CHAPTER 6. SPH SIMULATION 104

levels and wave conditions. The slope of the sediment ramp directly fronting the seawall

was also altered. Three different mean sea levels were tested, namely present day levels

and then 0.5m and 1m increases on this. In order to generate waves in a SPH model

a wave generator is necessary. A piston wave maker moving horizontally was chosen to

generate 50 regular, symmetrical waves without wave group oscillation. Three different

wave heights were assessed: 0.07m, 0.10m and 0.12m at a frequency of 0.3Hz. When

scaled to reality at Yanchep these are equivalent to wave heights of 1.4m, 2.0m and 2.4m,

respectively, with a period of 15s. The model had a water particle spacing of 0.007m. Each

simulation was run for 30s and the position and velocity of every particle was extracted

every 0.1s.

To assess the potential for sand to overtop the structure, a model simulating the

movement of sand particles was added to the SPH simulation. The model is based on

a simple Lagrangian tracking formulation. In this approach, sand is considered as a

Lagrangian particle being advected by the surrounding water particles. The advection of

the sand particle is calculated as:

dx

dt= uSPH +A

√ν (6.1a)

dy

dt= ws + vSPH +A

√ν (6.1b)

where uSPH and vSPH are the advective velocity; ws is the settling velocity and A is a

normally distributed random number and ν is a diffusivity term calculated as ν = 6Evδt

where Ev is equal to the standard deviation of the velocity within the sediment kernel

which is the area within 1.2mm of the sand particle. The advective velocity is simply

calculated as the averaged velocity of the water particle located within 1.2mm of the sand

particle. This distance corresponds to three times the SPH kernel size. The fall velocity

corresponds to the scaled fall velocity of sediment at Yanchep as 0.012ms−1. Particles are

initially released along the bottom when the velocity inside the sediment kernel exceeded

0.05ms−1. The discrete particle model was not integrated in the SPH model, instead all

the sand calculations were performed after the simulation of the hydrodynamics using the

saved outputs.

6.4. RESULTS AND DISCUSSION 105

6.4 Results and discussion

The model shows wave breaking near the sea wall. Complex flow structures resulting from

the breaking waves are predicted by the model (Figure 6.3). Figure 6.4 shows the vertical

current velocity every 0.5s for one of the simulations. The first snapshot (Figure 6.4a)

shows the bore of the broken wave propagating on the platform. The wave hits the

structure and creates a reflected wave that propagates back toward the wave maker and

later collides with the main incoming wave (Figure 6.4c,d). The wave steepens and breaks

just in front of the sea wall (Figure 6.4g,h). The bore hits the sea wall producing a splash

and the cycle restarts (Figure 6.4i,j,k,l).

Particles initially located on the sea-bed of the model near the sea wall are advected

toward the surface, as a response of the wave breaking, and then are projected onto the

platform. The vertical velocity near the sea wall reaches 0.5ms−1. When this is scaled to

prototype it corresponds to a speed of 2.2ms−1. The reflected wave plays an important role

in the timing of the wave breaking, but does not influence the volume of water overtopping

the platform.

Near the seawall, the model predicts a strong bottom velocity pulse (>0.6ms−1) when

the wave hits the structure (Figure 6.5, red line). This velocity is linked with the interac-

tion with the structure and is not present 1m away (Figure 6.5, black line) where velocities

remain below 0.4ms−1. The velocity pulse has been previously described in the study of

wave impact load on coastal structures (Cuomo et al., 2011).

The wave pulse is systematically present on every wave, including the first wave, sug-

gesting that it is not a result of interaction with the reflected wave. In addition, the wave

pulse is present during both water levels tested in the model (Figure 6.6). The higher

mean sea level reduces the intensity of some of the pulses and even prevents smaller pulses

from occurring. However, the larger pulses are mostly unaffected. Larger waves resulted

in larger pulses (Figure 6.7). The largest wave also resulted in more pulses although it is

likely to be the result of the interaction between the wave breaking and the backwash.

The velocity pulses observed in the simulations are likely to occur in Yanchep as well.

