Damage Curves Derived from Hurricane Ike in the West of Galveston Bay Based on Insurance Claims and Hydrodynamic Simulations
Abstract Hurricane Ike, which struck the United States in September 2008, was the ninth most expensive hurricane in terms of damages. It caused nearly USD 30 billion in damage after making landfall on the Bolivar Peninsula, Texas. We used the Delft3d-FM/SWAN hydrodynamic and spectral wave model to s...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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SpringerOpen
2023-12-01
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| Series: | International Journal of Disaster Risk Science |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s13753-023-00524-8 |
| _version_ | 1797350151045513216 |
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| author | Chaoran Xu Benjamin T. Nelson-Mercer Jeremy D. Bricker Meri Davlasheridze Ashley D. Ross Jianjun Jia |
| author_facet | Chaoran Xu Benjamin T. Nelson-Mercer Jeremy D. Bricker Meri Davlasheridze Ashley D. Ross Jianjun Jia |
| author_sort | Chaoran Xu |
| collection | DOAJ |
| description | Abstract Hurricane Ike, which struck the United States in September 2008, was the ninth most expensive hurricane in terms of damages. It caused nearly USD 30 billion in damage after making landfall on the Bolivar Peninsula, Texas. We used the Delft3d-FM/SWAN hydrodynamic and spectral wave model to simulate the storm surge inundation around Galveston Bay during Hurricane Ike. Damage curves were established through the relationship between eight hydrodynamic parameters (water depth, flow velocity, unit discharge, flow momentum flux, significant wave height, wave energy flux, total water depth (flow depth plus wave height), and total (flow plus wave) force) simulated by the model and National Flood Insurance Program (NFIP) insurance damage data. The NFIP insurance database contains a large amount of building damage data, building stories, and elevation, as well as other information from the Ike event. We found that the damage curves are sensitive to the model grid resolution, building elevation, and the number of stories. We also found that the resulting damage functions are steeper than those developed for residential structures in many other locations. |
| first_indexed | 2024-03-08T12:41:36Z |
| format | Article |
| id | doaj.art-b19b9270c5ee48a288404b997530ae48 |
| institution | Directory Open Access Journal |
| issn | 2095-0055 2192-6395 |
| language | English |
| last_indexed | 2024-03-08T12:41:36Z |
| publishDate | 2023-12-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | International Journal of Disaster Risk Science |
| spelling | doaj.art-b19b9270c5ee48a288404b997530ae482024-01-21T12:08:47ZengSpringerOpenInternational Journal of Disaster Risk Science2095-00552192-63952023-12-0114693294610.1007/s13753-023-00524-8Damage Curves Derived from Hurricane Ike in the West of Galveston Bay Based on Insurance Claims and Hydrodynamic SimulationsChaoran Xu0Benjamin T. Nelson-Mercer1Jeremy D. Bricker2Meri Davlasheridze3Ashley D. Ross4Jianjun Jia5State Key Laboratory of Estuarine and Coastal Research, School of Marine Sciences, East China Normal UniversityDepartment of Civil and Environmental Engineering, University of MichiganDepartment of Civil and Environmental Engineering, University of MichiganDepartment of Marine and Coastal Environmental Science, Texas A&M University at GalvestonDepartment of Marine and Coastal Environmental Science, Texas A&M University at GalvestonState Key Laboratory of Estuarine and Coastal Research, School of Marine Sciences, East China Normal UniversityAbstract Hurricane Ike, which struck the United States in September 2008, was the ninth most expensive hurricane in terms of damages. It caused nearly USD 30 billion in damage after making landfall on the Bolivar Peninsula, Texas. We used the Delft3d-FM/SWAN hydrodynamic and spectral wave model to simulate the storm surge inundation around Galveston Bay during Hurricane Ike. Damage curves were established through the relationship between eight hydrodynamic parameters (water depth, flow velocity, unit discharge, flow momentum flux, significant wave height, wave energy flux, total water depth (flow depth plus wave height), and total (flow plus wave) force) simulated by the model and National Flood Insurance Program (NFIP) insurance damage data. The NFIP insurance database contains a large amount of building damage data, building stories, and elevation, as well as other information from the Ike event. We found that the damage curves are sensitive to the model grid resolution, building elevation, and the number of stories. We also found that the resulting damage functions are steeper than those developed for residential structures in many other locations.https://doi.org/10.1007/s13753-023-00524-8Delft3d-FMFlood riskHurricane IkeResidential damage ratioSWANWeibull function |
| spellingShingle | Chaoran Xu Benjamin T. Nelson-Mercer Jeremy D. Bricker Meri Davlasheridze Ashley D. Ross Jianjun Jia Damage Curves Derived from Hurricane Ike in the West of Galveston Bay Based on Insurance Claims and Hydrodynamic Simulations International Journal of Disaster Risk Science Delft3d-FM Flood risk Hurricane Ike Residential damage ratio SWAN Weibull function |
| title | Damage Curves Derived from Hurricane Ike in the West of Galveston Bay Based on Insurance Claims and Hydrodynamic Simulations |
| title_full | Damage Curves Derived from Hurricane Ike in the West of Galveston Bay Based on Insurance Claims and Hydrodynamic Simulations |
| title_fullStr | Damage Curves Derived from Hurricane Ike in the West of Galveston Bay Based on Insurance Claims and Hydrodynamic Simulations |
| title_full_unstemmed | Damage Curves Derived from Hurricane Ike in the West of Galveston Bay Based on Insurance Claims and Hydrodynamic Simulations |
| title_short | Damage Curves Derived from Hurricane Ike in the West of Galveston Bay Based on Insurance Claims and Hydrodynamic Simulations |
| title_sort | damage curves derived from hurricane ike in the west of galveston bay based on insurance claims and hydrodynamic simulations |
| topic | Delft3d-FM Flood risk Hurricane Ike Residential damage ratio SWAN Weibull function |
| url | https://doi.org/10.1007/s13753-023-00524-8 |
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