Wave Setup in Inlets: Some Practical Considerations

2007 ◽  
Author(s):  
Dale Kerper ◽  
Christian M. Appendini ◽  
Henrik Kofoed-Hansen ◽  
Ida Bro̸ker
Keyword(s):  
Numerical Models ◽  
Current Model ◽  
Wave Model ◽  
Total Water ◽  
Wave Runup ◽  
Modeling Tools ◽  
Mean Sea Level ◽  
Wave Setup ◽  
Astronomical Tide ◽  
Total Water Level

For the determination maximum flood elevations, a number of components contributing to the total water level need to be considered. For instance, astronomical tide, storm surge, relative changes in mean sea level, wave setup, wave runup and wave splash. In this study, numerical models were used to evaluate under which conditions wave setup penetrates into an idealized inlet. A number of idealized inlet/lagoon configurations were tested. A coupled wave-current model was used to assess the static component of the wave setup. A Boussinesq wave model was used to assess the influence of the dynamic oscillating component of the wave setup. This study demonstrates how numerical modeling tools can be effectively used to assess how wave setup develops depending on a specific inlet configuration.

scholarly journals SYNTHESIS OP HURRICANE RESPONSE HYDROGRAPHS

1982 ◽  
Vol 1 (18) ◽  
pp. 7
Author(s):  
Rodney J. Sobey
Keyword(s):  
Water Level ◽  
Historical Data ◽  
Breaking Wave ◽  
Total Water ◽  
Coastal Site ◽  
Data Set ◽  
Storm Tide ◽  
Synthesis Technique ◽  
Astronomical Tide ◽  
Total Water Level

A hindcasting methodology is described for the total water level and wave hydrographs at a coastal site during a hurricane. It accommodates phasing of the separate components of the sustained water level (astronomical tide, storm tide, breaking wave setup) , as well as storm variability and coastal bathymetry. Complete hindcast models are utilised, but an intermediate cost and precision is achieved by compromising the number of complete hindcast storms, rather than the precision of the hindcast model. A synthesis technique is developed to predict the response hydrographs of the remaining storms in the historical data set.

scholarly journals BOUSSINESQ MODELING OF COMBINED STORM SURGE AND WAVES OVER WETLANDS FORCED BY WIND

2020 ◽  
pp. 6
Author(s):  
Qin Chen ◽  
Ling Zhu ◽  
Fengyan Shi ◽  
Steve Brandt
Keyword(s):  
Storm Surge ◽  
Numerical Models ◽  
Wind Waves ◽  
Wave Model ◽  
Short Wave ◽  
Momentum Balance ◽  
Wave Runup ◽  
Time Step ◽  
Boussinesq Model ◽  
Coupling Interval

Coastal wetlands protect the shoreline and infrastructure by attenuating wind waves and reducing storm surge. It is of importance to accurately quantify the flood protection provided by vegetation. Existing numerical models for hurricane waves and storm surge are based on the phase-averaged wave action balance equation and the nonlinear shallow water equations, respectively, with the wind forcing and vegetal drag as the free surface and bottom boundary conditions. To consider the interaction of waves and surge, the phase-averaged short wave and long wave (storm surge) models can be coupled in a staggered fashion. If the time step of the wave model and storm surge model are 30 minutes and 1 s, respectively, both models would exchange information every 30 minutes. There is no iteration between the wave and surge models at each coupling interval. An alternative to this state-of-the-practice of hurricane wave and storm surge modeling is to simulate the combined wave and surge motion driven by wind and attenuated by wetland vegetation using a phase-resolving Boussinesq model. The objective of this study is threefold: 1) to demonstrate the capability of modeling wave growth by wind, wave reduction by vegetation, and the total water level (wave setup, wind setup and wave runup) using the extended FUNWAVE-TVD model; 2) to analyze the energy balance of the combined wave and surge motion; 3) to examine the momentum balance with an emphasis on the vegetal drag owing to the combined wave orbital velocity and wind-driven current velocity.Recorded Presentation from the vICCE (YouTube Link): https://youtu.be/-o_kx4hPvC8

scholarly journals Combining probability distributions of sea level variations and wave run-up to evaluate coastal flooding risks