In Yanchep, the pulses should result in sediment resuspension. However, this study does

not evaluate how much sediment could be transported onto the platform through this

mechanism. Field observations suggest that a significant volume of sediment is projected

CHAPTER 6. SPH SIMULATION 106

onto the reef platform, but only when the sediment ramp fronting the sea wall is high

enough.

Simulation of suspended sand transport shows that in the case of the vertical seawall

few sand particles can overtop the structures. Most particles initially at the bottom are

resuspended but are advected seaward by the undertow. This is one of the mechanisms

that creates the scour step in the first place. The wave breaking on the structure creates

a pulse of velocity near the bottom that resuspends the sand. The average current then

advects the suspended sand seaward. However, reducing the slope of the seawall increased

the number of particle overtopping the reef and reaching the lagoon by a factor of six

(Figure 6.8).

The simulation shows that the sand is more likely to reach the lagoon if the slope

of the reef is reduced. In Yanchep lagoon the slope of the reef is near vertical but the

sand successfully overtops the structure and builds the perched beach every summer. We

propose that this is happening when sand builds up against the sea side of the reef forming

a sand ramp. When this ramp reaches near the top of the reef the sand easily overtops

the reef and feeds the beach. However for such a sand ramp to form, a large supply of

sand is required to reach the reef in a short amount of time to overcome the effect of the

scour step. This could occur when the nearshore sand bars that form seaward of the reef

during the winter storms are pushed inshore by the strong summer sea-breezes. When the

sand bar reaches the reef, the bedload transport would push the sand against the reef and

form a sand ramp. Although this process has not been observed yet in Yanchep, similar

example of sand bar moving onshore has been observed in Scarborough beach and detailed

bathymetry data from Two Rocks marina (10 Km North of Yanchep) suggest that this

may happen there as well.

6.5 Concluding remarks

This chapter presents results of a study aimed at improving understanding of the mecha-

nism of cross-shore transport of sediment on the Yanchep perched beach. The study uses

the flexibility of a SPH model to simulate the complex flows occurring with wave breaking

near a natural sea wall. The model shows very realistic results including the presence of

velocity pulses previously observed by others (Cuomo et al., 2011). The validity of SPH

6.5. CONCLUDING REMARKS 107

0.5

1.0

1.5

m

4 5 6

m

0.0 0.2 0.4 0.6 0.8 1.0

ms−1

Figure 6.3: SPH model output showing the wave breaking across the reef. Shading showthe absolute velocity of water particles

models with wave breaking and flow near structures has been previously verified (Crespo

et al., 2011) but this study confirms the usefulness and flexibility of SPH models. The

simulations described show very large velocities near the structures reaching the sea-bed.

These velocities suggest that sediment resuspension and transport above the reef platform

of the perched beach is possible. However, it appears clear from this analysis of sand

transport that the sand accreting every summer on the bluff beach does not overtop the

full height of the bluff to come to the beach. Instead a sand ramp may form along the

bluff using the sediment brought in by the sea-breeze littoral drift. This ramp then al-

lows the sand to reach the lagoon and feed the beach. It is clear that observations of the

formation of the sand ramp and the relation to the timing of the accretion on the beach

would confirm this hypothesis. More data need to be collected from perched beaches to

fully understand the mechanism of recovery and accretion. In fact the change in sea level

could dramatically change the conditions during which the beach accretes and could also

lead to full accretion of the bluff beach in summer occurring less often. This would have

strong consequences on the beaches down drift that are affected by the seasonal variation

of this perched beach. Finally this study demonstrates the feasibility of fine scale sand

transport in SPH simulation in a coastal engineering perspective.

