8th International Coastal Symposium

Modelling morphological changes of beach and dune induced by storm on the Southern Baltic coast using XBeach (case study: Dziwnow Spit)

1

Modelling morphological changes of beach and dune induced by storm on the Southern Baltic coast using XBeach (case study: Dziwnow Spit) Natalia Bugajny†, Kazimierz Furmańczyk†, Joanna Dudzińska-Nowak†, Barbara Paplińska-Swerpel‡ †Institute of Marine and Coastal Sciences University of Szczecin, Szczecin 70-383, Poland [email protected]

‡ Institute of Hydro-Engineering Polish Academy of Sciences, Gdańsk, 80-328, Poland

www.cerf-jcr.org

[email protected]

ABSTRACT

www.JCRonline.org

Bugajny, N., Furmańczyk, K., Dudzińska-Nowak, J., Paplińska-Swerpel, B., 2013. Modelling morphological changes of beach and dune induced by storm on the Southern Baltic coast using XBeach (case study: Dziwnow Spit) In: Conley, D.C., Masselink, G., Russell, P.E. and O’Hare, T.J. (eds.), Proceedings 12th International Coastal Symposium (Plymouth, England), Journal of Coastal Research, Special Issue No. 65, pp. 672-677, ISSN 0749-0208. The purpose of this paper is to demonstrate the usefulness of XBeach model (1D) in modelling changes of beach and dune morphology in terms of significant storm influence at sandy Dziwnow Spit area located in the non -tidal Baltic Sea, on the western part of the Polish coast. Research were carried out in the framework of the MICORE project (7 th FP) the main goal of which was to develop an operational early warning system for coastal hazard based on the XBeach model. For model calibration, one significant storm event registered in 2009 was simulated and compared against pre- and post-storm morphological data consisting of geodetic measurement and airborne laser scanning data. XBeach model has been run for 8 cross-shore profiles with different configuration of model parameters. The model skill were tested on the base of statistical descriptor BSS for the terrestrial part of the profiles. The highest BSS values varied from 0.54 to 0.90 depending on the profile. The best performance of XBeach model for each profile was obtained by deactivating longwave stirring lws and keeping hmin parameter value to 0.05 in all simulations. Values of wetslp equalled 0.3 or 0.4 while dryslp were 1 or 1.5. The facua parameter values oscillated between 0.1 and 0.5. The results show that XBeach is reasonably modelling morphological changes like dune and beach erosion induced by storm event in Southern Baltic conditions and can be successfully applied to create an effective tool for hazard prediction. ADDITIONAL INDEX WORDS: beach and dune erosion, XBeach, numerical modelling, storm response, morphological changes

INTRODUCTION Morphological changes occurring in the coastal zone can be considered in different timescales. Nevertheless the most dynamic coastal changes take place during extreme events with simultaneous strong wave and sea level increase. Erosion of the beach and dune occurs as a result of large storm surges and high waves, what can further lead to overtopping the dune either by breaking the dune and, as a consequence, the hinterland area can be flooded. These areas are usually inhabited and have welldeveloped touristic infrastructure. Modelling such process creates a possibility to predict the hazards to the coast induced by the said phenomena and constitutes a crucial element which can generate a useful tool applied to coastal management. Such a tool has been created in the form of an online early warning system during the MICORE project (Morphological Impacts and Coastal Risk Induced by Extreme Storm Events, 7th FR Programme). The system has been elaborated for a 12 km long section of dune coast of the Southern Baltic Sea, which was a Polish pilot area. Eventually, nine similar systems have been developed across Europe, each one is operating in different coast and sea conditions (www.micore.eu). ____________________ DOI: 10.2112/SI65-xxx.1 received Day Month 2012; accepted Day Month 2013. © Coastal Education & Research Foundation 2013

