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Contribution of IG waves to local runup and flooding
Beach of Biarritz
Denis Morichon1
, Iñaki De Santiago1
,
Matthias Delpey2
, Nikola Danglade2
, Volker Roeber3
, Pedro Liria4
1
SIAME EA 4581, Université de Pau et des Pays de l'Adour
2
SUEZ Eau France, Centre Rivages Pro Tech
3
Univ of Hawaii at Manoa, Dpt of Oceanography
4
Azti Tecnalia
XBeachX Conference
1st
to 3rd
of November 2017
Deltares, Delft
Natural beaches
Storm impact along the Aquitanian coast
during the winter 2013-2014
Engineered beaches

Identify the key processes to include in EWS

Estimate the contribution of long waves (IG) to run-up

Monitor storm impact events

Use process based models
Study site
Grande Plage of Biarritz (FRANCE)
Wave climate
(Abadie et al., 2006)
Hs = 2.4 m
Tp = 12 s
Dp = 300°
Beach
Intermediate reflective
D50 = 0,3 mm
foreshore
up to 10 %
 ~ 2 %
Meso-tidal
MWL = 2.48 m
HWL = 4.65 m
LWL = 0.45 m
Station
video
Characteristics

Station height ~ 30 m above MSL

4 cameras to cover all beach (3 cameras - 8mm, 1camera – 16mm)

Cross-shore (angular) resolution ~ 1-15 cm

Alongshore (radial) resolution ~ 1-5 m
Video monitoring system
(SIRENA Open Source)
Snapshot Timex
(14 min averaged)
Timestack
(f=1Hz during 14 min
1min process)
Video monitoring system
(SIRENA Open Source)
Time
X-shore
Shoreline
Topography survey to
provide beach
elevation
Video runup estimation
η(t )=ηtide +ηsurge +ηwave set−up+Sswash (t )
Timestack
transects
Wave Run-up
Sswash(t)=SIG(f<0 .03Hz) +SINC(f>0 .03Hz )
Swash induced water level fluctuation
Video runup estimation
IG dominated swash
Balance between IG and
incident swash contribution
Images analysis procedure :
- Image thresholding techniques (Otsu, N., 1979)
- Time series of total water elevation
- Spectral analysis to quantify contribution of incident and IG waves
LONG SWELL SHORT SWELL
Offshore wave conditions
Directional wave buoy 50 m
Nearshore wave conditions
Hs
(ig)=80cm
Hs
(ig)=25cm
ID02
Video data analysis
ID01 ID01
Hin
2
/H2
Hig
2
/H2
Hin
2
/H2
Hig
2
/H2
ID02
Grid
x = 950 m
y = 1140 m
dx = ~12m – 0.5m
dy = 10m
Params
Gamma = 0.4
Facua = 0.3
hmin = 1
Calibration
rmse = ~0.25m
XBeach model set up
v1.22.4867 Kingsday
ID02
ID01
ID01
Rmse = 0.83 m
Rmse LWL-HWL =0.22 m
Rmse HWL = 0.91 m
ID02
Rmse = 1.14 m
Rmse LWL-HWL = 0.37 m
Rmse HWL = 1.31 m
Total water elevation
XBeach versus video
Swash time series and energy spectra
XBeach
Image
Mean water level High water level
Total water level computed using an empirical parameterization to
estimate maximum run-up (Stockdon, 2006)
Roeber et al. 2010
-Boussinesq-type equations based on Nwogu (1993)
-Shock-capturing based on conservative formulation of the equations
-Wave-breaking representation based on eddy viscosity
Computational domain
5 m grid resolution; 8.5 km*7.75 km
1700*1550 cells
Swash spectra
model v.s. obs
Phase resolving approach
BOSZ : Boussinesq model
ID01 ID02
Field of free
surface
elevation
Extraction
of run-up
timeseries
Ss_obs (IG) = 1.2 m Ss_obs(INC) = 3.8 m
Ss_bosz (IG) = 1.1 m Ss_bosz(INC) = 1.8 m
Error = 8 % Error = 53 %
Ss_obs (IG) = 1.9 m Ss_obs(INC) = 2.0 m
Ss_bosz (IG) = 1.4 m Ss_bosz(INC) = 1.4 m
Error = 25 % Error = 27 %
Flooding case (Feb 28)
Phase resolving approach
BOSZ : Boussinesq model
BuildingBoardwalk
Flooding
occurence
OffshoreBeach
Conclusion

Run-up is dominated by short waves for HWL

XBeach underestimates run-up and energy in the infragravity band

BOSZ model highlights the contribution of short waves to run-up

BOSZ results suggest that swash energy is dominated by IG frequency band
during extreme conditions
Future work

Download the XbeachX new release

Extend storm data set and carry out an extensive nearshore field campaign

Investigate the influence of wave/seawall interaction on flooding events
Acknowledgement : This work is co-financed by the European Regional
Development Fund (FEDER).
Thank you for your attention

