North Atlantic Coast Comprehensive Study (Naccs) Storm Simulation and Statistical Analysis: Part I – Overview

Cialone, Mary A.; Bocamazo, Lynn; Nadal-Caraballo, Norberto C.; Massey, Thomas C.; Melby, Jeffrey A.

doi:10.1142/9789814689977_0217

Cited by 21 publications

(30 citation statements)

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“…Table 3 displays the conditions considered in these 13 cases. Water depths and wave heights of these cases were derived based on the 13 Annual Exceedance Probability values reported by the Coastal Hazard System (see Cialone et al (2015) and Nadal-Caraballo et al (2015) for further details). Cases ranged from mild conditions (case 1) to extreme conditions (case 13).…”

Section: Wave Attenuation Under a Comprehensive Range Of Sea And Meadmentioning

confidence: 99%

Wave Attenuation by Spartina Saltmarshes in the Chesapeake Bay Under Storm Surge Conditions

et al. 2019

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This study investigates the capacity of a Spartina alterniflora meadow to attenuate waves during storm events based on field observations in the Chesapeake Bay. These observations reveal that environmental conditions including the ratio between water depth and plant height (hr), the ratio between wave height (HS) and water depth, and current directions impact the wave height decay. Further, we present empirical representations of the bulk drag coefficient (Cd) as a function of the Keulegan‐Carpenter (KC) and Reynolds (Re) numbers, and the hr ratio. When applying the distinction between current directions, this representation exhibits better agreement when using the Re (ρ2 = 54%) and hr (ρ2 = 77%) than with the KC (ρ2 = 39%). Furthermore, we show that the representation of Cd can be improved by using a hr‐based modified Re and KC formulation, yielding correlations of 76% (modified Re) and 78% (modified KC). The proposed expressions are validated during another storm and predicted HS computed within the marsh results in a root‐mean‐square error of 0.014 m, overestimating the largest HS (0.22 m) by 18%. Finally, these expressions are applied to several hypothetical sea conditions. Under similar vegetation characteristics, HS of 1.55 and 0.8 m (close to a 10,000‐ and 100‐year recurrence interval storm) are attenuated by 50% and 70%, respectively, at 250 m from the marsh edge. This study provides evidence that validates the saltmarsh wave attenuation capacity during storms, quantifies this attenuation, and supports the transferability of the existing formulas in the literature across similar coastal marshes.

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Section: Wave Attenuation Under a Comprehensive Range Of Sea And Meadmentioning

confidence: 99%

Wave Attenuation by Spartina Saltmarshes in the Chesapeake Bay Under Storm Surge Conditions

et al. 2019

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“…The nearshore wave model Steady-State spectral WAVE (STWAVE) was applied as part of the shoaling analysis for the navigation channel deepening in NYNJH. One STWAVE grid, previously developed as part of the North Atlantic Coast Comprehensive Study (NACCS), was updated for this modeling effort (Cialone et al 2015).…”

Section: Wave Energymentioning

confidence: 99%

New York/New Jersey Harbor sedimentation study : numerical modeling of hydrodynamics and sediment transport

McAlpin¹,

Letter²,

Bryant³

et al. 2020

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The contents of this report are not to be used for advertising, publication, or promotional purposes. Citation of trade names does not constitute an official endorsement or approval of the use of such commercial products. All product names and trademarks cited are the property of their respective owners. The findings of this report are not to be construed as an official Department of the Army position unless so designated by other authorized documents.

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“…Applying these forcing conditions, the twodimensional (2D), depth-integrated ADCIRC model has proven to accurately predict tidal-and wind-driven water-surface levels. ADCIRC has been successfully applied in a large number of coastal applications, most recently in support of the NACCS (Cialone et al 2015), FEMA flood risk map updates in (1) the northern Gulf of Mexico region, (2) FEMA Region II and III, (3) the Lake Michigan storm wave and water level study (Jensen et al 2012), and (4) the Lake St. Clair storm wave and water level study (Hesser et al 2013); and in support of USACE projects such as the Louisiana Coastal Protection and Restoration project (USACE 2009a;Bunya et al 2010) and the Mississippi Coastal Improvements Program (Wamsley et al 2013). (A detailed description for the general application of ADCIRC is available at http://www.adcirc.org.…”

Section: Storm Surge Modelsmentioning

confidence: 99%

“…Sources of error for water level modeling and validation have been identified in previous studies where ADCIRC has been employed (Hanson et al 2013;Cialone et al 2015) and include errors in forcing winds, errors in modeling mesh due to bathymetry or surveying, as well as a combination of different sources of data in a grid error in the validation water levels and error relating to tidal calibration.…”

Section: Storm Surge Modelsmentioning

confidence: 99%

“…The skill of the WAM model needs to be quantified as part of an analysis by evaluating differences between model results and measurements. The evaluation can be based on Quartile-Quartile graphics or statistical tests such as bias, root-mean-square-error, regression, correlation, and scatter index, performed at measurement sites (Cialone et al 2015 The primary objective of applying a nearshore wave model is to quantify the change in wave parameters (wave height, period, direction, and spectral shape) from an offshore location (typically depths of less than 40 m) to the shoreline. Offshore wave information obtained from wave buoys or global-or regional-scale wave hindcasts and forecasts is transformed through the nearshore coastal region using these nearshore wave transformation models.…”

Section: Wave Prediction Model (Wam)mentioning

confidence: 99%

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Quantification of uncertainty in probabilistic storm surge models : literature review

González¹,

Nadal-Caraballo²,

Melby³

et al. 2019

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Probabilistic coastal hazard assessment is characterized by the relationship between storm hazards, such as storm surge, and corresponding annual exceedance probability. The probabilistic analysis of storm surge is an integral component of the flood hazard assessment of structures and facilities located near coastal areas. The Joint Probability Method (JPM) has become the standard probabilistic modeling approach for the assessment of coastal storm hazards in hurricane-prone areas in the United States. A comprehensive literature review was conducted to evaluate the components, technical considerations, and limitations of different implementations of the JPM, with emphasis on the methods adopted by U.S. government agencies, including the U.S. Army Corps of Engineers and the Federal Emergency Management Agency. The traditional treatment of uncertainty (e.g., meteorological, hydrodynamic, and probabilistic modeling error) in storm surge studies was found to be better documented than the quantification of epistemic uncertainty through the concurrent consideration of alternate data, methods, and models. This literature review is part of the U.S. Nuclear Regulatory Commission-sponsored study "Quantification of Uncertainties in Probabilistic Storm Surge Models." DISCLAIMER: The contents of this report are not to be used for advertising, publication, or promotional purposes. Citation of trade names does not constitute an official endorsement or approval of the use of such commercial products. All product names and trademarks cited are the property of their respective owners. The findings of this report are not to be construed as an official Department of the Army position unless so designated by other authorized documents.

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North Atlantic Coast Comprehensive Study (Naccs) Storm Simulation and Statistical Analysis: Part I – Overview

Cited by 21 publications

References 0 publications

Wave Attenuation by Spartina Saltmarshes in the Chesapeake Bay Under Storm Surge Conditions

Wave Attenuation by Spartina Saltmarshes in the Chesapeake Bay Under Storm Surge Conditions

New York/New Jersey Harbor sedimentation study : numerical modeling of hydrodynamics and sediment transport

Quantification of uncertainty in probabilistic storm surge models : literature review

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