2018 ◽  
Vol 18 (10) ◽  
pp. 2785-2799 ◽  
Author(s):  
Ulpu Leijala ◽  
Jan-Victor Björkqvist ◽  
Milla M. Johansson ◽  
Havu Pellikka ◽  
Lauri Laakso ◽  
...  
Keyword(s):  
Water Level ◽  
Sea Level ◽  
Probability Distributions ◽  
Water Levels ◽  
Total Water ◽  
Mean Sea Level ◽  
Sea Level Variations ◽  
Wave Conditions ◽  
Run Up ◽  
Total Water Level

Abstract. Tools for estimating probabilities of flooding hazards caused by the simultaneous effect of sea level and waves are needed for the secure planning of densely populated coastal areas that are strongly vulnerable to climate change. In this paper we present a method for combining location-specific probability distributions of three different components: (1) long-term mean sea level change, (2) short-term sea level variations and (3) wind-generated waves. We apply the method at two locations in the Helsinki archipelago to obtain total water level estimates representing the joint effect of the still water level and the wave run-up for the present, 2050 and 2100. The variability of the wave conditions between the study sites leads to a difference in the safe building levels of up to 1 m. The rising mean sea level in the Gulf of Finland and the uncertainty related to the associated scenarios contribute notably to the total water levels for the year 2100. A test with theoretical wave run-up distributions illustrates the effect of the relative magnitude of the sea level variations and wave conditions on the total water level. We also discuss our method's applicability to other coastal regions.

scholarly journals Evaluating the accuracy and uncertainty of atmospheric and wave model hindcasts during severe events using model ensembles

2021 ◽  
Author(s):  
Ali Abdolali ◽  
Andre van der Westhuysen ◽  
Zaizhong Ma ◽  
Avichal Mehra ◽  
Aron Roland ◽  
...  
Keyword(s):  
Extreme Event ◽  
Numerical Models ◽  
Model Performance ◽  
Ground Truth ◽  
Wave Model ◽  
Atmospheric Model ◽  
Stationary Source ◽  
Source Point ◽  
Spectral Wave Model ◽  
Model Ensembles

AbstractVarious uncertainties exist in a hindcast due to the inabilities of numerical models to resolve all the complicated atmosphere-sea interactions, and the lack of certain ground truth observations. Here, a comprehensive analysis of an atmospheric model performance in hindcast mode (Hurricane Weather and Research Forecasting model—HWRF) and its 40 ensembles during severe events is conducted, evaluating the model accuracy and uncertainty for hurricane track parameters, and wind speed collected along satellite altimeter tracks and at stationary source point observations. Subsequently, the downstream spectral wave model WAVEWATCH III is forced by two sets of wind field data, each includes 40 members. The first ones are randomly extracted from original HWRF simulations and the second ones are based on spread of best track parameters. The atmospheric model spread and wave model error along satellite altimeters tracks and at stationary source point observations are estimated. The study on Hurricane Irma reveals that wind and wave observations during this extreme event are within ensemble spreads. While both Models have wide spreads over areas with landmass, maximum uncertainty in the atmospheric model is at hurricane eye in contrast to the wave model.

An empirical formula for maximum wave setup based on a coupled wave-current model

2018 ◽  
Vol 147 ◽  
pp. 215-226 ◽  
Author(s):  
Chao Ji ◽  
Qinghe Zhang ◽  
Yongsheng Wu
Keyword(s):  
Empirical Formula ◽  
Current Model ◽  
Wave Setup ◽  
Coupled Wave

scholarly journals Radiational tides: their double-counting in storm surge forecasts and contribution to the Highest Astronomical Tide

Ocean Science ◽  
2018 ◽  
Vol 14 (5) ◽  
pp. 1057-1068 ◽  
Author(s):  
Joanne Williams ◽  
Maialen Irazoqui Apecechea ◽  
Andrew Saulter ◽  
Kevin J. Horsburgh
Keyword(s):  
Tide Gauge ◽  
Storm Surges ◽  
Double Counting ◽  
Atmospheric Conditions ◽  
Sea Level Changes ◽  
Astronomical Tide ◽  
Operational Forecasts ◽  
The Difference ◽  
The Uk ◽  
Total Water Level