The purpose of this paper is to demonstrate the usefulness of the XBeach model (1D) in modelling the changes of beach and dune morphology in terms of significant storm influence at Dziwnow Spit area. The recently developed depth-average (2DH) XBeach model is the one of the main components of the Early Warning System (EWS). The model has been calibrated and validated against (1D) flume tests (Roelvink et al., 2009; van Thiel de Vries, 2009) as well as field tests (2DH) performed on Assateague Island, Maryland (Roelvink et al., 2009) and on Santa Rosa Island, Florida (McCall et al., 2010). XBeach has been also successfully introduced in Europe at sand tidal coasts of Portugal (Vousdoukas et al., 2011), Italy (Harley et al., 2011) and Belgium (Bolle et al., 2011) as well as on gravel tidal coast of southwest England (Ruiz de Alegria-Arzaburu et al., 2011; Williams et al., 2012). No publications dealing with the Xbeach model application to the southern Baltic could be found. The Dziwnow Spit is located in the non-tidal Baltic Sea, in the western part of the Polish coast, separating Pomeranian Bay and Kamienski Lagoon. Maximum tidal range is limited to centimetres (Sztobryn et al., 2005); therefore, tides have minimal impact on coastal changes. This is the accumulation area of marine and eolian sediments. The beach and bottom sediments consist of fine and medium sand.

Journal of Coastal Research, Special Issue No. 65, 2013

2

Bugajny, et al.

Figure 1. Area of investigation showing the location of the eight cross-shore profiles chosen for modelling. The spit is 12 km long and 300-500 m wide at the narrowest point. Dune system is varied with height 3-12 m and width 50-150 m. The coast is accompanied by a 30-50 m width beach. The nearshore slopes down gently northwestwards. The 2-meter isobath is located 200-300 m off the shoreline, while the 5-meter isobaths in 350-650 m distance and the 10-meter in 800-1500 m distance (Figure 1). A system of 2-3 underwater longshore bars is clearly apparent, which reach a relative height of 2 m (Dobracki and Zachowicz, 2005). The whole area is an important tourist destination, with about 70,000 people visiting during the summer (permanent population in 2011 was 4112 citizens) (Central Statistical Office Report, 2012). Three municipalities are located on the spit: Dziwnow town, Miedzywodzie and Dziwnowek. The Dziwnow town is located on the narrowest part of the spit at the eastern side of the inlet. In some parts of the Dziwnow town, buildings are located directly on the dune system close to the open sea. According to long-term morphodynamic analyses, the coast of the investigated area is oscillating, with predominant tendency for erosion (Dudzińska-Nowak, 2006). At the beginning of 20th century, when an artificial channel (Dziwna) in the middle of investigated area was constructed (1892–1900) increasing erosion was observed. Afterwards different kinds of hydroengineering structures, such as seawalls and different kind of revetments, groynes, jetties and treatments like beach nourishment and vegetation plantings (Figure 1), were

implemented in order to protect threatened sectors of the cost (Racinowski and Seul, 1999; Dudzińska-Nowak, 2006). The analysis of regional variability of the wave climate in the Pomeranian Bay is based on the wave measurements taken during a period of four months (Paplińska, 2001) and a 44-year hindcast (1958-2001) of wave field over the Baltic performed within HIPOCAS project (Cieślikiewicz and Paplińska-Swerpel, 2008). The greatest measured height of an individual wave was 6.5 m and the maximum value of a measured wave period was 9.5 s. The highest significant wave height was 3.3 m. The mean value of the significant wave height over the period of measurements amounts to 0.75 m and mean significant period - 4.0 s. Narrow spectra with 1 Hz frequency at the peak were characteristic for the wave energy distribution. Only 10% of the time significant wave height exceeds 0.2 m and significant wave period 2.6 s, whereas 50% of the time exceeds 0.65 m and 4.2 s respectively. The significant wave height over 1.0 m occurred 28% of the time. 25% of waves moved in an easterly direction, 21% and 20% respectively SW and SE. Only 16% of the waves moved south. The analysis of wave modelling results shows that wave fields are not homogeneous in the whole area. The gradual increase (up to 50%) of yearly mean values of selected wave parameters can be observed going from the south-westerly of the Bay to northeasterly direction. Directional distribution of significant wave height is determined by wind climate and shape of the basin and prevails in easterly, south-easterly, south-westerly directions.