CHAPTER 6. SPH SIMULATION 108

a b

c d

e f

g h

i j

k l

Figure 6.4: Snapshots of the vertical velocity every 0.5s from 9.5s to 15s into the simulation

6.5. CONCLUDING REMARKS 109

Figure 6.5: Near bottom velocity at 4.7m (black line) and 5.1m (red line)

Figure 6.6: Near bottom velocity at 5.1m during a mid sea level (0.90m) in black line anda high sea level (1.0m) in red line

CHAPTER 6. SPH SIMULATION 110

Figure 6.7: Near bottom velocity at 5.1m during for small wave height (0.07m)(Blackline), medium wave height (0.10m)(Blue line) and large wave height (0.12m)(Red line)

a

b

Figure 6.8: Simulated sand particles (red dots) at the end of the simulation of the initiallagoon design (a) and with a sand ramp fronting the reef (b).

Chapter 7

Discussion

7.1 Introduction

This chapter discuss the overall findings on the sensitivity of perched beaches to waves, sea

level and reef topography and how the range of numerical models at a cascade of spatial

and temporal scales was used in this research. The first section summarises the original

contribution of the research, followed by a section discussing the implications of the key

findings. Then section 7.4 discuss aspects of this research that could be improved in the

future.

7.2 Original contribution

The research presented in this thesis assessed the sensitivity of perched beaches to the

wave energy they receive from offshore and the topography of reefs fronting these type

of beaches. Although the research site was a series of perched beaches on a 3km stretch

of coastline near Yanchep in Western Australia, the research focused on a much wider

range of spatial and temporal scales. This allowed us to study the effect of offshore wave

climate variability, the transformation of waves as they cross the continental shelf and

finally the fine scale hydrodynamics and sand transport on perched beaches. This was

achieved with the use of different numerical models simulating processes at a range of

spatial and temporal scales from the longer term description of the offshore wave climate

in the Indian Ocean basin down to the sand transport associated with a single wave on

Yanchep reef. The main findings and the original and novel contributions of this research

CHAPTER 7. DISCUSSION 112

are summarised in the following paragraphs.

The variability and trends in the mean significant wave height offshore of Western

Australia were quantified for the first time over a multi-decadal time scale. Analysis of

the wave climate showed that the number of large wave events in Western Australia did

not significantly change despite the increasing number of wave events in the Southern

Indian Ocean. The research also showed that the mean latitude of large wave events is

negatively correlated to the Southern Annular Mode. Therefore, the Southern Annular

Mode modulates the inter annual variability of the wave height but the swell generated

from the increasing number of storms in the Southern Ocean contributes to increasing

the mean annual wave height offshore of Western Australia. These findings are impor-

tant to understand the transport and mixing of surface water offshore and further our

understanding on the climate of the southern hemisphere storm belt.

To better understand how the variability of the wave climate offshore translates to

the nearshore, the dissipation of an extreme storm on the continental shelf was simulated

using a number of numerical models coupled innovatively over different spatial scales. The

storm of the 20th of July 2009 did not cause significant erosion along the coast of Western

Australia. The simulation of the generation, propagation and dissipation of the storm

show that the wave energy only reached the coast after the peak in the storm surge. The

relatively low water level allowed the swell to be quickly dissipated on the reefs of the

continental shelf. Simulations of the sensitivity of wave dissipation to the sea level suggest

that sea level rise may cause an increase of 14 to 16% of the wave height during future

storms. The coupling of different spatial scale model can be used to hindcast the erosion

of past storms and forecast the impact of future storms.

Although the conditions during storms are uniform along the coast near Yanchep,

the response of the perched beaches was very variable. To understand the role of the

variation in reef topography on perched beaches morphodynamics, numerical simulations

of the hydrodynamics and sand transport were undertaken on a high energy perched

beach for the first time at high resolution. The validated simulations showed that the

beach response to a storm was highly dependent on the variation of topography of the reef

fronting the perched beach, which has important repercussions for coastal management

and protection. The variation in the topography of the reef caused the formation of current

jets that enhanced the alongshore sand flux. Near the edge of the reef, jet currents veered

7.3. IMPLICATIONS OF KEY FINDINGS 113

offshore forming circulation patterns that locally enhanced the erosion.