Abstract. Tide predictions based on tide-gauge observations are not just the astronomical tides; they also contain radiational tides – periodic sea-level changes due to atmospheric conditions and solar forcing. This poses a problem of double-counting for operational forecasts of total water level during storm surges. In some surge forecasting, a regional model is run in two modes: tide only, with astronomic forcing alone; and tide and surge, forced additionally by surface winds and pressure. The surge residual is defined to be the difference between these configurations and is added to the local harmonic predictions from gauges. Here we use the Global Tide and Surge Model (GTSM) based on Delft-FM to investigate this in the UK and elsewhere, quantifying the weather-related tides that may be double-counted in operational forecasts. We show that the global S2 atmospheric tide is captured by the tide-and-surge model and observe changes in other major constituents, including M2. The Lowest and Highest Astronomical Tide levels, used in navigation datums and design heights, are derived from tide predictions based on observations. We use our findings on radiational tides to quantify the extent to which these levels may contain weather-related components.

scholarly journals Deriving the 100-Year Total Water Level around the Coast of Corsica by Combining Trivariate Extreme Value Analysis and Coastal Hydrodynamic Models

2021 ◽  
Vol 9 (12) ◽  
pp. 1347
Author(s):  
Jessie Louisor ◽  
Jérémy Rohmer ◽  
Thomas Bulteau ◽  
Faïza Boulahya ◽  
Rodrigo Pedreros ◽  
...  
Keyword(s):  
Water Level ◽  
Return Period ◽  
Extreme Value ◽  
Coastal Areas ◽  
Extreme Value Analysis ◽  
Total Water ◽  
Hydrodynamic Models ◽  
Value Analysis ◽  
Multivariate Extreme Value ◽  
Total Water Level

As low-lying coastal areas can be impacted by flooding caused by dynamic components that are dependent on each other (wind, waves, water levels—tide, atmospheric surge, currents), the analysis of the return period of a single component is not representative of the return period of the total water level at the coast. It is important to assess a joint return period of all the components. Based on a semiparametric multivariate extreme value analysis, we determined the joint probabilities that significant wave heights (Hs), wind intensity at 10 m above the ground (U), and still water level (SWL) exceeded jointly imposed thresholds all along the Corsica Island coasts (Mediterranean Sea). We also considered the covariate peak direction (Dp), the peak period (Tp), and the wind direction (Du). Here, we focus on providing extreme scenarios to populate coastal hydrodynamic models, SWAN and SWASH-2DH, in order to compute the 100-year total water level (100y-TWL) all along the coasts. We show how the proposed multivariate extreme value analysis can help to more accurately define low-lying zones potentially exposed to coastal flooding, especially in Corsica where a unique value of 2 m was taken into account in previous studies. The computed 100y-TWL values are between 1 m along the eastern coasts and a maximum of 1.8 m on the western coast. The calculated values are also below the 2.4 m threshold recommended when considering the sea level rise (SLR). This highlights the added value of performing a full integration of extreme offshore conditions, together with their dependence on hydrodynamic simulations for screening out the coastal areas potentially exposed to flooding.

scholarly journals Coupled wave-equation and eddy-current model for modelling and measuring propagating stress-waves

2015 ◽  
Vol 64 (2) ◽  
pp. 215-226
Author(s):  
Tommi Peussa ◽  
Anouar Belahcen
Keyword(s):  
Flux Density ◽  
Eddy Current ◽  
Current Model ◽  
Wave Model ◽  
Magnetic Flux Density ◽  
The Finite Element Method ◽  
Coupled Models ◽  
Steel Bar ◽  
Measured Stress ◽  
Coupled Wave