3

METHODS The research that were carried out consisted in registering the hydrodynamic parameters of storm event and morphological effects it caused on the coast of Dziwnow Spit. For this purpose, as a part of MICORE project, a monitoring of the Polish pilot area was being conducted, lasting from June 2008 till June 2010. Only one storm event that caused significant changes to the coast was recorded during this timeframe. It took place on 12-16.10.2009. This storm was characterised by maximum significant wave height (Hs) 3.75 m and wave peak period (Tp) 11.17 s. Maximum sea level reached 576 cm, i.e. 76 cm above mean sea level, which is 500 cm (the Normal Null Amsterdam). Wave parameters were obtained from the WAM model (Wave Model) Cycle 4 (WAMDI Group, 1988) provided by the Interdisciplinary Centre for Mathematical and Computational Modelling of Warsaw University (ICM). The WAM model for the Baltic Sea was validated as described by Cieślikiewicz and Paplińska-Swerpel (2008). The parameters consisted of hourly data of significant wave height, peak period and mean wave direction for a point located approximately 3 km to the North from town of Dziwnow (54,0625oN, 14,7664oE). The sea level data collected by a tide gauge placed in the Dziwna mouth were provided by the harbour master’s office in Dziwnow (location of the WAM point and tide gauge is showed in Figure 1). Sea level data were recorded every 4 h (Figure 2). The pre-storm morphological data consisted of bathymetric and topographic profiles provided by the Maritime Office in Szczecin. This high-resolution cross-shore profile measurement data with an interval of 500 m alongshore and length of 2000 m were made between 28-31 of August 2009, before storm season as a annual monitoring of the coast under the responsibility of the Maritime Offices in Szczecin. The measurements of the topographic part of the profiles were done using geodetic methods (vertical precision ±5 cm). The bathymetric part of the profiles were done with a high-resolution multi-beam echo-sounder. The vertical precision of the device is ±8 cm and the horizontal precision is ±20 cm. The post-storm topographic data were obtained from an aerial laser scanner TopEye (red LIDAR) on 30th November with density of 8 pt / m2 and with the horizontal and vertical accuracy x, y and z ±20 cm. Eight profiles of the coast located along the investigated area have been chosen for the XBeach model calibration. Going eastwards, the profiles are: 395.5, 394, 393, 392, 390, 389, 388 and 386.5. Names of the profiles indicate their location according to the kilometrage of seacoast used by Maritime Offices in Poland. The area of Dziwnow Spit was analysed in terms of morphological changes of beach, dune and nearshore and subsequently divided into 8 sectors of similar morphology (profile shape, beach width, dune height) and the existence of protection structures. The selected profile represent morphology of individual sector. A few dozen of XBeach (rev.1241) 1D simulation were applied to each of 8 profiles. For each profile a varying grid was created with a resolution of 20 m in the offshore and up to 3 m the onshore. All simulations were run for the same storm event lasting approx. 101 hours. Wave boundary conditions were implemented as time series of sea state (instant=41) with perpendicular direction to the coast. All simulations were run with morphological factor (morfac) set to 10 and with usage of breaker model option described in Roelvink (1993) (break=1). Additionally, the maximum courant number (CFL) was adjusted to 0.9, while a parameter indicating threshold depth for drying and flooding (eps) was set to 0.01 and viscosity coefficient for roller induced turbulent horizontal viscosity (nuhfac) increased to 1, pursuant to suggestions of XBeach model developers. A special