Such a modelling exercise required a large number of simulations of nearshore waves,

hydrodynamics and sand transport at fine resolution and for several weeks. Traditional

models such as XBeach require supercomputing facilities to run with such high resolution

in a timely manner. However in this research a clone of XBeach was developed to run

on the Graphic Processing Unit (GPU) of a desktop computer. Using the processing

capability of high-end GPU for morphodynamics modelling allowed the simulations to run

more than 30 times faster than traditional models. XBeach GPU is now being prepared

for distribution to the scientific community and the public.

In between storms some areas of Yanchep perched beaches were observed to accrete.

However, recovery and accretion on perched beaches is affected by the scour step formed

seaward of reefs. In Yanchep the step can reach 3m high and previously this was thought

to prevent sand from reaching the beach. Fine scale SPH hydrodynamic simulations of the

interaction of wave breaking on a structure suggest that sand at the base of the structure

would be resuspended but this sand is more likely to be transported offshore rather than

onto the beach. Simulations showed that sand would more likely reach the beach if a sand

ramp is present in front of the reef. Such a sand ramp is believed to form in summer and

allow the accretion of the beach.

7.3 Implications of key findings

7.3.1 Multiscale modelling approach

The multi-scale methodology presented in this study differs from the unstructured grid

coupling system used in models such as ADCIRC (Dietrich et al., 2011b,a). Coupled un-

structured grids offer a seamless way to simulate waves, circulation and sediment transport

from the regional to the local scale while offering an excellent compromise between high

resolution and short run times. However, the SWAN wave model used for the coupling

presents some limitations. SWAN is not recommended for use at the ocean basin scale and

does not offer as many parameter controls as the WW3 model. The WW3 results from

this study could have easily been transferred to the continental shelf with a regional un-

structured coupled SWAN model. This would reduce the nesting error as the unstructured

grid offshore could be designed to closely match the resolution of the WW3 output.

CHAPTER 7. DISCUSSION 114

Another limitation of SWAN comes from the inability to include wave groups. The

inclusion of wave groups is also prevented by the long coupling time step between SWAN

and the hydrodynamic model, which is typically 1 to 10 minutes. Energy from wave groups

can vary in a few seconds because they are generated from the interaction of multiple waves.

Therefore a coupling time step of at least 1 second is required to resolve wave groups in

a coupled model. This results in a lack of long bound and infragravity waves generated

from the dissipation of wave groups in the unstructured model coupling system. These

processes have been shown to play a significant role inside fringing reefs (Pequignet et al.,

2009) as well as in controlling overtopping and erosion of dune systems because most of

the gravity wave energy is located on the infragravity band (Roelvink et al., 2009). Field

data from Gallop et al. (2012a) at Yanchep during the 2010 storm showed a significant

amount of energy in the infragravity band. In the simulations presented in Chapter 5, the

subaerial beach morphology and erosion of the dunes was due to the action the wave groups

infragravity waves. Consequently, the only way to include the processes associated with

wave groups with an unstructured coupled model system is to couple the unstructured

models with a model such as XBeach as in the methodology presented in Chapter 4.

The methodology presented in Chapter 4 is not a substitute for unstructured model

coupling but could complement it by benefiting from models that include features, such as

wave groups, that are not implemented in the regional scale models. Ongoing development

in WW3 will allow the use of unstructured grids and XBeach is being implemented to

incorporate wave input along the boundary that will allow a seamless nesting to and from

an unstructured coupled model. This could help improve the accuracy of morphological

models.

Improvements in multiscale coupling will not resolve some major issues of multiscale

simulation of wave climate. Multi-decadal wave hindcast at a basin scale is possible

because the models working at these scale have been optimised to do so and because global

wind products are readily available. However, this is not the case for the regional or beach

scale. Regional and beach scale model are much slower to run than global model because

of the finer resolution that reduce the time-step and increase the number of iterations

needed for the model to converge and because regional and beach model include more

processes. Regional models also require more input (wind, water levels, currents) which

may not be available. For example, there are no available wind products at the resolution

7.3. IMPLICATIONS OF KEY FINDINGS 115

needed for multi-decadal regional wave simulations in South West Australia and the global

wind products are not suitable because it does not include processes like cyclones or land

and sea-breezes. In this study, wind input were created for recent events for which wind

data was available but the regional and the local wind data was not available for the 40

years selected to hindcast the wave climate of the Southern Indian Ocean. Being able to

simulate the variability of wave climate nearshore is critical to better evaluate how changes

in the wave climate will affect the sediment budget and affect coastal erosion.

