Dynamic Modeling of Storm Surge and Inland Flooding in a Texas Coastal Floodplain

Ray, T. K.; Stepinski, Emilia; Sebastian, Antonia; Bedient, Philip B.

doi:10.1061/(asce)hy.1943-7900.0000398

Cited by 46 publications

(39 citation statements)

References 8 publications

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“…Human tragedies occur due to a combination of heavy rainfall, inland flooding and high wind velocities. According to FEMA, nine out of ten hurricane fatalities are attributed to storm surge [5]. Depending on the watershed characteristics and the rainfall distribution in time and space, the maximum flood depth in coastal areas is produced by a combination of both storm surge and inland flooding.…”

Section: Maximum Flood Inundation Mapsmentioning

confidence: 99%

“…The initial moisture and the overland roughness coefficients have less impact on the model response. Previously, GSSHA has shown to be quite sensitive to the soil hydraulic conductivity, overland and channel roughness, retention storage and plant interception of rainfall [5].…”

Section: Sensitivity Analysismentioning

confidence: 99%

“…Flooding on coastal zones could be exacerbated by the addition of overland runoff. Flood risk analysis and damage in many coastal watersheds might be underestimated under current Federal Emergency Management Agency (FEMA) floodplain procedures if they do not consider dynamic storm surge boundary conditions in hydraulic models to determine inland consider dynamic storm surge boundary conditions in hydraulic models to determine inland flooding risk [5]. Process-based hydrologic models are becoming increasingly critical in short-term forecasting of inundation dynamics and in situations where complex land-atmosphere coupling is essential for accurate predictions [6].…”

Section: Introductionmentioning

confidence: 99%

“…Their model simulates tides, depth-averaged tidal currents, wind-driven surges and currents by solving the full set of depth-integrated, non-linear equations, through a finite difference scheme. As a case study, Ray et al developed a dynamic modeling of storm surge and inland flooding in the coastal floodplain of Galveston, TX, USA [5]. A one-dimensional hydraulic model of Armand Bayou watershed, located in Texas, for the two principal streams was built.…”

Section: Introductionmentioning

confidence: 99%

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Dynamic Modeling of Surface Runoff and Storm Surge during Hurricane and Tropical Storm Events

et al. 2018

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Hurricane events combine ocean storm surge penetration with inland runoff flooding. This article presents a new methodology to determine coastal flood levels caused by the combination of storm surge and surface runoff. The proposed approach couples the Simulating Waves Nearshore model and the Advanced Circulation (ADCIRC) model with the Gridded Surface Subsurface Hydrologic Analysis (GSSHA) two-dimensional hydrologic model. Radar precipitation data in a 2D hydrologic model with a circulation model allows simulation of time and spatially varied conditions. The method was applied to study flooding scenarios occurring during the passage of Hurricane Georges (1998) on the east coast of Puerto Rico. The combination of storm surge and surface runoff produced a critical scenario, in terms of flood depth, at this location. The paper describes the data collection process, circulation and hydrologic models, their assemblage and simulation scenarios. Results show that peak flow from inland runoff and peak flow due to storm surge did not coincide in the coastal zone; however, the interaction of both discharges causes an aggravated hazardous condition by increasing flood levels beyond those obtained with storm surge penetration only. Linking of storm surge and hydrologic models are necessary when storm surge conditions occur simultaneously with high precipitation over steep and small coastal watersheds.

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Section: Maximum Flood Inundation Mapsmentioning

confidence: 99%

Section: Sensitivity Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Dynamic Modeling of Surface Runoff and Storm Surge during Hurricane and Tropical Storm Events

et al. 2018

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“…While this is a clear simplification of flood processes, water levels in the catchment are currently derived under similar assumptions to create the FEMA flood insurance rate maps (FIRMs) [18,26]. The spatial discretization was obtained from surveyed cross-sections [79] at approximately every kilometer, and the water surface elevations were calculated every 100 m, here forth referred to as river calculation points.…”

Section: D Hydraulic Modelmentioning

confidence: 99%

A Copula-Based Bayesian Network for Modeling Compound Flood Hazard from Riverine and Coastal Interactions at the Catchment Scale: An Application to the Houston Ship Channel, Texas

Couasnon¹,

Sebastian

Morales-Nápoles

2018

Preprint

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Abstract:Traditional flood hazard analyses often rely on univariate probability distributions; however, in many coastal catchments, flooding is the result of complex hydrodynamic interactions between multiple drivers. For example, synoptic meteorological conditions can produce considerable rainfall-runoff, while also generating wind-driven elevated sea-levels. When these drivers interact in space and time, they can exacerbate flood impacts, a phenomenon known as compound flooding. In this paper, we build a Bayesian Network based on Gaussian copulas to generate the equivalent of 500 years of daily stochastic boundary conditions for a coastal watershed in Southeast Texas. In doing so, we overcome many of the limitations of conventional univariate approaches and are able to probabilistically represent compound floods caused by riverine and coastal interactions. We model the resulting water levels using a one-dimensional (1D) steady-state hydraulic model and find that flood stages in the catchment are strongly affected by backwater effects from tributary inflows and downstream water levels. By comparing our results against a bathtub modeling approach, we show that simplifying the multivariate dependence between flood drivers can lead to an underestimation of flood impacts, highlighting that accounting for multivariate dependence is critical for the accurate representation of flood risk in coastal catchments prone to compound events.

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Defining Flood Zone Transitions in Low‐Gradient Coastal Regions

Bilskie

Hagen

2018

Geophysical Research Letters

124

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Worldwide, coastal, and deltaic communities are susceptible to flooding from the individual and combined effects of rainfall excess and astronomic tide and storm surge inundation. Such flood events are a present (and future) cause of concern as observed from recent storms such as the 2016 Louisiana flood and Hurricanes Harvey, Irma, and Maria. To assess flood risk across coastal landscapes, it is advantageous to first delineate flood transition zones, which we define as areas susceptible to hydrologic and coastal flooding and their collective interaction. We utilize numerical simulations combining rainfall excess and storm surge for the 2016 Louisiana flood to describe a flood transition zone for southeastern Louisiana. We show that the interaction of rainfall excess with coastal surge is nonlinear and less than the superposition of their individual components. Our analysis provides a foundation to define flooding zones across coastal landscapes throughout the world to support flood risk assessments.

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Dynamic Modeling of Storm Surge and Inland Flooding in a Texas Coastal Floodplain

Cited by 46 publications

References 8 publications

Dynamic Modeling of Surface Runoff and Storm Surge during Hurricane and Tropical Storm Events

Dynamic Modeling of Surface Runoff and Storm Surge during Hurricane and Tropical Storm Events

A Copula-Based Bayesian Network for Modeling Compound Flood Hazard from Riverine and Coastal Interactions at the Catchment Scale: An Application to the Houston Ship Channel, Texas

Defining Flood Zone Transitions in Low‐Gradient Coastal Regions

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