Figure 2. Time-series of significant wave height (Hs), peak period (Tp) and sea level during storm event used in XBeach simulation for Dziwnow Spit. attention was paid to a few parameters that have a significant impact on morphodynamic evolution, namely wetslp and dryslp responsible for avalanching process, hmin, the threshold water for concentration and return flow, facua, the parameter for the sediment transport related to the wave shape and lws, the longwave stirring. The results of each simulation were evaluated by juxtaposing pre-storm and post-storm profiles measured in-situ and post-storm profiles obtained from the simulation with the Brier Skill Score (BSS) as a criterion. BSS is commonly used statistic indicator for numerical model evaluation, especially for morphological changes. Correlation of the measured profiles (pre-storm – xb and post-storm – xp) and modelled profile (xm) can be expressed as follows:

 x x 2  m p BSS  1   2  x p  xb 

    

The classification of model performance for BSS is given as follows: BSS< 0 bad, 0-0.3 poor, 0.3-0.6 reasonable/fair, 0.6-0.8 good and 0.8-1 excellent (van Rijn et al., 2003). BSS values were only calculated for a land part of the profile allowing for beach and dune changes. The verification of the modelling results were carried out in two ways: on the basis of the highest value of BSS for each profile and on the basis of the highest mean BSS value of all profiles together for one set of parameters.

RESULTS AND DISCUSSION Tests carried out with the XBeach model had on purpose to indicate the set of parameters which best reflects the changes in beach and dune morphology caused by storm event in all 8 profiles located along Dziwnow Spit. A few dozen simulation were run that focused on following parameters: wetslp, dryslp, hmin, facua and lws. In the beginning of the research, the default values of said parameters were accepted (Roelvink et al., 2010). The result of simulation run with default values of considered parameters has negative BSS value ranged from -1.64 to -20.27 (bad adjustment) for all profiles. Therefore, their values were shifting as follows: wetslp was equal from 0.1 to 1, dryslp form 0.5 to 1.5, hmin from 0.01 to 0.1, facua from 0 to 0.5, while lws was turned off or on. Simulations with enabled lws parameter provided a very large erosion of both dune and beach, to an almost complete destruction of them in some profiles.


Bugajny, et al.

Table 1. Brier Skill Scores (BSS) for the best eight simulations for each profile. Also shown are the mean and standard deviation values for each simulation. Profiles 395.5 394 393 392 390 389 388 386.5 mean st.dev.

1 -4.35 -0.47 0.86 0.16 0.49 0.66 -1.54 0.25 -0.49 1.73

2 -1.12 0.19 0.76 0.56 0.87 0.89 0.15 0.83 0.39 0.68

3 0.35 0.45 0.57 0.42 0.86 0.82 0.76 0.90 0.64 0.22

Simulation 4 5 0.29 0.78 0.52 0.54 0.48 0.34 0.55 0.23 0.73 0.67 0.83 0.62 0.75 0.82 0.88 0.70 0.58 0.64 0.21 0.20

6 0.35 0.45 0.57 0.42 0.86 0.82 0.76 0.90 0.64 0.22

7 0.82 0.02 0.17 -0.02 0.44 0.38 0.53 0.42 0.35 0.28

8 0.29 0.52 0.48 0.55 0.73 0.83 0.82 0.88 0.64 0.21

Therefore, the lws parameter was turned off. Another observation concerned facua parameter. The higher value it received, the less erosion volume of beach and dune it caused. The increase of the wetslp parameter value caused greater erosion of the beach than dune, while the decrease resulted in inverted situation: significant dune erosion in relation to small beach erosion. The last dryslp parameter did not cause so visible differences to erosion process. Eight simulations that yielded the best results on each profile (the best BSS skill) were identified and labeled from 1 to 8, (Table 1). The mean BSS values for each simulation were calculated afterwards. The best adjustment, i.e. the highest mean BSS values (0.64) at standard deviation ± 0.22/0.21 were received for 4 simulations: 3, 4, 6 and 8. This is considered as good adjustment of the model. A similar result (BSS = 0.58 at standard deviation ± 0.20) was obtained from simulation 5. The rest simulations considerably diverge from the ones described above. The best adjustment for particular profiles together with a number of simulations is presented by a solid black line in Figure 3. As it is shown on the figure, the BSS value for each of 8 profiles exceeded 0.5. The best results, where BSS values exceed

