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Hindcast of pluvial, fluvial, and coastal flood damage in Houston, Texas during Hurricane Harvey (2017) using SFINCS

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Abstract

As demonstrated by recent tropical cyclone events, including U.S. Hurricanes Harvey, Irma, and Maria (2017), and Florence (2018), the destructive potential of flooding driven by wind, precipitation, and coastal surge coupled with growing exposure of people and property along coastlines is leading to unprecedented damage from coastal storms. In this paper, we demonstrate the ability of the recently developed Super-Fast INundation of CoastS (SFINCS) model to delineate the depth and extent of flooding during Hurricane Harvey in Houston, Texas. The model was validated against water level time-series at twenty-one United States Geological Survey (USGS) observation points and 115 high water mark locations. FEMA depth-damage curves were used to estimate building and content damages from the combined flood sources (e.g., pluvial, fluvial, and marine) and total losses are compared against insurance claims registered with the U.S. National Flood Insurance Program (NFIP) and a depth grid produced during the U.S. Federal Emergency Management Agency’s (FEMA) Preliminary Damage Assessment (PDA). The results suggest that Harvey may have caused upwards of $8.3 billion USD in uninsured residential loss within the model domain. Comparison against FEMA’s PDA indicates that the SFINCS model predicts much larger total losses, indicating that the incorporation of spatially-distributed pluvial hazards into the modeling method is critical for identifying high-risk areas and supports the need for further flood risk analyses in the region.

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Unless otherwise noted in the methods, the data used in the analysis are publicly available as follows: (i) the U.S. Geological Survey (USGS) 3D Elevation Program (3DEP) National Elevation Dataset (NED) (https://viewer.nationalmap.gov/basic/) and (ii) the U.S. Coastal Relief Model (CRM) Vol. 5–Western Gulf of Mexico (https://www.ngdc.noaa.gov/mgg/coastal/crm.html) were used to build the model domain; (iii) Houston-Galveston Area Council (H-GAC) land cover data set (http://www.h-gac.com/land-use-and-land-cover-data/default.aspx) was used to generate raster grids representing overland roughness; (iv) Harris County Flood Control District (HCFCD) sensor data (https://www.harriscountyfws.org/) was used to obtain 15-minute precipitation accumulation; (v) USGS stage hydrographs (https://waterdata.usgs.gov/) were used to validate the model formulation; (vi) high water mark (HWM) were obtained from the USGS Flood Event Viewer (https://stn.wim.usgs.gov/fev/); (vii) a 1-meter DEM from the Texas Natural Resource Information System (TNRIS) Strategic Mapping Program (StratMap) for the Upper Texas Coast (https://data.tnris.org/) was used to downscale modeled water depths; (viii) Harris County Appraisal District (HCAD) parcel data (https://pdata.hcad.org/) and (ix) Microsoft U.S. Building Footprints (https://github.com/microsoft/USBuildingFootprints) were used to build a structures database; and (x) FEMA depth-damage curves were obtained from the Hazus-Flood Assessment Structure Tool (FAST) via GitHub (https://github.com/nhrap-hazus/FAST).

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Acknowledgments

The authors would like to acknowledge Dr. Y.(V.) Wang for his help with coding and revising the uncertainty analysis. The authors would also like to thank two anonymous reviewers for their valuable feedback during the submission and editing process of this manuscript. This manuscript is the result of thesis work by D.J.B. which can be found in the Delft University of Technology digital repository. A.S. received funding from NSF PIRE Grant No. OISE-145837 to support international collaboration and the Texas General Land Office Contract No. 9-181-000-B574 to advance scientific understanding of flood risk in Southeast Texas. D.J.B., C.M.N., T.W.B.L. received funding from the Deltares research program "Quantifying Flood Hazards and Impacts" (Project 616 No. 1123750) for development of the SFINCS model and to write the manuscript.

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Authors and Affiliations

  1. Department of Earth, Marine and Environmental Sciences, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA

    A. Sebastian

  2. Department of Marine Sciences, Texas A&M University at Galveston, Galveston, Texas, USA

    A. Sebastian

  3. Department of Hydraulic Engineering, Delft University of Technology, Delft, The Netherlands

    D. J. Bader, J. D. Bricker & S. G. J. Aarninkhof

  4. Deltares, Marine and Coastal Systems, Boussinesqweg 1, 2629 HV, Delft, The Netherlands

    D. J. Bader & T. W. B. Leijnse

  5. Deltares USA, 8601 Georgia Ave, Silver Spring, MD, 20910, USA

    C. M. Nederhoff

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Contributions

D.J.B. constructed the SFINCS model and provided the preliminary results. A.S., D.J.B. and C.M.N. analyzed the model results and wrote the initial draft of the manuscript. C.M.N. and T.W.B.L. developed the SFINCS model code. A.S., C.M.N., T.W.B.L., J.D.B., and S.G.J.A. served on the thesis committee of D.J.B. All authors contributing to revisions and gave final approval for publication.

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Correspondence to A. Sebastian.

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Sebastian, A., Bader, D.J., Nederhoff, C.M. et al. Hindcast of pluvial, fluvial, and coastal flood damage in Houston, Texas during Hurricane Harvey (2017) using SFINCS. Nat Hazards 109, 2343–2362 (2021). https://doi.org/10.1007/s11069-021-04922-3

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