7.3.2 Comparison between present wave climate trends and predicted

future wave climate

In Chapter 3, the wave climate offshore of Western Australia was described and the vari-

ability and longer term changes in the wave climate between 1970 and 2009 were assessed.

Most importantly, these changes have been shown to include an increasing annual mean

significant wave height of nearly 0.004m/year (Figure 3.9), but no statistically significant

changes in the large wave events in the Western Australian region were found to have

occured over this period. These findings are consistent with previous findings from Hemer

(2010) and Young et al. (2011). However the trend presented in this research is in contra-

diction with the changes predicted in climate change studies by Wang and Swail (2006),

Mori et al. (2010) and Hemer et al. (2013).

Until recently multi-decadal simulations of the wave climate could not be calculated

using wave model because the resolution of the wind input from Global Circulation Models

(GCM) were too coarse spatially and temporally to adequately simulate wave events.

However the wave height could be assessed to an extent using more simple statistical

approaches. Wang and Swail (2006) correlated the wave heights around the globe to the

atmospheric pressure at mean sea level and used this relationship to predict future wave

climate using the mean sea level atmospheric pressure from GCM models. Using this

technique, they produced a map of the difference between the present wave climate (1990)

and the future wave climate (2080). This map shows a negative difference (i.e. smaller

future wave) in the seasonal wave height in the south west of Australia and a positive

difference (i.e. larger future waves) in the storm belt. This method, however, ignores the

distant swells which, as results from Chapter 3 showed, are a dominant feature on the coast

of Western Australia. Although more recent GCM have a finer resolution, they are still too

CHAPTER 7. DISCUSSION 116

Table 7.1: Predicted wave climate change.

Changes between future andpresent wave height in thesouthern Indian Ocean

Future climate Authors

-4% to 0% 2080 Wang and Swail (2006)-10% to 0% 2075—2099 Mori et al. (2010)-6% to -3% 2070—2099 Hemer et al. (2013)+18% 2099 Chapter 3

coarse to force a wave model. However these GCM could be “downscaled” to a resolution

suitable for wave simulation. Mori et al. (2010) used a downscaled GCM developed by the

Japanese Meteorological Research Institute and the Japan Meteorological Agency with a

SWAN global wave model. They also found a decrease in the future (2075-2099) mean

wave height near Western Australia and an increase of the future mean wave height in the

storm belt. Similarly Hemer et al. (2013) used two GCM models that were downscaled to

a fine resolution to force a global wave model using WW3. The GCM models included a

present climate and a future climate period. Hemer et al. (2013) used this to correct the

GCM wind for biases. They also found an increase in the mean wave height in the storm

belt and a decrease in the mean wave height in Western Australia.

The future climate predictions from these three studies are summarised in Table 7.1

as changes between present and future mean wave height as a percentage of the present

wave height. Also listed in the table, the percentage change of the mean wave height if

the trend found in this study is extrapolated unchanged until 2099.

The future wave climate predictions are all relatively consistent and all give a very

different answer from the extrapolation of the results from Chapter 3 and suggest that

different processes will influence the wave climate in the future. This also suggests that,

if the future predictions of wave climate are accurate, the trends in the present day wave

climate will go through a reversal which could mean that dramatic changes will occur in

the number and track of large wave events in the Southern Indian Ocean. Clearly further

research is needed to better understand the wave climate of the Southern Ocean and the

effect of climate change.

7.3. IMPLICATIONS OF KEY FINDINGS 117

7.3.3 Effect of climate change and sea level rise on Western Australian

beaches

Predicting the long term change in the morphology of beaches is a particularly challenging

task. It requires long term monitoring and detailed understanding of the processes that

dominate the morphodynamics of such beaches. In addition, changes in the wave climate

and sea level rise add uncertainties in the prediction. Using the results of this research

in addition with the results presented by Gallop et al. (2011a,b, 2012b,a,c) the potential

effect of climate change and sea level rise to perched beaches in Yanchep can be assessed.