Sim. 7

Sim. 5

Sim. 1

Table 2. Set of parameters of the XBeach model for the best eight simulations. Default value

1

2

3

6

7

8

hmin lws

0.05 1

0.05 0

0.05 0

0.05 0

0.05 0

0.05 0

0.05 0

0.05 0

0.05 0

facua

0

0.1

0.2

0.3

0.3

0.4

0.3

0.5

0.3

wetslp

0.3

0.3

0.3

0.3

0.4

0.3

0.3

0.3

0.4

dryslp

1

1

1

1.5

1

1

1

1

1.5

393, 390, 389, 388, 386.5), whereas for the two last profiles (394, 392) the results are reasonable which means that BSS value is between 0.3 and 0.6. The values of particular parameters of the best 8 simulations are presented in Table 2. The hmin parameter value in all simulations was set to 0.05, wetslp equalled 0.3 or 0.4 while dryslp was 1 or 1.5. The facua parameter which is responsible for onshore transport oscillate between 0.1 and 0.5. It is worth to notice that facua parameter is the most important, because it is the only parameter, which values are the most variable. The variability of facua for particular profiles is presented in Figure 3. As it follows from spatial distribution of these values on the diagram, high values of facua are located on the edges of the investigated area. Facua values of 0.5 or 0.4 occur in the western part, on profiles 395.5 and 394, located on the unprotected coast. The eastern part of the area, profiles 388 and 386.5 show facua 0.3, where the groynes protect the coast only. The lowest values of facua (0.2 and 0.1) occurred on profiles 389, 390, 392 and 393 located on relatively heavy protected area. Different values of this parameter reflects an impact of different kind of hydroengineering structures for coastal processes. The best result in one simulation for all profiles together was obtained in simulation 4 and 8, which was characterised by hmin=0.05, dryslp=1 or 1.5, facua value increased to 0.3 and wetslp value set to 0.4 (Table 2). The BSS values for particular

Sim. 2

0,86

0,82

Simulation 4 5

Parameter

Sim. 2

Sim. 2 Sim. 4 and 8

0,87

0,89

Sim. 3 and 6

0,90

0,9

0,82 0,88 0,83

0,52

0,5

0,8

0,82

0,7

0,73

0,56

0,54

0,6

0,5

0,55 0,48

0,4

0,4

0,3 0,3

0,29 0,2

0,2

0,2

390

389

0,3

0,2 0,1

0,1 396

395

394

1

393

BSS / facua parameter

4

0 392

391 Profiles

388

387

386

Figure 3. The best adjustment of Brier Skill Scores (BSS) for particular profiles together with a simulations number (solid line), mean BSS values for particular profiles for the simulation 4 (dashed line), values of the facua parameter of the best simulation for each profile (triangles).



5

Figure 4. Post-storm XBeach result (1) the best simulation for the profile (dotted line with points as markers), (2) the best simulation for all profiles (dotted line with crosses as markers) compared to the measured pre- and post-storm profiles (solid and dashed lines, respectively). profiles of this simulation is presented by dashed line in Figure 3. The best adjustment of this simulation is reached in the eastern part of the investigated area at good and excellent level, whereas in the western part at reasonable and on the westernmost profile – poor. That high value of facua parameter seems to be proper for unprotected coast, where onshore transport cannot be neglected. Simulations results for each of 8 profiles, both of the highest BSS for given profile as well as for simulations of the highest mean BSS value for all profiles are presented in Figure 4 for comparison with pre- and post-storm profiles. It can be seen that the XBeach model simulates well both: dune erosion and beach erosion along all the profiles. The biggest discrepancy between the simulations could be observed at profiles 395.5 and 393. At 395.5 profile, the beach erosion is overestimated (for simulation with max mean BSS for all profiles) and the opposite situations is visible at 393. However, beach erosion for other profiles is well represented. According to model assumptions (Roelvink et al. 2010), XBeach does not model beach recovery while the storm is calming down, what was also confirmed in the research carried out on gravel coast by Ruiz de Alegria-Arzaburu (2011). It should be realized that post-storm registration of topography was carried out over a month after the storm event and therefore recreated beach bar is clearly visible on every profile. It is a typical situation that occur after the storm on this type of coast. This feature of the profile constitutes the greatest discrepancy between post-storm survey data and XBeach results, what influences on obtaining lower BSS values than ones that would

