Scale and Resolution Considerations in the Application of HAZUS-MH 2.1 to Flood Risk Assessments

Banks, James Carl; Camp, Janey; Abkowitz, Mark

doi:10.1061/(asce)nh.1527-6996.0000160

Cited by 14 publications

(7 citation statements)

References 4 publications

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“…The results presented here for the exposed domain show a positive or neutral bias of the six metrics of interest overall, similar to flood risk model comparison studies (Table 1) and a growing body of work on hydrodynamic models (Banks et al, 2015;Ghimire & Sharma, 2021;Mohanty et al, 2020;Muthusamy et al, 2021;Saksena & Merwade, 2015). While our work stops short of computing risk or impact metrics, the remarkable four-fold increase in exposed assets we find provides a logical, albeit partial, explanation for the bias reported by these studies.…”

Section: Discussionsupporting

confidence: 85%

“…Because of the computational demands of such models, resolution has been extensively studied and found to be one of the parameters of most importance for accuracy (Alipour et al., 2022; Fewtrell et al., 2008; Papaioannou et al., 2016; Savage et al., 2016). Focusing on the relationship between model resolution and inundation area, many studies of fluvial floods find a positive inundation area and flood depth bias at coarser resolutions (Banks et al., 2015; Ghimire & Sharma, 2021; Mohanty et al., 2020; Muthusamy et al., 2021; Saksena & Merwade, 2015; Xafoulis et al., 2023) while studies of urban flooding are less conclusive (Fewtrell et al., 2008). For the underlying terrain model grids or digital elevation models (DEM), the resampling method used to generate the coarse analogs is often found to be of little significance (Muthusamy et al., 2021; Saksena & Merwade, 2015) except at high resolutions when buildings are present in the fine DEM (Fewtrell et al., 2008).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Bias in Flood Hazard Grid Aggregation

Bryant,

Kreibich,

Merz

2023

Water Resources Research

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Reducing flood risk through disaster planning and risk management requires accurate estimates of exposure, damage, casualties, and environmental impacts. Models can provide such information; however, computational or data constraints often lead to the construction of such models by aggregating high‐resolution flood hazard grids to a coarser resolution, the effect of which is poorly understood. Through the application of a novel spatial classification framework, we derive closed‐form solutions for the location (e.g., flood margins) and direction of bias from flood grid aggregation independent of any study region. These solutions show bias of some key metric will always be present in regions with marginal inundation; for example, inundation area will be positively biased when water depth grids are aggregated and volume will be negatively biased when water surface elevation grids are aggregated through averaging. In a separate computational analysis, we employ the same framework to a 2018 flood and successfully reproduce the findings of our study‐region‐independent derivation. Extending the investigation to the exposure of buildings, we find regions with marginal inundation are an order of magnitude more sensitive to aggregation errors, highlighting the importance of understanding such artifacts for flood risk modellers. Of the two aggregation routines considered, averaging water surface elevation grids better preserved flood depths at buildings than averaging of water depth grids. This work provides insight into, and recommendations for, aggregating grids used by flood risk models.This article is protected by copyright. All rights reserved.

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Section: Discussionsupporting

confidence: 85%

Section: Introductionmentioning

confidence: 99%

Bias in Flood Hazard Grid Aggregation

Bryant,

Kreibich,

Merz

2023

Water Resources Research

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“…Hazus-MH can estimate floodplains using a single discharge value or, after allowing the program to make hydrologic calculations, any return period from one to 500 years; this study employs both the 100-year and 500-year flood levels. This process is suitable for county-level estimations of flood extent, but generally unsuitable for use at smaller scales (Banks et al 2015 While using level one Hazus-MH analyses to delineate floodplains is a relatively easy task, the simplicity of only needing to provide a DEM comes at the cost of accuracy. Hazus-MH level one analyses tend to underestimate the extent of floodplains (Gall et al 2007;Ding et al 2008;Banks et al 2015).…”

Section: Floodmentioning

confidence: 99%

“…This process is suitable for county-level estimations of flood extent, but generally unsuitable for use at smaller scales (Banks et al 2015 While using level one Hazus-MH analyses to delineate floodplains is a relatively easy task, the simplicity of only needing to provide a DEM comes at the cost of accuracy. Hazus-MH level one analyses tend to underestimate the extent of floodplains (Gall et al 2007;Ding et al 2008;Banks et al 2015). Additionally, there is evidence that the regulatory floodplains are underestimates as well (Criss 2016).…”

