre-calculated and applied to total AAL value, which is relatively straightforward to calculate. This capability would facilitate estimation of flood losses experienced by homeowners, particularly if uncertainty can be incorporated, supporting research that attempts to understand adaptive strategies in flood risk management and factors affecting flood loss recovery and mitigation decisions in their proper context.

To see the results in detail and read more about our peer-reviewed publication on this research click on the link below:

Analytical advances in homeowner flood risk quantification considering insurance, building replacement value, and freeboard

Rahim, M.A., Friedland, C.J., Mostafiz, R.B., Rohli, R.V., and Bushra, N. (2023). Analytical advances in homeowner flood risk quantification considering insurance, building replacement value, and freeboard. Frontiers in Environmental Science, 11, Art. No. 1180942. doi: 10.3389/fenvs.2023.1180942