have been obtained if the measurement had been taken directly after the storm. So far, the implementation of the XBeach model for non-tidal seas has not been published. Among the studies performed on tidal water areas, wave conditions similar to Polish occur on the Adriatic Sea in Northern Italy (Harley et al., 2011), where wave climate is generally small. In those research the best XBeach model adjustment was obtained for a storm with significant wave height of Hs = 3.91 and storm surge peak of WL = 0.92 m. The BSS value thereof, which was also calculated for the terrestrial part of profile, was equal to ca. 0.56.

CONCLUSION The carried out research concerned the adaptation of the XBeach model for the first time in Poland to a non-tidal Baltic Sea of dune coast represented by Dziwnow Spit. A single storm event that occurred in 2009 and caused a significant beach and dune erosion was selected for the XBeach model 1D simulation on 8 profiles located within the investigated area. The model skill were tested on the base of statistical descriptor BSS. The highest BSS values reached from 0.54 to 0.9 depending on the profile, what yielded reasonable, good and excellent adjustment. The mean BSS value equaled 0.64 for the best simulation for all profiles at once what is good result. The best performance of XBeach model for each profile was obtained by deactivating longwave stirring lws and keeping hmin parameter value to 0.05 in all simulations. Values of wetslp were


6

Bugajny, et al.

equalled 0.3 or 0.4 while dryslp was 1 or 1.5. Values of facua parameter oscillated between 0.1 and 0.5. Taking into account all profiles together, the best adjustment was obtained when hmin=0.05, wetslp=0.4, dryslp=1 or 1.5 and facua=0.3 or 0.4. Further calibration of the XBeach model in 1D, which would include the nearshore area, is planned in the future, when bathymetric post-storm data become available. A 2DH model taking consideration of different types of hydroengineering structures located along the study area is also under development. The obtained results show that XBeach model fit the beach and dune morphology changes well in Southern Baltic conditions and can be successfully applied to create an effective tool for hazard prediction.

ACKNOWLEDGEMENT This research was supported by the European Community's Seventh Frameworks Programme under grant agreement no. 202798 (MICORE Project - Morphological Impacts and Costal Risk Induced by Extreme Storm Events). The authors would like to thank ICM (Interdisciplinary Centre for Mathematical and Computational Modelling) for providing wind data for the WAM model calculation and the Maritime Office in Szczecin for providing morphological and sea level data.

LITERATURE CITED Bolle, A., Mercelis, P., Roelvink, D., Haerens, P. and Trouw, K., 2011. Application and validation of XBeach for three different field sites. In: Smith, J.K. and Lynnet, P. (eds.), Proceedings 32nd Conference on Coastal Engineering (Shanghai, China), Coastal Engineering, Special Issue No. 32, sediment.40. doi:10.9753/icce.v32.sediment.40. Central Statistical Office Report, 2012. Narodowy Spis Powszechny Ludności i Mieszkań. Warszawa, Poland, 178p. Cieślikiewicz, W. and Paplińska-Swerpel, B., 2008. A 44-year hindcast of wind wave fields over the Baltic Sea. Coastal Engineering, 55 (11), 894-905. Dobracki, R. and Zachowicz, J., 2005. Mapa Geodynamiczna Polskiej Strefy Brzegowej Bałtyku. Szczecin: Państwowy Instytut Geologiczny Oddział Pomorski, skala 1:10,000, 2 arkusze. Dudzińska-Nowak, J., 2006. Coastline long-term changes of the selected area of the Pomeranian Bay. In: Tubielewicz, A. (ed.), Proceedings 8th International Conference LITTORAL (Gdańsk, Poland), Coastal Dynamic, Geomorphology and Protection, pp. 163–170. Harley, M., Armaroli, C. and Ciavola, P., 2011. Evaluation of XBeach predictions for a real-time warning system in Emilia-Romagna, Northern Italy. In: Furmańczyk, K. (ed.), Proceedings 11th International Coastal Symposium (Szczecin, Poland), Journal of Coastal Research, Special Issue No. 64, pp. 1861-1865.