Section: Floodmentioning

confidence: 99%

Spatiotemporal analysis of residential flood exposure in the Atlanta, Georgia metropolitan area

Ferguson

Ashley

2017

Nat Hazards

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Financial losses due to flooding have increased substantially over the past several decades. Previous research implies that flood losses are rising due to changes in precipitation and increases in exposure. While prior research has explored changes in floodplain exposure at the county level, few efforts have examined patterns across an entire metropolitan area. This thesis examines changes in residential built-environment flood exposure within the current boundaries of the Atlanta, Georgia metropolitan statistical area by estimating the number of housing units that are located within the floodplains of the region. Housing unit data at the block level from the 1990-2010 decennial censuses are used to estimate housing unit exposure to floods using a binary dasymetric and proportional allocation method. Due to concerns about flood model accuracy and the fact that regulatory 500-year floodplains have not yet been delineated for all parts of the study area, three different representations of the 100-year (1 percent annual chance) and 500-year (0.2 percent annual chance) floodplain are employed: the generally more conservative floodplains created using the Federal Emergency Management Agency's Hazus-MH software, the generally more extensive floodplains included in the proprietary Flood Hazard Data product from KatRisk LLC and the regulatory floodplains from the NFIP. It was found that residential exposure within both the 100 and 500-year floodplain increased from 1990-2010 throughout the Atlanta region. The NFIP appeared to be marginally effective overall. Regulatory 100-year floodplain development was most likely to be favored over development outside the floodplain where overall development was strong or on the edge of the developing area. Development within the marginal 500-year was favored near the core of the urban area. Results using the KatRisk product reveal both greater overall exposure and a greater increase in exposure within the 100-year floodplain than the regulatory product suggests. Overall, the results argue that heightened flood exposure is, along with changes in precipitation and runoff, an important factor to consider when addressing the impact of the flood hazard.

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“…We calculated the direct economic losses using HAZUS (HAZard USa), a software developed by the Federal Emergency Management Agency (FEMA, 2003), to calculate economic losses associated with different natural disasters, including floods (see, among others, Ding et al, 2008;Banks et al, 2014;Gutenson et al, 2015). We used HAZUS-MH to calculate how the HEC-RAS simulated flooding led to direct economic losses to agriculture (crops), buildings and public infrastructure such as telecommunication lines and roads.…”

Section: Methodsmentioning

confidence: 99%

Tracking an atmospheric river in a warmer climate: from water vapor to economic impacts

et al. 2018

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Abstract. Atmospheric rivers (ARs) account for more than 75 % of heavy precipitation events and nearly all of the extreme flooding events along the Olympic Mountains and western Cascade Mountains of western Washington state. In a warmer climate, ARs in this region are projected to become more frequent and intense, primarily due to increases in atmospheric water vapor. However, it is unclear how the changes in water vapor transport will affect regional flooding and associated economic impacts. In this work we present an integrated modeling system to quantify the atmospheric-hydrologic-hydraulic and economic impacts of the December 2007 AR event that impacted the Chehalis River basin in western Washington. We use the modeling system to project impacts under a hypothetical scenario in which the same December 2007 event occurs in a warmer climate. This method allows us to incorporate different types of uncertainty, including (a) alternative future radiative forcings, (b) different responses of the climate system to future radiative forcings and (c) different responses of the surface hydrologic system. In the warming scenario, AR integrated vapor transport increases; however, these changes do not translate into generalized increases in precipitation throughout the basin. The changes in precipitation translate into spatially heterogeneous changes in sub-basin runoff and increased streamflow along the entire Chehalis main stem. Economic losses due to stock damages increase moderately, but losses in terms of business interruption are significant. Our integrated modeling tool provides communities in the Chehalis region with a range of possible future physical and economic impacts associated with AR flooding.

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Scale and Resolution Considerations in the Application of HAZUS-MH 2.1 to Flood Risk Assessments

Cited by 14 publications

References 4 publications

Bias in Flood Hazard Grid Aggregation

Bias in Flood Hazard Grid Aggregation

Spatiotemporal analysis of residential flood exposure in the Atlanta, Georgia metropolitan area

Tracking an atmospheric river in a warmer climate: from water vapor to economic impacts

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