A Data-driven, Probabilistic, Multiple Return Period Method of Flood Depth Estimation

Mostafiz, Rubayet Bin; Friedland, Carol J.; Rahim, Md Adilur; Rohli, Robert V.; Bushra, Nazla

doi:10.1002/essoar.10509337.1

Cited by 17 publications

(21 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Not surprisingly given the paucity of updated scientific work on flood, few if any historical records of such estimates may exist to guide construction, protection, or restoration efforts. Thus, reliance on hydrologic and hydraulic modeling of flood events as a function of AEP is necessary (Mostafiz et al, 2021c ). However, relatively flood-safe areas often have “null” (i.e., zero or negative) depth values at modeled return periods, even while vulnerability remains substantial during the life span of the infrastructure (Mostafiz et al, 2021c ).…”

Section: Introductionmentioning

confidence: 99%

“…The overarching goal of this research is to characterize flood hazards at locations both inside and outside the SFHA. More specifically, the research addresses the question, “If no modeled flood data exist for some or all return periods, what are the flood characteristics?” To that end, this research introduces a method for describing flood hazards whereby the flood is characterized using the Gumbel extreme value distribution (Waylen and Woo, 1982 ; Nadarajah and Kotz, 2004 ; Al Assi et al, 2022b ), and flood elevations are projected at higher return periods (Mostafiz et al, 2021c ). The gaps in flood surfaces due to limited data are filled by spatial interpolation techniques.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A data-driven spatial approach to characterize the flood hazard

et al. 2022

View full text Add to dashboard Cite

Model output of localized flood grids are useful in characterizing flood hazards for properties located in the Special Flood Hazard Area (SFHA—areas expected to experience a 1% or greater annual chance of flooding). However, due to the unavailability of higher return-period [i.e., recurrence interval, or the reciprocal of the annual exceedance probability (AEP)] flood grids, the flood risk of properties located outside the SFHA cannot be quantified. Here, we present a method to estimate flood hazards that are located both inside and outside the SFHA using existing AEP surfaces. Flood hazards are characterized by the Gumbel extreme value distribution to project extreme flood event elevations for which an entire area is assumed to be submerged. Spatial interpolation techniques impute flood elevation values and are used to estimate flood hazards for areas outside the SFHA. The proposed method has the potential to improve the assessment of flood risk for properties located both inside and outside the SFHA and therefore to improve the decision-making process regarding flood insurance purchases, mitigation strategies, and long-term planning for enhanced resilience to one of the world's most ubiquitous natural hazards.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A data-driven spatial approach to characterize the flood hazard

et al. 2022

View full text Add to dashboard Cite

show abstract

“…The site-specific u and α are corrected according to Mostafiz et al (2021) so that the u parameter at each cell overlying the structure is negative. The u value should be negative for most residential buildings, as flood depth at lower return period flood event would only be possible for waterlogged terrain.…”

Section: Characterizing Flood Hazardmentioning

confidence: 99%

Improved building-specific flood risk assessment and implications of depth-damage function selection

et al. 2022

Self Cite

View full text Add to dashboard Cite

Average annual loss (AAL) is traditionally used as the basis of assessing flood risk and evaluating risk mitigation measures. This research presents an improved implementation to estimate building-specific AAL, with the flood hazard of a building represented by the Gumbel extreme value distribution. AAL is then calculated by integrating the area under the overall loss-exceedance probability curve using trapezoidal Riemann sums. This implementation is compared with existing AAL estimations from flood risk assessment. A sensitivity analysis is conducted to examine the variability in AAL results based on depth-damage function (DDF) choice. To demonstrate the methodology, a one-story single-family residence is selected to assess the financial benefits of freeboard (i.e., increasing lowest floor elevations). Results show that 1 ft. of freeboard results in annual flood risk reduction of over $1,000, while 4 ft of freeboard results in annual flood risk reduction of nearly $2,000. The sensitivity result suggests that the DDF selection is critical, as a large proportion of flood loss is counted below the top of the first floor. The findings of this paper will enhance DDF selection, improve flood loss estimates, encourage homeowners and communities to invest in flood mitigation, and provide government decision-makers with improved information when considering building code changes.

show abstract

“…The building AAL (𝐴𝐴𝐿 ) is estimated using the method presented in Gnan (2021) and Gnan et al (2022a). Flood depths derived from Monte Carlo simulations (e.g., Brodie, 2013;Hennequin et al, 2018;Kind, 2014;Kind et al, 2020;Qi et al, 2013;Rahim et al, 2021Rahim et al, , 2022aRahman et al, 2002;Taghinezhad et al, 2020;Yu et al, 2013) with the fitted Gumbel extreme value distribution (e.g., Al Assi et al, 2022;Bhat et al, 2019;Gnan et al, 2022b;Kim & Lee, 2021;Manfreda et al, 2021;Mostafiz et al, 2021a;2022b;Rahim et al, 2022b;Singh et al, 2018) are translated to building loss percentages using the U.S. Army Corps of Engineers (USACE; 2000) depth-damage function (DDF) designed for the home's attributes (e.g., onestory or two-or-more stories, with or without basement). The loss percentages are then multiplied by the structure replacement cost (i.e., building value, 𝐵𝑉), and the average of the resulting losses of all Monte Carlo-simulated flooding events is the AAL.…”

Section: Building Aalmentioning

confidence: 99%

Freeboard Life-Cycle Benefit-Cost Analysis of a Rental Single-family Residence for Landlord, Tenant, and Insurer

Gnan

Mostafiz

Rahim

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

Abstract. Flood risk to single-family rental housing remains poorly understood, leaving a large and increasing population underinformed to protect themselves, including regarding insurance. This research introduces a life-cycle benefit-cost analysis for the landlord, tenant, and insurer (i.e., National Flood Insurance Program (NFIP)) to optimize freeboard (i.e., additional first-floor height above the base flood elevation (BFE)) selection for a rental single-family home. Flood insurance premium; apportioned flood risk among the landlord, tenant, and NFIP by insurance coverage and deductible; rental loss; moving and displacement costs; freeboard construction cost; and rent increase upon freeboard implementation are considered in estimating net benefit (NB) by freeboard. For a 2,500 square-foot case study home in Metairie, Louisiana, a two-foot freeboard optimizes the combined savings for landlord and tenant, with joint life-cycle NB of $23,658 and $14,978, for a 3 % and 7 % real discount rate, respectively. Any freeboard up to 2.5 feet benefits the tenant and NFIP, while the landlord benefits for freeboards up to 4.0 feet. Collectively, results suggest that at the time of construction, even minimal freeboard provides substantial savings for the landlord, tenant, and NFIP. The research provides actionable information, supporting the decision-making process for landlords, tenants, and others, thereby enhancing investment and occupation decisions.

show abstract

A Data-driven, Probabilistic, Multiple Return Period Method of Flood Depth Estimation

Cited by 17 publications

References 0 publications

A data-driven spatial approach to characterize the flood hazard

A data-driven spatial approach to characterize the flood hazard

Improved building-specific flood risk assessment and implications of depth-damage function selection

Freeboard Life-Cycle Benefit-Cost Analysis of a Rental Single-family Residence for Landlord, Tenant, and Insurer

Contact Info

Product

Resources

About