McCall, R.T., van Thiel de Vries, J., Plant, N.G, van Dongeren, A., Roelvink, J.A., Thompson, D.M. and Reniers, A.J.H.M., 2010. Twodimensional time dependent hurricane overwash and erosion modeling at Santa Rosa Island. Coastal Engineering, 57, 668-683. Paplińska, B., 2001. Specific features of sea waves in the Pomeranian Bay. Archives of Hydro-Engineering and Environmental Mechanics, 48 (2), 55-72. Racinowski, R. and Seul, C., 1999. Brzeg i podbrzeże Mierzei Dziwnowskiej. In: Borówka, R.K., Młynarczyk, Z. and Wojciechowski, A. (eds.), Ewolucja geosystemów nadmorskich południowego Bałtyku. Bogucki Wyd. Nauk., Poznań-Szczecin, pp. 115-120. Roelvink, J.A., 1993. Dissipation in random waves groups incident on a beach. Coastal Engineering, 19, 127-150. Roelvink, D., Reniers, A., van Dongeren, A., van Thiel de Vries, J., McCall, R. and Lescinski, J., 2009. Modelling storm impacts on beaches dunes and barrier islands. Coastal Engineering, 56 (11-12), 1133-1152. Roelvink, D., Reniers, A., van Dongeren, A., van Thiel de Vries, J., Lescinski, J. and McCall, R., 2010. XBeach Model Description and Manual. Unesco-IHE Institute for Water Education, Deltares and Delft University of Technology. Report June, 21 2010 version 6. Ruiz de Alegria-Arzaburu, A., Williams, J. J. and Masselink, G., 2011. Application of XBeach to model storm response on a macrotidal gravel barrier. In: Smith, J.K., and Lynnet, P. (eds.), Proceedings 32nd Conference on Coastal Engineering (Shanghai, China), Coastal Engineering, Special Issue No. 32, sediment.39. doi:10.9753/icce.v32.sediment.39. Sztobryn, M., Stigge, H.-J., Wielbińska, D., Weidig, B., Stanisławczyk, I., Kańska, A., Krzysztofik, K., Kowalska, B., Letkiewicz, B. and Mykita, M., 2005. Storm Surges in the Southern Baltic Sea (western and central parts). Rostock Berichte des Bundesamtes für Seeschifffahrt und Hydrographie, 39. 74 p. Vousdoukas, M.I., Almeida, L.P. and Ferreira, Ó., 2011. Modelling storminduced beach morphological change in a meso-tidal, reflective beach using XBeach. In: Furmańczyk, K. (ed.), Proceedings 11th International Coastal Symposium (Szczecin, Poland), Journal of Coastal Research, Special Issue No. 64, pp. 1916-1920. WAMDI Group, 1988. The WAM model-a third generation ocean wave prediction model. Journal of Physical Oceanography, 18, 1775–1810. Williams, J.J., Ruiz de Alegria-Arzaburu, A., McCall, R. and van Dongeren, A., 2012. Modelling gravel barrier profile response to combined waves and tides using XBeach: Laboratory and field results. Coastal Engineering, 63, 62-80. van Rijn, L.C., Walstra, D.J.R., Grasmeijer, B., Sutherland, J., Pan, S. and Sierra, J.P., 2003. The predictability of cross-shore bed evolution of sandy beaches at the time scale of storms and seasons using processbased Profile models. Coastal Engineering, 47 (3), 295-327. van Thiel de Vries, J.S.M., 2009. Dune erosion during storm surges. Amsterdam, Netherlands: IOS Press, 202p.
