Application of a Large‐Scale Terrain‐Analysis‐Based Flood Mapping System to Hurricane Harvey

Zheng, Xiong; D'Angelo, Claudia; Maidment, David R.; Passalacqua, Paola

doi:10.1111/1752-1688.12987

Cited by 10 publications

(5 citation statements)

References 18 publications

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“…Thus far, FACET outputs and its predecessor the Stream Channel and Floodplain Metric Toolbox (Hopkins, Lamont, et al, 2018) have been incorporated into modeling to estimate streambank sediment fluxes at local (Hopkins, Noe, et al, 2018) and regional scales (Noe et al, 2022). FACET outputs such as channel metrics and HAND grids may provide useful inputs for emerging approaches to regional flood inundation mapping which have used HAND methods in combination with synthetic rating curves (Ghanghas et al, 2022) or HAND in combination with high water marks from extreme weather events such as hurricanes (Zheng et al, 2022). Others have attempted to use HAND to derive hydraulic properties essential to hydraulic models, replacing the need for cross‐sectional measurements (Zheng, Tarboton, et al, 2018), which are typically obtained from field measurements of cross sections or regionally developed regression equations to predict bankfull depth and width.…”

Section: Discussionmentioning

confidence: 99%

Mapping stream and floodplain geomorphometry with the Floodplain and Channel Evaluation Tool

Hopkins,

Ahmed,

Claggett

et al. 2023

J American Water Resour Assoc

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Broad‐scale mapping of stream channel and floodplain geomorphic metrics is critical to improve the understanding of geomorphic change, biogeochemical processes, riverine habitat quality, and opportunities for management intervention. The Floodplain and Channel Evaluation Tool (FACET) was developed to provide an open‐source tool for automated processing of digital elevation models (DEMs) to generate regional‐scale estimates of bank height, channel width, floodplain width, and a suite of other fluvial geomorphic dimensions that can be summarized at the stream reach‐ or catchment‐scale. FACET was tested on 3‐m DEMs covering the Delaware River watershed and 85% of the Chesapeake Bay watershed in the United States (U.S.) and on 1‐m DEMs for a subset of the study area. Accuracy was assessed from data collected at 67 field sites in the study area. FACET successfully measured geomorphometry for over 270,000 stream reaches (88% of streams attempted) in the study area. Factors that reduced the ability of FACET to accurately estimate geomorphic metrics included errors in DEM hydro‐conditioning, gradually sloping banks, incised stream channels, and the use of fixed input parameters to define buffer lengths. Even with these limitations, FACET was able to map regional patterns in stream and floodplain geomorphometry providing a robust dataset that can enhance modeling and management efforts throughout the mid‐Atlantic region, U.S.

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Section: Discussionmentioning

confidence: 99%

Mapping stream and floodplain geomorphometry with the Floodplain and Channel Evaluation Tool

Hopkins,

Ahmed,

Claggett

et al. 2023

J American Water Resour Assoc

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“…where TP is true positive, TN is true negative, FP is false positive, and FN is false negative. We do not further test GeoFlood since it has been done in previous publications (Zheng et al, 2018a(Zheng et al, , 2022.…”

Section: Validation Metricsmentioning

confidence: 99%

c-HAND: near real-time coastal flood mapping

Wang,

Passalacqua,

Cai

et al. 2024

Front. Water

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The Texas Gulf Coast region contains significant centers of population, infrastructure, and economy and is threatened by intensifying tropical storms. The flooding from these tropical storms often has multiple compounding drivers. This characteristic presents a complex numerical problem where a simulation must consider multiple hydrologic forcings. While several procedures exist for addressing this problem numerically, they tend to be resource-intensive and cannot be conducted in near real-time. We extend GeoFlood, a reduced physics approach for fluvial flood forecasting, to rapidly predict coastal and compound fluvial-coastal inundation. This method is validated against a numerical ocean circulation model (ADCIRC) simulation of Hurricane Ike, a major coastal flooding event that happened on the Texas Gulf Coast in 2008. We show that the inundation map generated by coastal HAND (c-HAND) has reasonable agreement with the ADCIRC simulation while taking about 1.7% of the time currently needed to run ADCIRC on a supercomputer. While our model correctly predicts 99% of ADCIRC-inundated DEM cells, it also overpredicts inundated area by a factor of approximately 27%. We combine c-HAND with the GeoFlood framework for fluvial flood forecasting to create a compound fluvial-coastal inundation mapping workflow that can be run in near real-time. c-HAND's fast wall-clock time and low CPU requirements can support decision making by first response personnel. The method provides timely and convenient access to crucial information, such as the locations of flooded roads and inundated coastal areas.

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“…GeoFlood has been shown to capture the general fluvial inundation patterns of flood events, with inundation extents overlapping with 60 %-90 % of FEMA inundation extents (Zheng et al, 2018(Zheng et al, , 2022. To compare Fill-Spill-Merge and our pluvial inundation estimates to a full hydrodynamic model, we employed a physically based 2D hydrodynamic model by using the software ProMaIDes (Protection Measures against Inundation Decision support).…”

Section: Pluvial Flooding Comparisonmentioning

confidence: 99%

Intersecting near-real time fluvial and pluvial inundation estimates with sociodemographic vulnerability to quantify a household flood impact index

Preisser

Passalacqua²,

Bixler

et al. 2022

Hydrol. Earth Syst. Sci.

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Abstract. Increased interest in combining compound flood hazards and social vulnerability has driven recent advances in flood impact mapping. However, current methods to estimate event-specific compound flooding at the household level require high-performance computing resources frequently not available to local stakeholders. Government and non-governmental agencies currently lack the methods to repeatedly and rapidly create flood impact maps that incorporate the local variability in both hazards and social vulnerability. We address this gap by developing a methodology to estimate a flood impact index at the household level in near-real time, utilizing high-resolution elevation data to approximate event-specific inundation from both pluvial and fluvial sources in conjunction with a social vulnerability index. Our analysis uses the 2015 Memorial Day flood in Austin, Texas, as a case study and proof of concept for our methodology. We show that 37 % of the census block groups in the study area experience flooding from only pluvial sources and are not identified in local or national flood hazard maps as being at risk. Furthermore, averaging hazard estimates to cartographic boundaries masks household variability, with 60 % of the census block groups in the study area having a coefficient of variation around the mean flood depth exceeding 50 %. Comparing our pluvial flooding estimates to a 2D physics-based model, we classify household impact accurately for 92 % of households. Our methodology can be used as a tool to create household compound flood impact maps to provide computationally efficient information to local stakeholders.

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Application of a Large‐Scale Terrain‐Analysis‐Based Flood Mapping System to Hurricane Harvey

Cited by 10 publications

References 18 publications

Mapping stream and floodplain geomorphometry with the Floodplain and Channel Evaluation Tool

Mapping stream and floodplain geomorphometry with the Floodplain and Channel Evaluation Tool

c-HAND: near real-time coastal flood mapping

Intersecting near-real time fluvial and pluvial inundation estimates with sociodemographic vulnerability to quantify a household flood impact index

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