Research article

South Texas coastal area storm surge model development and improvement

  • Received: 01 June 2020 Accepted: 17 July 2020 Published: 21 July 2020
  • The intensification of climatic changes, mainly natural geophysical hazards like hurricanes, are of great interest to the South Texas region. Scientists and engineers must protect essential resources from coastal threats, such as storm surge. This study presents the development process and improvements of a hydrodynamic finite element model that covers the South Texas coast, specifically the Lower Laguna Madre, for the aid of local emergency management teams. Four historical tropical cyclone landfalls are evaluated and used as a means of verification of the hydrodynamic model simulation results. The parameters used to improve the accuracy of the model are the tidal harmonic constituents and the surface roughness coefficient, or manning’s n value. A total of four different scenarios that use a variety of tidal constituent combinations and nodal attribute files were developed to identify the best case. Statistical evaluation, such as regression analysis, normalized root mean square error, and scatter index, was used to determine the significance of each hydrodynamic computational storm surge result with observed historical water surface elevations. In an effort to improving all models locally, using seven tidal constituents combinations along with a surface roughness nodal attribute grid that assigns values with respect to bathymetric data improves the accuracy of the storm surge model and should, therefore, be implemented for future hydrodynamic studies in the South Texas region.

    Citation: Sara E. Davila, Cesar Davila Hernandez, Martin Flores, Jungseok Ho. South Texas coastal area storm surge model development and improvement[J]. AIMS Geosciences, 2020, 6(3): 271-290. doi: 10.3934/geosci.2020016

    Related Papers:

  • The intensification of climatic changes, mainly natural geophysical hazards like hurricanes, are of great interest to the South Texas region. Scientists and engineers must protect essential resources from coastal threats, such as storm surge. This study presents the development process and improvements of a hydrodynamic finite element model that covers the South Texas coast, specifically the Lower Laguna Madre, for the aid of local emergency management teams. Four historical tropical cyclone landfalls are evaluated and used as a means of verification of the hydrodynamic model simulation results. The parameters used to improve the accuracy of the model are the tidal harmonic constituents and the surface roughness coefficient, or manning’s n value. A total of four different scenarios that use a variety of tidal constituent combinations and nodal attribute files were developed to identify the best case. Statistical evaluation, such as regression analysis, normalized root mean square error, and scatter index, was used to determine the significance of each hydrodynamic computational storm surge result with observed historical water surface elevations. In an effort to improving all models locally, using seven tidal constituents combinations along with a surface roughness nodal attribute grid that assigns values with respect to bathymetric data improves the accuracy of the storm surge model and should, therefore, be implemented for future hydrodynamic studies in the South Texas region.


