Homeowner Flood Risk and Risk Reduction from Home Elevation between the 100- and 500-year Floodplains

Abstract

Floods inflict significant damage even outside the 100-year floodplain. Thus, restricting flood risk analysis to the 100-year floodplain (special flood hazard area (SFHA) in the U.S.A.) is misleading. Flood risk outside the SFHA is often underestimated because of minimal floodrelated insurance requirements and regulations and sparse flood depth data. This study proposes a systematic approach to predict flood risk for a single-family home using average annual loss (AAL) in the shaded X Zonethe area immediately outside the SFHA (i.e., the 500-year floodplain), which lies between the 1.0-and 0.2-percent annual flood probability. To further inform flood mitigation strategy, annual flood risk reduction with additional elevation above an initial first-floor height (𝐹𝐹𝐻 0 ) is estimated. The proposed approach generates synthetic flood parameters, quantifies AAL for a hypothetical slab-on-grade, single-family home with varying attributes and scenarios above the slab-on-grade elevation, and compares flood risk for two areas using the synthetic flood parameters vs. an existing spatial interpolation-estimated flood parameters. Results reveal a median AAL in the shaded X Zone of 0.13 and 0.17 percent of replacement cost value (𝑉 𝑅 ) for a one-story, single-family home without and with basement, respectively, at 𝐹𝐹𝐻 0 and 500-year flood depth < 1 foot. Elevating homes one and four feet above 𝐹𝐹𝐻 0 substantially mitigates this risk, generating savings of 0.07-0.18 and 0.09-0.23 percent of 𝑉 𝑅 for a one-story, single-family home without and with basement, respectively. These results enhance understanding of flood risk and the benefits of elevating homes above 𝐹𝐹𝐻 0 in the shaded X Zone.

Flood risk assessment for residences at the neighborhood scale by owner/occupant type and first-floor height

“…In the next 30 years, flood-related property damage may increase by 60% as a result of climate change (Sastry, 2021 ), and many communities and individuals underestimate the potential for flood damage (Burningham et al, 2008 ; Mol et al, 2020 ). Therefore, many researchers worldwide have focused on flood risk and loss assessments (e.g., Dutta et al, 2003 ; Scawthorn et al, 2006 ; Tam et al, 2014 ; Afifi et al, 2019 ; Mostafiz et al, 2021a , d ; Al Assi et al, 2022a , b ; Jin et al, 2022 ; Rahim et al, 2022a , b ) and the value of mitigating the flood risk (Taghinezhad et al, 2020 ).…”

A data-driven spatial approach to characterize the flood hazard

“…Consequences of this gap in scientific analysis ripple into many facets of flood awareness, communication, modeling, planning, preparation, and recovery (Huang and Xiao, 2015 ). Thus, improved quantification of flood hazards, and therefore flood risk, is crucial not only for its own sake, but also for the benefit of other, related efforts to reduce flood-induced losses to life and property (Merz et al, 2014 ; Mostafiz et al, 2021b , 2022a ; Al Assi et al, 2022a ; Gnan et al, 2022a ; Rahim et al, 2022a ).…”

Automated first floor height estimation for flood vulnerability analysis using deep learning and Google Street View

“…The results showed that the water depth above the first finished floor is strongly correlated with total building damage ratios. Some recent studies have applied FFH indirectly or directly along with the number of stories, basement existence, area, and unit area repair cost in USD to calculate the average annual loss in Louisiana, USA (Al Assi, Mostafiz, Friedland, Rahim, & Rohli, 2023; Al Assi, Mostafiz, Friedland, Rohli, & Rahim, 2023; Gnan et al, 2022). Another application of FFH is in flood insurance models and setting premium policies, for example, Flood Risk 2.0 is a flood insurance model introduced by FEMA.…”