Comparison of Neighborhood-Scale, Residential Property Flood-Loss Assessment Methodologies

Abstract

Leading flood loss estimation models include Federal Emergency Management Agency’s (FEMA’s) Hazus, FEMA’s Flood Assessment Structure Tool (FAST), and (U.S.) Hydrologic Engineering Center’s Flood Impact Analysis (HEC-FIA), with each requiring different data input. No research to date has compared the resulting outcomes from such models at a neighborhood scale. This research examines the building and content loss estimates by Hazus Level 2, FAST, and HEC-FIA, over a levee-protected census block in Metairie, in Jefferson Parish, Louisiana. Building attribute data in National Structure Inventory (NSI) 2.0 are compared against “best available data” (BAD) collected at the individual building scale from Google Street View, Jefferson Parish building inventory, and 2019 National Building Cost Manual, to assess the sensitivity of input building inventory selection. Results suggest that use of BAD likely enhances flood loss estimation accuracy over existing reliance on default data in the software or from a national data set that generalizes over a broad scale. Although the three models give similar mean (median) building and content loss, Hazus Level 2 results diverge from those produced by FAST and HEC-FIA at the individual building level. A statistically significant difference in mean (median) building loss exists, but no significant difference is found in mean (median) content loss, between building inventory input (i.e., NSI 2.0 vs BAD), but both the building and content loss vary at the individual building scale due to difference in building-inventory-reported foundation height, foundation type, number of stories, replacement cost, and content cost. Moreover, building loss estimation also differs significantly by depth-damage function (DDF), for flood depths corresponding with the longest return periods, with content loss differing significantly by DDF at all return periods tested, from 10 to 500 years. Knowledge of the extent of estimated differences aids in understanding the degree of uncertainty in flood loss estimation. Much like the real estate industry uses comparable home values to appraise a home, flood loss planners should use multiple models to estimate flood-related losses. Moreover, results from this study can be used as a baseline for assessing losses from other hazards, thereby enhancing protection of human life and property.

Property Risk Assessment of Sinkhole Hazard in Louisiana, U.S.A

“…Although the total loss from the sinkhole hazard is small compared to losses due to other Louisiana hazards, such as extreme heat and cold (Mostafiz et al, 2020a;2020b), expansive soils (Mostafiz et al, 2021a), wildfire (Mostafiz et al, 2021b), and flood (Mostafiz et al, 2021c;2021d), these losses are nevertheless important to document as part of a complete hazard mitigation plan. Furthermore, the localized nature of this hazard, in contrast to others, which are statewide problems, causes the calculation of a statewide mean per capita loss to appear small.…”

Economically optimizing elevation of new, single-family residences for flood mitigation via life-cycle benefit-cost analysis

“…Likewise, USACE (2015) offers other advantages, but because it was designed for the North Atlantic Coast, its DDFs are developed considering inundation, waves, and erosion mechanisms for different building prototypes. Thus, the more generic DDFs in USACE (2000) for inland flooding are selected here, and sensitivity to the issue of selection of DDF is not included in this analysis, but it could affect the outcome of results substantially (Mostafiz et al, 2021b).…”

Actionable Information in Flood Risk Communications and the Potential for New Web-Based Tools for Long-Term Planning for Individuals and Community

“…Technological advances and enhanced grassroots efforts have traditionally improved communications regarding the flood risk, before, during, and after flood disasters. Such endeavors via mass media, citizen science, and social media are helpful but continue to fall short in some ways, as evidenced by the fact that losses in flood-prone areas continue to increase (Mostafiz et al, 2021b(Mostafiz et al, , 2021c.…”