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DSD-INT 2017 Contribution of IG waves to local runup and flooding Beach of Biarritz - Morichon

  • 1. Contribution of IG waves to local runup and flooding Beach of Biarritz Denis Morichon1 , Iñaki De Santiago1 , Matthias Delpey2 , Nikola Danglade2 , Volker Roeber3 , Pedro Liria4 1 SIAME EA 4581, Université de Pau et des Pays de l'Adour 2 SUEZ Eau France, Centre Rivages Pro Tech 3 Univ of Hawaii at Manoa, Dpt of Oceanography 4 Azti Tecnalia XBeachX Conference 1st to 3rd of November 2017 Deltares, Delft
  • 2. Natural beaches Storm impact along the Aquitanian coast during the winter 2013-2014 Engineered beaches  Identify the key processes to include in EWS  Estimate the contribution of long waves (IG) to run-up  Monitor storm impact events  Use process based models
  • 3. Study site Grande Plage of Biarritz (FRANCE) Wave climate (Abadie et al., 2006) Hs = 2.4 m Tp = 12 s Dp = 300° Beach Intermediate reflective D50 = 0,3 mm foreshore up to 10 %  ~ 2 % Meso-tidal MWL = 2.48 m HWL = 4.65 m LWL = 0.45 m Station video
  • 4. Characteristics  Station height ~ 30 m above MSL  4 cameras to cover all beach (3 cameras - 8mm, 1camera – 16mm)  Cross-shore (angular) resolution ~ 1-15 cm  Alongshore (radial) resolution ~ 1-5 m Video monitoring system (SIRENA Open Source)
  • 5. Snapshot Timex (14 min averaged) Timestack (f=1Hz during 14 min 1min process) Video monitoring system (SIRENA Open Source)
  • 6. Time X-shore Shoreline Topography survey to provide beach elevation Video runup estimation η(t )=ηtide +ηsurge +ηwave set−up+Sswash (t ) Timestack transects Wave Run-up Sswash(t)=SIG(f<0 .03Hz) +SINC(f>0 .03Hz ) Swash induced water level fluctuation
  • 7. Video runup estimation IG dominated swash Balance between IG and incident swash contribution Images analysis procedure : - Image thresholding techniques (Otsu, N., 1979) - Time series of total water elevation - Spectral analysis to quantify contribution of incident and IG waves
  • 8. LONG SWELL SHORT SWELL Offshore wave conditions Directional wave buoy 50 m
  • 10. ID02 Video data analysis ID01 ID01 Hin 2 /H2 Hig 2 /H2 Hin 2 /H2 Hig 2 /H2 ID02
  • 11. Grid x = 950 m y = 1140 m dx = ~12m – 0.5m dy = 10m Params Gamma = 0.4 Facua = 0.3 hmin = 1 Calibration rmse = ~0.25m XBeach model set up v1.22.4867 Kingsday ID02 ID01
  • 12. ID01 Rmse = 0.83 m Rmse LWL-HWL =0.22 m Rmse HWL = 0.91 m ID02 Rmse = 1.14 m Rmse LWL-HWL = 0.37 m Rmse HWL = 1.31 m Total water elevation XBeach versus video
  • 13. Swash time series and energy spectra XBeach Image Mean water level High water level
  • 14. Total water level computed using an empirical parameterization to estimate maximum run-up (Stockdon, 2006)
  • 15.
  • 16. Roeber et al. 2010 -Boussinesq-type equations based on Nwogu (1993) -Shock-capturing based on conservative formulation of the equations -Wave-breaking representation based on eddy viscosity Computational domain 5 m grid resolution; 8.5 km*7.75 km 1700*1550 cells Swash spectra model v.s. obs Phase resolving approach BOSZ : Boussinesq model ID01 ID02 Field of free surface elevation Extraction of run-up timeseries Ss_obs (IG) = 1.2 m Ss_obs(INC) = 3.8 m Ss_bosz (IG) = 1.1 m Ss_bosz(INC) = 1.8 m Error = 8 % Error = 53 % Ss_obs (IG) = 1.9 m Ss_obs(INC) = 2.0 m Ss_bosz (IG) = 1.4 m Ss_bosz(INC) = 1.4 m Error = 25 % Error = 27 %
  • 17. Flooding case (Feb 28) Phase resolving approach BOSZ : Boussinesq model BuildingBoardwalk Flooding occurence OffshoreBeach
  • 18. Conclusion  Run-up is dominated by short waves for HWL  XBeach underestimates run-up and energy in the infragravity band  BOSZ model highlights the contribution of short waves to run-up  BOSZ results suggest that swash energy is dominated by IG frequency band during extreme conditions Future work  Download the XbeachX new release  Extend storm data set and carry out an extensive nearshore field campaign  Investigate the influence of wave/seawall interaction on flooding events
  • 19. Acknowledgement : This work is co-financed by the European Regional Development Fund (FEDER). Thank you for your attention