A summary of the potential changes in the beach morphology due to increase wave height

and rising sea level is given below.

Wave climate models predict a reduction of up to 10% in the offshore mean annual

wave height. The high end of this prediction corresponds to about twice the inter-annual

variability of the wave height but the most likely prediction correspond to half the inter-

annual variability. Wave climate change models are unfortunately not reliable enough to

predict changes in the mean wave direction. In Yanchep, no significant correlations were

found between the offshore mean wave height and the beach width (Gallop et al., 2012c).

However, the reduction in the mean wave height offshore is expected to lead to a reduction

of the annual variability of beach width.

Sea level rise is likely to have more consequences than changes in offshore wave climate

on the evolution of the beach morphology in Yanchep. The beaches are likely to slowly

adapt to higher sea levels but our knowledge of the beach behaviour is insufficient to

speculate on the long term response of Yanchep perched beaches to sea level rise. However,

Chapter 4 shows that extreme erosion occurs in conjunction with sustained high water

levels. Therefore, higher sea level will likely cause more erosion during storm events.

This is also suggested by the results of the simulation of the 2010 storm on lower rock

topography (Figure 5.14b). In addition to modifying the morphology of the beach, sea

level rise will reduce the effect of wave dissipation (depth-induced breaking and bottom

friction) on the reef offshore. Therefore, higher sea level could result in higher annual mean

wave height near the shore and a 3 to 8% increase of larger waves during storms. This

effect could compensate the reduction in the mean offshore wave height and overshadow

the effect of wave climate change on the beach. It is, however, likely to cause more erosion

CHAPTER 7. DISCUSSION 118

during storm events.

It is likely that changes in wave climate and sea level rise will lead to more erosion

during storms and a reduced inter-annual variability in beach width. However, the effect

of changes in the oceanographic and meteorological forcing will not necessarily reflect in

the same variations in beach morphology along the coast. In particular, perched beaches

show a non-linear relationship between the fronting reefs and the wind and waves. Gallop

et al. (2012c) showed that there are no significant correlations between the inter-annual

variability of Yanchep beach width and the wind, wave or water level. There is, however,

an inverse correlation between the Bluff beach width and the Lagoon beach width. This

indicates that the exchange of sediment between different sections of perched beaches play

an important role in the variability of the beach width. This suggests that the prediction

of changes in the morphology of perched beaches requires an assessment of the changes in

the surrounding beaches. Therefore, predicting long term change on perched beaches may

require an assessment of the effect of climate changes on an entire section of coastline. The

complex relationship between the meteorology, oceanography and the beach variability

warrants the use of longer term modelling of the morphodynamics of perched beaches at

spatial scales that includes the surrounding beaches.

7.4 Future work

Following on from the points discussed in the previous section, this section describes

additional work that could be undertaken in the future to enhance the research on perched

beaches.

7.4.1 Mapping the roughness of the reefs

Chapter 4 and 5 showed that the dissipation of waves at a regional scale as well as the

dissipation of waves at the beach scale is highly sensitive to the roughness of reefs. Yet,

at present, there are no practical ways to map the roughness reefs. This roughness can be

variable depending on the type of reef. Studies of coral reefs have shown that the bottom

wave dissipation parameter can vary from 0.07 to 0.7 from the inshore reef flat with small

roughness elements to external reef with metric roughness elements (Pequignet et al.,

2011). The wave bottom friction can be linked to the roughness using formulation such as

7.4. FUTURE WORK 119

Swart (1974). Mapping the reef roughness requires sophisticated techniques such as the

deployment of underwater vehicles, side-scan sonar, or LiDAR. All these methods require

an analysis of the the correlation between the apparent roughness of the reef and the

friction factors. This requires a relatively large scale field experiment where the hydraulic

roughness, wave friction parameter and the roughness of reefs is measured. Perhaps the

development of cheap autonomous wave recorders would facilitate such experiments.