AbstractThe coupling of the propagating stress wave with the eddy current model is presented. The applied stress produces magnetization in the sample that can be measured outside the sample by measuring the resulting magnetic flux density. The stress and flux density measurements are made on a mechanically excited steel bar. The problem is modelled with the finite element method for both the propagating wave and the eddy current. Three aspects are considered: eddy current model using magnetization from the measurements, coupled wave and eddy current models, and coupled different dimensions in the wave model. The measured stress can be reproduced from the measured flux density by modelling. The coupled models work both for stress and flux couplings as well as for the different dimensionality couplings.

scholarly journals FRF WAVE TEST BED AND BATHYMETRY INVERSION

2017 ◽  
pp. 22 ◽  
Author(s):  
Jane McKee Smith ◽  
Spicer Bak ◽  
Tyler Hesser ◽  
Mary A. Bryant ◽  
Chris Massey
Keyword(s):  
Numerical Models ◽  
Field Research ◽  
Wave Model ◽  
Army Corps ◽  
Army Corps Of Engineers ◽  
Test Bed ◽  
Inversion Algorithm ◽  
Us Army ◽  
Spectral Wave Model ◽  
Limited Application

An automated Coastal Model Test Bed has been built for the US Army Corps of Engineers Field Research Facility to evaluate coastal numerical models. In October of 2015, the test bed was expanded during a multi-investigator experiment, called BathyDuck, to evaluate two bathymetry sources: traditional survey data and bathymetry generated through the cBathy inversion algorithm using Argus video measurements. Comparisons were made between simulations using the spectral wave model STWAVE with half-hourly cBathy bathymetry and the more temporally sparse surveyed bathymetry. The simulation results using cBathy bathymetry were relatively close to those using the surveyed bathymetry. The largest differences were at the shallowest gauges within 250 m of the coast, where wave model normalized root-mean-square was approximately twice are large using the cBathy bathymetry. The nearshore errors using the cBathy input were greatest during events with wave height greater than 2 m. For this limited application, the Argus cBathy algorithm proved to be a suitable bathymetry input for nearshore wave modeling. cBathy bathymetry was easily incorporated into the modeling test bed and had the advantage of being updated on approximately the same temporal scale as the other model input conditions. cBathy has great potential for modeling applications where traditional surveys are sparse (seasonal or yearly).

scholarly journals The Role of Mean Sea Level Annual Cycle on Extreme Water Levels Along European Coastline

2020 ◽  
Vol 12 (20) ◽  
pp. 3419
Author(s):  
Tomás Fernández-Montblanc ◽  
Jesús Gómez-Enri ◽  
Paolo Ciavola
Keyword(s):  
Water Level ◽  
Sea Level ◽  
North Sea ◽  
Extreme Events ◽  
Annual Cycle ◽  
Coastal Flooding ◽  
Water Levels ◽  
Total Water ◽  
Mean Sea Level ◽  
The Impact

The knowledge of extreme total water levels (ETWLs) and the derived impact, coastal flooding and erosion, is crucial to face the present and future challenges exacerbated in European densely populated coastal areas. Based on 24 years (1993–2016) of multimission radar altimetry, this paper investigates the contribution of each water level component: tide, surge and annual cycle of monthly mean sea level (MMSL) to the ETWLs. It focuses on the contribution of the annual variation of MMSL in the coastal flooding extreme events registered in a European database. In microtidal areas (Black, Baltic and Mediterranean Sea), the MMSL contribution is mostly larger than tide, and it can be at the same order of magnitude of the surge. In meso and macrotidal areas, the MMSL contribution is <20% of the total water level, but larger (>30%) in the North Sea. No correlation was observed between the average annual cycle of monthly mean sea level (AMMSL) and coastal flooding extreme events (CFEEs) along the European coastal line. Positive correlations of the component variance of MMSL with the relative frequency of CFEEs extend to the Central Mediterranean (r = 0.59), North Sea (r = 0.60) and Baltic Sea (r = 0.75). In the case of positive MMSL anomalies, the correlation expands to the Bay of Biscay and northern North Atlantic (at >90% of statistical significance). The understanding of the spatial and temporal patterns of a combination of all the components of the ETWLs shall improve the preparedness and coastal adaptation measures to reduce the impact of coastal flooding.

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