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    [1] NOAA National Centers for Environmental Information (NCEI) U.S. (2020) Billion-Dollar Weather and Climate Disasters. Available from: https://www.ncdc.noaa.gov/billions/.
    [2] National Oceanic Atmospheric Administration (2017) National Weather Service, Major Hurricane Beulah-September 20th 1967. Available from: https://www.weather.gov/crp/Beulah.
    [3] Blake E, Landsea C, Gibney EJ (2011) The Deadliest, Costliest, and Most Intense United States Tropical Cyclones From 1851 to 2010 (and other frequently requested hurricane facts). NOAA technical memorandum NWS NHC-6, National Weather Service, National Hurricane Center, Miami, Florida.
    [4] Tunnell JW, Judd FW (2002) The Laguna Madre of Texas and Tamaulipas, Texas A&M University Press, 1-380.
    [5] Christian J, Fang Z, Torres J, et al. (2015) Modeling the Hydraulic Effectiveness of a Proposed Storm Surge Barrier System for the Houston Ship Channel During Hurricane Events. Nat Hazard Rev 16: 04014015. doi: 10.1061/(ASCE)NH.1527-6996.0000150
    [6] Zachary BC, Booth WJ, Rhome JR, et al. (2015) A National View of Storm Surge Risk and Inundation. Weather Clim Soc 7: 109-117. doi: 10.1175/WCAS-D-14-00049.1
    [7] National Oceanic Atmospheric Administration (2020) National Weather Service, Major Hurricane Harvey-August 25-29, 2017. Available from: https://www.weather.gov/crp/hurricane_harvey.
    [8] Southern Climate Impacts Planning Program (2020) SURGEDAT: The World's Storm Surge Data Center. Available from: http://surge.srcc.lsu.edu/index.html.
    [9] Mayo T, Butler T, Dawson C, et al. (2014) Data assimilation within the Advanced Circulation (ADCIRC) modeling framework for the estimation of Manning's friction coefficient. Ocean Model 76: 43-58. doi: 10.1016/j.ocemod.2014.01.001
    [10] Schoenbaechler C, Guthrie CG, Matsumoto J, et al. (2011) TxBlend Model Calibration and Validation for the Laguna Madre Estuary. Tex Water Dev Board, 60.
    [11] US Army Corp of Engineers (2016) SMS-Surface Water Modeling System. Available from: https://www.erdc.usace.army.mil/Media/Fact-Sheets/Fact-Sheet-Article-View/Article/919656/sms-surface-water-modeling-system/.
    [12] National Oceanic and Atmospheric Administration (2018) National Center for Environmental Information. Available from: https://www.ncei.noaa.gov/.
    [13] Militello A, Zundel A (1999) Surface Water Modeling System Tidal Constituents toolbox for ADCIRC. Engineer Research and Development Center Vicksburg MS Coastal and Hydraulics Lab, Coastal Eng Tech Note IV-21: 1-8.
    [14] Szpilka C, Dresback K, Kolar R, et al. (2016) Improvements for the Western North Atlantic, Caribbean and Gulf of Mexico ADCIRC Tidal Database (EC2015). J Mar Sci Eng 4: 72. doi: 10.3390/jmse4040072
    [15] National Oceanic and Atmospheric Administration (2018) NOAA Historical Hurricane Tracks. Available from: https://coast.noaa.gov/hurricanes/.
    [16] Medeirosa SC, Hagena SC, Weishampel JF (2012) Comparison of floodplains surface roughness parameters derived from land cover data and field measurements. J Hydrol 452: 139-149. doi: 10.1016/j.jhydrol.2012.05.043
    [17] Wu G, Shi F, Kirby J, et al. (2018) Modeling wave effects on storm surge coastal inundation. Coast Eng 140: 371-382. doi: 10.1016/j.coastaleng.2018.08.011
    [18] The University of Texas Rio Grande Valley (2019) High-Performance Computing Center. Available from: https://www.utrgv.edu/hpcc/resources/index.htm.
    [19] The University of North Carolina at Chapel Hill (2019) ADCIRC Input File Description. Available from: https://adcirc.org/home/documentation/users-manual-v50/input-file-descriptions/.
    [20] Xu S, Huang W (2008) Integrated hydrodynamic modeling framework and frequency analysis for predicting a 1% storm surge. J Coast Res 10052: 253-260. doi: 10.2112/1551-5036-52.sp1.253
    [21] Hardy RJ, Bates PD, Anderson MG (1999) The importance of spatial resolution in hydraulic models for floodplain environments. J Hydrol 216: 124-136. doi: 10.1016/S0022-1694(99)00002-5
    [22] National Oceanic and Atmospheric Administration, National Data Buoy Center, Station (2020) PTIT2-8779770-Port Isabel, TX. Available from: https://www.ndbc.noaa.gov/station_page.php?station=ptit2.
    [23] Arbic BK, Scott RB (2008) On Quadratic Bottom Drag, Geostrophic Turbulence, and Oceanic Mesoscale Eddies. J Phys Oceanogr 38: 84-103. doi: 10.1175/2007JPO3653.1
    [24] Research Database for Gulf of Mexico Research (2020) General Facts about the Gulf of Mexico, 1999. Available from: https://web.archive.org/web/20091210103009/http:/www.gulfbase.org/facts.php.
    [25] Davila SE, Garza A, Ho J (2018) Development of Hurricane Storm Surge Model to Predict Coastal Highway Inundation for South Texas. Intl J Interdiscip Res Innov 6: 522-527.
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