7.4.2 Recovery and accretion in beaches

The beach elevations observed during the storm of 2010 showed that recovery occurs during

erosion events and between storms. In some locations the recovery after the storm may

have been hindered by the presence of the reef but no direct observation of the process

could be made. As a result of the obvious coastal management implication, the research

has focused on beach erosion and a lot remains to be learned about the processes that

drive recovery. In the case of perched beaches, the process of recovery is complex because

of the presence of reefs. Accretion events are difficult to predict and more should be done

to monitor beaches and hydrodynamics in calm conditions. A better understanding of

the recovery and accretion of beaches could lead to more accurate implementation of both

recovery and erosion in process-based morphodynamics models. In turn this will allow for

more accurate long term simulations of beach morphodynamics. Such simulations could

provide coastal managers with better insight of the response of beaches to sea level rise

and climate change.

7.4.3 GPU computing

This study has showed that GPU computing in coastal engineering is not only valuable

for fine scale simulation of complex computational fluid dynamics models but also benefits

more classical morphodynamic models. This study has demonstrated that a significant

reduction in computation time can be achieved with simple GPU implementation of state

of the art models. Such innovation in coastal modelling should be encouraged and will

significantly benefit the coastal engineering community with present model and with fur-

ther development in the modelling of beach morphodynamics which are likely to be more

computationally demanding.

CHAPTER 7. DISCUSSION 120

Chapter 8

Conclusion

The overall aim of this thesis was to better understand the morphodynamics and the

sensitivity of perched beaches to sea level, waves and the reef topography. This was

achieved by using a range of numerical simulations that evaluated the role of processes at

different spatial and temporal scales. It was found that:

� Significant wave heighs and peak periods significantly increased near southwest WA

over the past 40 years. It appears that this is a direct consequence of the intensi-

fication of the storm belt from where larger swell propagates to WA, thus leading

to an increase in HS . However, no significant increases in large wave event heights

were found around the WA coastline over the hindcast period. This suggests that al-

though larger wave events are present in the Southern Indian Ocean their probability

of reaching Australia is reduced with the trend towards a higher SAM index.

� Large wave events do not always result in extreme beach erosion. On perched

beaches, extreme beach erosion may only occur when large wave heights coincide

with a sustained high water level. Also, the amount of wave energy reaching the

shore was sensitive to water level. A 1m rise in sea level could lead to an increase of

3 to 8% in storm wave height.

� Morphodynamic response of perched beaches varied considerably alongshore as a

consequence of variation in the topography of reefs. The variation of the topography

of reefs was responsible for the formation of strong current jets, which enhanced

the alongshore sand fluxes. These jets also enhanced the erosion at the boundary

CHAPTER 8. CONCLUSION 122

between the perched and non-perched beach. These jets also directly influenced the

morphological response of the beach hundreds of meters away from the reefs.

� Reefs can also alter the recovery of perched beaches. Sand accreting every summer

does not overtop the full height of the reef step to come to the beach. Instead a

sand ramp forms along the reef step using the sediment brought in by the sea-breeze

littoral drift. This ramp then allows the sand to reach the lagoon and feed the beach.

Overall the work demonstrates that perched beaches behave quite differently from

normal sandy beaches and therefore they have to be considered separately in coastal

management and coastal hazards inquiries.

The thesis provides innovative methodologies to indentify the behaviour of perched

beaches at Yanchep Western Australia. Such methodologies could be replicated at other

locations and in turn provide valuable coastal management tools including:

� Multi-scale modelling methodology

� Wave events tracking

� GPU simulation of morphodynamics

� Sediment dispersion based on SPH hydrodynamics

Some of these tools are being prepared for public release.

This work also raised a lot of questions on the transport of sand on rough reef flats

and the evolution of perched beach profiles. Answering these questions will require further

field work and fine scale numerical modelling investigations. It is hoped that this work will

inspire further research on the interaction of waves, water level, reefs and sand. I believe

that this thesis has made an important contribution in raising the awareness of the role

of geological structures in beach variability.

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